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Research ArticleA Lightweight Classification Algorithm for External Sources ofInterference in IEEE 802.15.4-Based Wireless Sensor NetworksOperating at the 2.4 GHz

Sven Zacharias, Thomas Newe, Sinead OKeeffe, and Elfed Lewis

Department of Electronic and Computer Engineering, University of Limerick, Limerick, Ireland

Correspondence should be addressed to Sven Zacharias; [email protected]

Received April ; Revised August ; Accepted August ; Published September

Academic Editor: Liqiang Zhang

Copyright Sven Zacharias et al. Tis is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

IEEE.. is thetechnologybehindwirelesssensor networks(WSNs) andZigBee. Most othe IEEE .. radiosoperatein thecrowded .GHz requencyband,which is used by many technologies. Since IEEE..is a lowpower technology, theavoidanceo intererence is vital to conserve energy and to extend the lietime o devices. A lightweight classication algorithm is presentedto detect the common external sources o intererence in the . GHz requency band, namely, IEEE .-based wireless localarea networks (WLANs), Bluetooth, and microwave ovens. Tis lightweight algorithm uses the energy detection (ED) eature (theeature behind received signal strength indication (RSSI)) o an IEEE ..-compliant radio. Tereore, it classies the intererers

without demodulation o their signals. As it relies on time patterns instead o spectral eatures, the algorithm has no need to changethe channel. Tus, it allows the radio both to stay connected to the channel and to receive while scanning. Furthermore, it has amaximum runtime o merely one second. Te algorithm is extensively tested in a radio requency anechoic chamber and in realworld scenarios. Tese results are presented here.

1. Introduction

IEEE ..-based radio chips are low power communica-tion solutions or wireless personal area networks (WPANs)and WSNs. Te IEEE Standard .. (latest version pub-lished in []) denes a physical (PHY) layer and amedium access control (MAC) sublayer or low rate WPANs.

Tis standard is also the base or the two lowest layers o theZigBee standard [] and, thereore, the term ZigBee impliesthe use o IEEE .. in its version rom the year [].Radios based on IEEE .., which are also reerred to asZigBee radios, are ones o the least power consuming radiosavailable today. o save valuable energy, they avoid resendingmessages. Te avoidance o retransmissions implies an avoid-ance o packet collisions (Te term packet is used here orthe physical protocol data unit (PPDU) as in IEEE Standards.Tereore, it is not strictly reerring to the Network Layero the open systems interconnection (OSI) reerence model[] and can also reer to a MAC rame). Tereore, it isan energy-consuming mistake to send at the same time as

a communication partner or an external communicationdevice operating on the same requency.

Tis work investigates the intererence caused by externaldevices, which is reerred to as external intererence in theollowing and in [, ], also called cross-technology interer-ence in [,,] or intertechnology intererence in [,].It occurs because a wireless medium (i.e., a specic radio

requency) is not exclusively reserved or a single technology.Tus, some wireless technologies can jam others. Tis type ointererence causes at least one o the technologies to receivecorrupted messages. Te inerior device is the victim, whilethe stronger sender is the intererer. It might be also the casethat messages o both victim and intererer technologies arecorrupted.

Te main challenge to overcome external intererence isthat different network technologies do not coordinate andhave no knowledge o each other. Tis work aims to changethis situation by giving IEEE ..-based networks with nopossibility to demodulate the signals o other technologies,the ability to classiy these interering technologies in their

Hindawi Publishing CorporationInternational Journal of Distributed Sensor NetworksVolume 2014, Article ID 265286, 24 pageshttp://dx.doi.org/10.1155/2014/265286
http://dx.doi.org/10.1155/2014/265286http://dx.doi.org/10.1155/2014/265286


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International Journal o Distributed Sensor Networks

requency channel. With the help o the resulting knowledge,they can adapt their communication by choosing a betterchannel or other mitigation strategies. Te ollowing sectiongives a short insight into the . GHz requency band andshows the increasing need to address the issue o intererencein this requency band.

2. The Crowded 2.4 GHz Frequency Band

Te original IEEE Standard ..- [] supports threelicense-ree industrial, scientic, and medical (ISM) bandswith one channel at . MHz in Europe (regulatedby the European elecommunications Standards Institute(ESI)), ten channels at MHz in North America(regulated by the Federal Communications Commission(FCC)), and nally channels in the . MHzrequency band or worldwide use.

Te . GHz requency band is predominantly chosen,which is due to a aster data rate and a worldwide customer

audience. Furthermore, it has no additional limitations onits channel use (e.g., the maximum duty cycle is limited to% in the MHz band). However, the . GHz requencyband is not exclusively used by IEEE ..; many othertechnologies also operate in the band. Te main users arepresented in the ollowing.

Te IEEE . Standards are a collection o standardsdescribing the two lowest layers o WLANs, which arenowadays omnipresent. Some o the standards are not usedanymore (as the outdated original IEEE Standard .,also known as legacy mode) and a ew do not work inthe . GHz requency band. Tus, the standards .b,.g [], and .n [] are o interest in the ollowing.

Te commonly used term Wi-Fi stands or an industryconsortium and is also a trademark or hardware that iscompatible with other Wi-Fi hardware.

Bluetooth [] is a wireless standard or WPANs. Te IEEEapproved and standardized older versions o the Bluetoothtechnology (Version . and .) in the IEEE Standard ..[]. Further, note that, throughout this work, only theconnection state o Bluetooth is considered: there are otherstates, or example, inquiry and page, which behavedifferently in the way that, or example, they have a channelhop rate o , hops/s. Tese other states are, or example,used during the connection setup but not or the exchange oapplication data.

Microwave ovens are common kitchen appliances with-out any intention to emit waves outside the shielded cook-ing chamber. Nevertheless, due to imperect shielding, thecooking process with waves around a center requency o. GHz leads to emissions outside the cooking chamber[]. Additional to the microwave ovens commonly used indomestic areas, there are commercial ovens [] only oundin gastronomy, which are not urther considered here.

Figure gives an overview o the spectral eatures othe prevalent technologies and a rst impression o thecrowdedness o the spectrum. WLANs are omnipresent andofen congured according to a rule o thumb: the WLANsdo not interere with each other when WLAN channels ,

, and are used. Tis rule leaves WSN channels , ,, and less or not interered with by WLANs, sincethey are within the guard bands o the WLAN channels.Tereore, these WSN channels are the best choices or IEEE... Tis channel alignment is shown inFigure in lightgray.

Since WSN channel is as ar away as possible rom aused WLAN channel, using this channel is the common solu-tionor WSNs.Channel isalsopreset in the two main WSNoperating systems (inyOS and ContikiOS). However, thesechannel patterns are based on North American requencyband restrictions.

In Europe, the situation is different, since two additionalWLAN channels (, ) are available. In practice, WLANdevices used in Europe requently use the North Americanchannel alignment due to compatibility reasons, but they arenot restricted to it. In Europe, the ideal WLAN channelsto provide the lowest inter-WLAN intererence are , , and. Consequently, WSN channels , , , and are lef

uninterered with, as shown inFigure in dark gray. Hence,the deault WSN channel is interered with by a WLANoperating on WLAN channel .

Furthermore, the channels, which seem to be uninter-ered due to the channel alignment o IEEE ., can beinterered with by out-o-band energy. As shown later inthis work, the out-o-band energy relates to the distancebetween intererer and victim device. Tereore, the problemo intererence accumulates when IEEE . and IEEE.. operate in close proximity or even inside a singledevice.

In addition to the intererence caused by IEEE .-based WLANs, there are urther sources o intererence that

potentially interere with at other requencies. Bluetooth andmicrowave ovens are shown in Figure ; additionally, thereare proprietary wireless devices that could use ranges othe requency spectrum. Furthermore, multiple WSNs usingchannel could result in inter-WSN intererence. o date,most WSNs occupy the channel only shortly due to powerconserving reasons, but some uture applications can resultin high channel utilization.

Finally, the intererence between different technologiesis currently only solved by using IEEE .. channel, which can be regarded as an unreliable and provisionalsolution. o overcome this situation, different intererencemitigation approaches can be used. Since the sources o

intererence vary in their behavior, adaptive approachesaddressing each possible source o intererence with an indi-

vidual strategy are efficient and have been suggested recently[, ]. Although intererence mitigation strategies arebeyond the scope o this work, the intererence classicationalgorithm presented here is a crucial building block o suchsel-adjusting intererence mitigation approaches. Further-more, the algorithm can support deployment planning []or parts o it can be used a as a low power preswitch or IEEE. network interace cards to conserve energy on laptopsor smartphones [].

Tere are more sources o intererence present in the. GHz requency band, or example, DEC phones or pro-


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2 43 5 6 7 8 9 10 11 12 132412 2417 24272422 2432 2437 2442 2447 2452 2457 2462 2467 2472

1 142484

(North America)

2 43 5 6 7 8 9 10 11 12 132412 2417 24272422 2432 2437 2442 2447 2452 2457 2462 2467 2472

1 142484

IEEE 802.11b

IEEE 802.11b

(Europe)

782402 2480

(class-dependent)

Bluetooth

0

2405 2410 2415 2420 2425 2430 2435 2440 2445 2450 2455 2460 2465 2470 2475 2480

Microwaveovens(depending on model)

11 1312 14 15 16 17 18 19 20 21 22 23 2524 262405 2410 2415 2420 2425 2430 2435 2440 2445 2450 2455 2460 2465 2470 2475 2480

ChannelFrequency (MHz)




Frequency (MHz)

IEEE 802.15.4

22 MHz

7 9 channels

1 MHz

2 MHz

Typically0 dBmAt least 3 dBm

0/4/20 dBm

Max.20 dBm

F : Overview o the . GHz requency band as used by different technologies. Bold channels are the most requently used ones: orIEEE ., the nonoverlapping(orthogonal)channels areused to achieve maximum WLAN perormance without inter-WLAN intererence.Tisleaves some IEEE .. channels in theguardbandsas less interered channels and, thereore, they are thebest choiceor IEEE ..(channel alignment). Te channel widths are an approximation o the bandwidth o the signals. Te channel powers reer to the ull channel.Do not scale spectral mask or output power rom this drawing.

prietary wireless solutions. European DEC phones shouldnot operate in the .GHz requency band, but in the rangerom.to.GHz[]. However, some phonesare reportedto operate at . GHz [], but these are only used in NorthAmerica.

Furthermore, there are wireless input devices or personalcomputers that are not based on Bluetooth as wirelesspresenters, keyboards, or mice. For example, the companyLogitech sells a proprietary wireless technology [] that hascomparable eatures to Bluetooth but uses requency agilityinstead o requency hopping. Tis means that the channel isonly changed when it is interered.

However, the presented sources o intererence are themost common ones and are researched in this work.

Section aims to develop an approach to detect and toclassiy sources o intererence based on the channel statusrequested with the help o the Clear Channel Assessment(CCA).

3. Related Work

Te topics o detecting and classiying sources o intererencehave gained more attention in the last ew years, which isdue to their high importance in real-world deployments andthe increasing use o the . GHz requency band. While

intererence detection is a term or noticing a source ointererence, intererence classication reers to a processwhich includes a distinction between different classes andreturns the class o the intererer. Te classes are mainlycorresponding to transer technologies, as IEEE . orBluetooth.

Te ollowing overview o literature is structured accord-ing toFigure , which shows a possible taxonomy based onthe method used to classiy the source o intererence. In thegure, the main differentiation is made between an activeclassication process and a passive process that does notrequire any sensing additionalto the normal communication.Te rst case includes the majority o approaches, which


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Interference classification withIEEE 802.15.4-compliant radios

Passive

Corrupted packet inspection

Hermans et al. (2013),Rensfelt et al. (2012),

Hermans et al. (2012) andNicolas and Marot (2012)

Active

Energy detection

Channel sweep

Modified hardware

Ansari et al. (2011)

No additional hardware

Chowdhury and Akyildiz (2009)and Bloessl et al. (2012)

Single channel

Zhou et al. (2010),Zacharias et al. (2012) and

Zacharias et al. (2012)

Probing packets

Zhou et al. (2005)

F : Overview o literature structured by classication method.

are then urther subdivided. Additional probing packetsadding overhead can be used. However, the most commonapproach is using the ED to monitor either the channel orthe ull spectrum. Te passive classication with the help ocorruptedpackets hasbeen published only recently andoffersa new approach, which is discussed in detail later.

A radio intererence detection protocol or WSNs is pre-sented by Zhou et al. [], which is based on sending packetswith different power transmissions. Tey detect only internalintererence but deal with the hidden terminal problem.

An approach to detect IEEE . is described by Zhouetal.[], being based on the same principles as the approachpresented here. Teir system is called ZiFi and has beenimplemented, or example, on a elosB sensor node. Tesystem uses the sensor node or RSSI sampling and the signalprocessing is computed on a connected computer. Teiralgorithm is based on the beacon rames sent by WLANaccess points (APs) and monitors a single channel. At rst,it takes binarized samples rom the RSSI register. Tis streamis then cleaned up by removing parts where the channel isused or a duration that is improper or a WLAN beacon.Tis signal is then processed by the Common MultipleFolding algorithm, which is also presentedin their paper. Tisalgorithm nds the requency component o the signal ordifferent periods. Unlike the authors o this paper, Zhou etal. [] consider different beacon intervals compared to thedeault time units (tu) to be relevant. A tu equals .ms and is used due to the simple implementation using abase o two. Robustness o this detection has been tested ordifferent amounts o IEEE . data traffic and the cross-

sensitivity has been validated or ZigBee traffic. While theapproach to detect different beacon periods ( tu) canbe argued to be an enhancement compared to the algorithmpresented here, the authors o this work are not able to relateto the decision o Zhou et al. [] to use the unusual beaconperiod o . ms = . ms throughout all theirexperiments. Te authors o this work argue that a beaconinterval o . ms is sufficient and predominantly used (seeSection .and able ). Te envisioned applications are alsodifferent since Zhou et al. [] use their algorithm as a lowpower preswitch or IEEE . network interace cards toconserve energy on laptops or smartphones. Te potential otheir algorithm or WSNs is not discussed.

Te algorithm presented here is based on ormer workdone by the authors. In a rst approach, a mote Sky sensornode is used to collect one second o RSSI readings sampledwith the help o the Frossi Sofware []. Te collected data isclassied in MALAB [] on a connected laptop; thus onlyan offline classication o the sourceo intererence is possible[]. However, the sampling rate o Frossi is not always stableand thus the eatures used or the classication are differentto the eatures used in this work. Also the offline nature o thework limited the application, but it was a proo o concept.

In [], a live version o the algorithm is shown, whichis based on a setup comparable to the work presented here.Te sampling o RSSI readings is done or a second with, Hz and the readings are binarized and stored. Afer thesampling, timing eatures o the binarizied RSSI trace areextracted and nally a classication decision returns the classo intererence.

Nevertheless, the algorithm presented hereis an enhance-ment o the ormer work: it uses CCA requests instead oRSSI readings. With the help o the aster CCA request, thehere presented algorithm supports aster decisions with thepossibility o an abort (less execution time means less energy-consuming channel sensing). It also relies on improvedcriteria enabling better classication results with sound eval-uation.

Chowdhury and Akyildiz [] present both an approachto classiy intererence by RSSI noise oor readings o aCC radio and a scheme or channel selection and MACparameter adjustment. Tey use a ull spectrum scan, whichis matched to a premeasured pattern o an IEEE .b-based

WLAN and a microwave oven. Te main points o criticismor their paper are the small number o researched devicesand the act that important parameters, as the sampling rateand number o samples, are not given.

Bloessl et al. [] present a ramework to utilize a elosBsensor node or spectrum scanning. Te spectrum scans canbe congured with the help o a job description language.Further, they give an outlook on how to detect IEEE .networks using the ramework.

WiSpot by Ansari et al. [] is an IEEE . networkdetection tool that uses modied hardware based on theelosB sensor node by connecting two nodes thus creating aradio array. With the modied hardware,a ull spectrum scan


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is done and IEEE . networks are ound by their spectraleatures.

Hermans et al. [] and Renselt et al. [] proposeSoNIC, a system consisting o a classication method andcountermeasures to mitigate the effects o intererence. Teclassication method uses individualcorruptedIEEE ..

packets and gathers the data only in periods o normaloperation. Hence, the system can be more energy conservingthan active sensing. However, as described in [], packetssent under intererence can be either lost (not received) orreceived. Te received packets can be correct (which meansthat the intererence did not affected the link) or corrupted.Te corrupted packets can also be partly (leading to less accu-rate classication) or ully interered with by the intererer.Hermans et al. [] state that the ratio o corrupted packets is% to% i a link has a packeterror rateabove %.Further,only packets with a payload greater than or equal to bytesare used or classication. o get all eatures needed or theclassication, a successul retransmission has to be achievedso that the position o the corrupted bits in the message canbe obtained due to comparison o the corrupted packet andthe correct packet o the retransmission. Te classicationrate based on a single packet seems low compared to theother approaches (almost down to only % or microwaveovens and IEEE .). However, to avoid misclassications,multiple classication results are combined. A time span o s or s is monitored until the nal decision about themitigation strategy is made []. SoNIC collects eaturesbased on RSSI, link quality indication (LQI), and corruptedbits rom the corrupted packets. Tese eatures were thenused to build a neural network (eed-orward articial neuralnetwork) [] or a decision tree to classiy the data [,].Renselt et al. [] report a decision tree consisting o nodes using ten eatures. Hermans et al. [] state nodesor the decision tree using six eatures. Te big number onodes compared to the number o eatures raises the questionthat the decision trees might be overtted. Te system isimplemented in ContikiOS on a elosB sensor node. Telatest version presented in [] is extensively tested in acontrolled and uncontrolled environment. SoNIC is based onthe work o Hermans et al. [] in terms o using the datasetcollected in a radio requency anechoic chamber.

Hermans et al. [] present an earlier stage classicationmethod that uses the same eatures collected rom corruptedpackets but classies the data with support vector machinesand xed and oating point neural networks. All SoNIC

versions classiy the packets into one o the ollowing groups:IEEE .b/g, Bluetooth, microwave oven, or insufficientsignal strength.

Nicolas and Marot [] present an approach called FIM,which identies the type o intererer. As Renselt et al. [],they use the bit error pattern o a received but corruptedpacket. Teir approach divides into IEEE .b, Bluetooth,and weak IEEE .. links. Finally, they propose interer-ence mitigation methods and, in an initial test, they showthe efficiency o their classication and a subsequent linkadaptation. Although their approach is promising, they donot present results or newer versions o IEEE ., becausethey argue that IEEE .g would back off or IEEE ..

due to its CCA threshold, but this is not always the case dueto different CCA modes, transmit powers, and sensitivities[]. Furthermore, they do notdiscuss differentIEEE ..packet lengths.

Te positions o erroneous bits within an IEEE ..packet interered with by IEEE . differ depending on

the distance between victim and intererer. Liang et al. []state that, in the symmetric region, errors occur primarilyat the beginning o a packet due to an incompatible backofftime o IEEE .. In the asymmetric region (IEEE .is not aware o IEEE .. anymore), the corrupted bitsare uniormly distributed within the packet. Tis distributionmatches the descriptions in [, ] and, thereore, it canbe assumed that their classication approaches are designedor this region.Figure shows the different distributions ocorrupted bits in IEEE .. packets under IEEE .gintererence in the symmetric and asymmetric region.

Te Bluetooth classications in [,,,] make nodifference between single- and multislot Bluetooth links,which are introduced in Section .and are obviously di-erent in their intererence pattern. Te authors assumethat especially the bit error pattern o a corrupted packetdiffers depending on the length o intererence, which isdifferent with regard to the Bluetooth link and packettypes. Intererence classication based on corrupted packetsworks or intererence on the receiver side, while sender-side intererence is not mentioned. Since there is a CCA-based backoff or microwave oven intererence [], an ED-based CCA mode can be assumed and, thereore, sender-side intererence can be caused by external intererers. I thepackets arrive correctly (due to a high signal to intererenceratio), no intererer classication is possible, while the trans-missions might be suppressed or delayed due to sender-sideintererence.

While the approaches reviewed so ar concentrate onIEEE . as sources o intererence, Airshark [] detects aull range o wireless devices and provides the characteristicsor these devices, with the help o a Wi-Fi network interacecard. An off-the-shel Wi-Fi network interace card in alaptop is used to sample the noise oor with the help oRSSI readings. But while the IEEE .. radios are able todetect the energy o a MHz wide channel, IEEE . cardssample over a single MHz wide channel and provide atbest inormation or a resolution o . MHz (orthogonalrequency-division multiplexing (OFDM) subcarrier spac-ing). Te sampling rate is stated with roughly . kHz. In the

ollowing signal processing phase, eatures can be extractedand classied based on a decision tree. Te computing powero a laptop allows or a simultaneous real-time detectiono different classes. Although the results o Airshark arecompelling, the hardware used and the ull spectrum scan isnotcomparable to the possibilities o a single sensor node thatstays connected to its network.

Lietal.[] present the main spectral and time eatures oIEEE ., Bluetooth, and ZigBee and how to identiy thesetechnologies with a GNU radio []. Tey also highlight theimportance o beacon rames sent by wireless access pointsand use a Fast Folding Algorithm to detect periodicity or arange o periods. Te Fast Folding Algorithm is also the basis


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Bit position

Frequency

(%)

0 128 256 384 512 640 768 896 1024

0

5

10

15

20

(a) In the symmetric region

Bit position

Frequency

(%)

0 128 256 384 512 640 768 896 1024

0

1

2

3

4

5

(b) In the asymmetric region

F : Distribution o bit errors in IEEE .. packets corrupted by IEEE .g. In the symmetric region, collision at the beginning oan IEEE .. packet is predominant. In the asymmetric region, the distribution looks signicantly different; the bit errors are distributeduniormly. aken rom [].

or the Common Multiple Folding used in []. Hence, thesampling rate o the GNU radio is in the range o millionsper second; more time eatures as short interrame spaces canbe used or identication compared to in the RSSI traces o

sensor nodes.

4. Classifying Sources of External Interference

At rst, in this section, the ED eature o IEEE ..is analyzed. Te ED builds the base o the classicationalgorithm. All interering technologies are then reviewedwith a ocus on their temporal eatures and the algorithm ispresented with its decision criteria.

.. IEEE Standard ... Te IEEE Standard ..supports an unscheduled network access approach knownas carrier sense multiple access with collision avoidance(CSMA-CA). As part o it, the so-called Listen Beore alkapproach monitors the channel. CCA is used to monitor thechannel beore sending. IEEE .. uses one o at leastthree modes to perorm a CCA. With the latest version o thestandard [], new CCA modes have been introduced (mainlyor ultra-wideband (UWB) communication), but they are noto urther interest here. For more details on CCA modes,Ramachandran and Roy [] give a detailed review o CCAmodes o wideband transmitters. CCAModes (energyabovethreshold) and (carrier sense or energy above threshold) arethe modes o choice to avoid external intererence. Te samemechanism o ED is also used or the channel scans required

by IEEE .. and the ZigBee standard.For the practical part o this work, a mote Sky sensor

node [] was used. Tis node is a typical sensor nodebuilt o commonly used components and can be ound inmany applications. Te node is identical in construction tothe elosB sensor node [] and is supported by the majorsensor node operating systems such as inyOS [] andContikiOS []. All the sofware used in the ollowing wasdeveloped in ContikiOS .. In the ollowing, the radio chipo the mote Sky is its most important unit: It is a ChipConCC . GHz radio requency transceiver []. Inable ,the eatures relevant to the ED o this radio are compared tothe requirements o [].

Te ED value is better known as RSSI value and is roughlythe signal power received at the radio and, thereore, canbe treated as power ratio and with the help o an offset oapproximatelydB []; the RSSI value o the CC

radio can be roughly mapped to a dBm value indicating thepower o the channel.

It has to be mentioned that the signal is measured overan approximately MHz wide channel, as dened by IEEE... Hence, i a signal is narrower than MHz (e.g.,Bluetooth), the measured value will be smaller than thesignals peak energy. Te RSSI values, which are also the baseor the CCA decision, are internally sampled over symbolperiods ( s), which roughly corresponds to the , Hzsampling rate ( s) used here.

An implementation detail to collect errorless RSSI read-ings is that the peak detectors in between the amplier stagesare activated []. Te intererence classication algorithm

presented later uses merely binary channel states, namely,clear or busy. Te channel state is sampled with the help othe CCA command in deault CCA Mode with the presetCCA threshold o dBm at , MHz.

.. IEEE Standard .b, g, n. Te IEEE Standard .with all its different versions is not only various in terms oits modulations (seeable ) but also very inhomogeneousin terms o traffic and duration o channel access.

A major eature that is equal throughout different IEEE. networks is the beacon rame sent by the AP o theWLAN, as also highlighted in [,,]. Te AP is the cen-tral instance,which organizesthe network, and, normally, it is

also a router that connects a local WLAN to the Internet. Tebeacon rames are sent periodically by the AP to announceand to maintain the network. However, beacon rames haveno reserved time and i the channel is busy due to datatraffic the beacon will be delayed and the next beacon will betransmitted according to the original schedule as shown inFigure . o provide maximum backward compatibility, thebeacon rames are normally sent with the lowest data rate,that is, or Mb/s. Te actual minimum airtime o a beaconrame depends mainly on our parts: the preamble ( s orthe longer PHY Layer convergence protocol (PLCP) header),the MAC header ( bytes), the cyclic redundancy check(CRC) ( bytes), and the actual MAC data. Depending on the


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: Selected parameter specicationsor an IEEE ..-compliant receiver, its ED requiredby [] and the correspondingspecicationso a CC radio [].

IEEE .. requirement ypical value o a CC radio Unit Comment

Sensitivity < dBm

Dynamic range > dB

Accuracy dB

Linearity dB

Average ED time s symbol periods

Adjacent channel rejection dB Desired channel

Alternate channel rejection dB Desired channel

: Key eatures o the different versions o IEEE Standard . operating in the . GHz requency band.

IEEE .b IEEE .g IEEE .n

Initial release year

Use in Expiring Widely used Growing use

Maximum theoretical data rate (Mb/s) up to . or . (channel bonding)

Spreading scheme DSSS OFDM OFDM

Modulations DBPSK, DQPSK BPSK, QPSK, -QAM, -QAM BPSK, QPSK, -QAM, -QAMChannel width (MHz) or (channel bonding)

DSSS: direct-sequence spread spectrum; OFDM: orthogonal requency-division multiplexing; DBPSK: differential binary phase shif keying; DQPSK:differential quadrature phase shif keying; BPSK: binary phase shif keying; QPSK: quadrature phase shif keying; QAM: quadrature amplitude modulation;and simple channel model.

: Features o beacon rames rom observed APs. More APsthan networks (based on service set identier (SSID)) mean that thenetwork was built o multiple APs or better coverage.

Environment APs/networks

Beaconinterval

Frame length Data rate

Office / tu bytes Mb/s

Mb/sResidential / tu bytes Mb/s

AP and the network eatures, the MAC data o a beacon candiffer in size. Assuming that a beacon rame has only byteso payload and is sent with a data rate o Mb/s, anairtime oroughly . ms can be taken as minimum. Ansari et al. statea minimum time o . ms [], while Zhou et al. claimthe minimum airtime o beacon rames to be . ms [].Tese are time durations that can be measured with a samplerate o , Hz, which is used in the ollowing. Seeable or an example o typical beacon properties. Although this

table is showing a limited data set, it gives a typical exampleor real-world WLAN deployments. Based on experience, theauthors assume a beacon interval o tu or the rest o thiswork, since this is the deault value, and the authors have notseen any other parameter in deployed networks. Te supporto a range o beacon intervals increases the computationalcomplexity o the classication and covers only rare specialcases. In ad hoc IEEE . networks (independent basicservice set (IBSS)) the master generates beacon rames.

Te rest o the IEEE . traffic varies too much tobe used or classication, with many inuencing actors asdata rate/modulation, numbers o participants, and high-level applications. I the link quality between AP and client

changes, the link eatures or the data traffic, includingmodulation, can also be altered on the y. Tus, by usinga more reliable modulation, a better link is provided. Tisadaption is called automatic data rate scaling [].

Additionally, the RSSI sampling rate o IEEE ..-compliant radios is not high enough to detect more sophis-

ticated temporal eatures o IEEE . as interrame spaces,which would be benecial or traffic classication.

Te channel can be utilized rom less than % (onlybeacon rames) up to nearly the whole time (saturated traffic)[]. An example o an RSSI trace o IEEE . traffic witheasily identiable beacon rames is shown inFigure . It canalso be seen that there is a differencebetween theenergy levelso the beacon rames and the data traffic. In this particularsetup, the sensor node collecting the RSSI trace was nextto the client laptop, while the AP was a ew meters away.Nevertheless, by relying on beacon rames only (as mostother approaches ound in literature [, , ]), there isthe case lef o being only under the intererence o a client

but being outside the range o the AP. However, this caseis unlikely, since the AP (mains-operated) normally sendswith higher power than the client (ofen battery-operated).It is not uncommon to have an AP with a transmit power o dBm and a WLAN interace card sending with dBm orless to save power. In theory, our times the power ( dB)doubles the range, though this is only the case in an idealenvironment. Furthermore, WLANs are also mostly usedin buildings where walls have a great impact on the range.In addition, the dominate traffic pattern o WLAN is thedownstream rom the AP, since most clients request data, orexample, rom the Internet, and the AP delivers it. Tus, thechance o a situation, in which the client is causing serious


8/25


0 100 200 300 400

Time (ms)

Signa

lpower

(dBm

)

BeaconBeacon

Beacon Beacon

100

90

80

70

60

50

40

30

20

F : ypical RSSI trace o a WLAN. CCA threshold o dBm shown in red. Data collected with the help o [].

782402 2480

ChannelMHz

0

tt 1 t 2t 3t 4

F : Bluetooth spectrum use due to channel hopping.

f(k)

f(k)

625s

f(k + 1) f(k + 2) f(k + 3) f(k + 4) f(k + 5)

f(k)

f(k + 3) f(k + 4) f(k + 5)

f(k + 5)

f(k + 6)

f(k + 6)

f(k + 6)

F : iming o single- and multislot Bluetooth packets. akenrom [].

intererence but the AP cannot be detected by the sensornodeanymore is unlikely.

.. Bluetooth. Bluetooth uses requency hopping on thePHY Layer; thus the effect o Bluetooth in a MHz wideIEEE .. channel is limited. Tree MHzwide Bluetoothchannels partly overlay with an IEEE .. channel andthereby even permanent channel usage results in 3 1/79.Figure shows the spectrum use o Bluetooth. Furthermore,Bluetooth uses time division multiple access with time divi-sion duplex (DMA/DD) to organize the channel access.Tus, the communication between the master o a piconetand its slaves uses alternative time slots. Te master pollsdata rom a slave and this interaction takes place in twoconsecutive time slots. Due to the scheduled access, thechannel is not monitored, since it is assumed to be ree, at

least o internal intererence. But, i packets on a channel arelost, the channel can be blacklisted or later transmits. Tisscheme is called adaptive requency hopping (AFH).

Another eature o Bluetooths architecture is the sup-port o ve different logical links or also called logi-cal transport types. Te link types used or data trafficcan be roughly divided into synchronous links, includ-ing synchronous connection-oriented (SCO) and extendedsynchronous connection-oriented (eSCO) links, and asyn-chronous connectionless (ACL) links. Te SCO links arenormally used or voice transer and are strictly based onsingle-slot packets, which are not retransmitted in case o aloss. Te newer eSCO links are also used or voice transer, butthey support limited retransmissions and their packet lengthsare more variable than the SCO packet lengths. Te reliableACL links are packet-based and can use one, three, or veslots. Furthermore, it has to be mentioned that there are twoadditional link types, the active slave broadcast (ASB) andparked slave broadcast (PSB) links, which are only used orcontrol and network maintenance and are not considered inthe ollowing. Te link type determines the used packet.

Te packet ormat, modulations, and data rates o Blue-tooth are not dealt with in detail, since they are beyond what ismeasurable with an IEEE ..-compliant radio. However,the given time slot is a maximum time, which should neverbe used ully due to guard times. Te transmission start time

is a clear indicator o Bluetooth communication, becausetransmissions start with the beginning o a time slot (asshown inFigure ) and thus time Xstart() = Xstart(0) + 625 s. Tis timing pattern and other typical eatures asthe maximum busy channel duration can be seen in Figure .

.. Microwave Ovens. Although the spectral spread and thepower o the leaking radiation differ, all three microwaveoven models researched by the authors show similar patterns:the strongest intererence occurs on a channel close to IEEE.. channel , which is around the stated microwaveoven center requency o MHz (normally the requency


9/25


0 15 30

Time (ms)

Signa

lpower

(dBm

)

Channel busyfor less than

100

90

80

70

60

50

40

30

20

625s

(a) Single-slot Bluetooth packets

0 15 30

Time (ms)

Signa

lpower

(dBm

)

Channel busyfor less than

betweentwo rising

edges

100

90

80

70

60

50

40

30

20

5 625 s

n 625s

(b) Multislot Bluetooth packets

F : ypical RSSI traces o a Bluetooth communication. CCA threshold o dBm shown in red. Data collected with the help o [].

0 10 20 30 40 50

Time (ms)

Signa

lpower

(dBm

)

Heating

Plateau

Spike

/risinge

dge

Spike

/fa

llinge

dge

Pause

100

90

80

70

60

50

40

30

20

F : ypical RSSI traces o microwave ovens. CCA thresholdo dBm shown in red. Data collected with the help o [].

is stated with other device properties on the back side othe oven). Te signal is periodic with a requency around Hz, which is the requency o the power supply (or North

America a requency around Hz can be expected). In aperiod o ms, there are an active phase and an inactivephase, which are roughly o the same length. Te active phasehas two maxima, one at the beginning and one at the end. Inbetween them is a plateau. Te height o this plateau differsdepending on the oven model, the time, and the channel, butit is generally higher as it is closer to the center requency. InFigure , these timing patterns are shown.

Furthermore, microwave ovens have different programsor different power levels that can be chosen by the user.However, the magnetron that emits the microwave radiationcan only work at ull power. Te user-set power level isachieved by pauses between the heating phases. Te active

and inactive phases o a Hz period are not altered. Afera ew seconds o heating, a ew seconds are given or theheat to spread. Tis heat spreading times can be easily heardwhen the microwave oven is not buzzing and when only the

ventilation and the turntable operate.

.. Classication Algorithm. As already explained, an IEEE..-compliant radio has with the help o the ED thechance to detect the increased power in its channels causedby signals; the radio chip doesnot demodulate. Te algorithmpresented here collects data with the help o CCA requests,

which return binary decisions i the channel is idle or busy,at a sampling rate o , Hz. A CCA request is perormedaster than an RSSI request and thereore leaves more timeto process the returned result in between the sampling.Tus, the sample can be analyzed immediately and i a classcriterion is ullled, the algorithm ends beore the maximumruntime o a second and energy can be conserved or asuitable intererence mitigation strategy can be applied. Teclass decision criteria are based on the timing pattern othe channel access and occupation duration o the differenttechnologies. Te eatures computed while sampling can besplit into three main groups.

... Simple Features. Simple eatures, which are maxima orsums, can be easily computed and are listed in the ollowing:

(i) the maximum continuous time duration in which thechannel was busy

max,

(ii) the maximum continuous time duration in which thechannel was idle

max ,

(iii) the channel utilization , which is the number oCCA samples indicating that the channel was busydivided by the number o samples collected.

... Transmission Start Patterns. ransmission start pat-terns are based on the duration between two rising edges


10/25


if(( Hz)>)and(% non)

then return(1)if(

max < , s)and(+(. tu1))

and( > non)then return(2)

if(cu = %)then return()

return()

A : Class conditions ().

Beacon interval

Beacon Busy mediumother transmissionstransmissions

F : Beacon transmission on a busy network. aken rom [].

(idle to busy channel transitions). I the time between twosuccessive rising edges is a multiple o the Bluetooth slot time( s), it is assumed to be a Bluetooth pattern. Te ts andthe mists are counted as Bluetooth slot patterns andnon-Bluetooth slot patternsnon, respectively.

Since the sampling time o / s is not an integermultiple o the Bluetooth slot time o s, the durationcomputation has been implemented in xed-point arith-metic.

... Periodicity. Te periodicity (periodicity), which isa unction returning a metric , here, is computed by asimple algorithm to check whether an input signal (signal) isperiodic. Due to the limited memory and computing powero sensor nodes, a simple approach to nd the requencycomponent or a binary signal has been selected. It is basedon correlation and nds a requency component, since asignal or unction is periodic when () = ( ). Te

sampled signal is processed and the binary value at time is combined with a logical conjunction with the valueo the time , where is the desired period. Tis isdone rom = to = , where is the number osamples. Te resulto each conjunction is added to a temporalarray, buffer, at position (mod ). Te maximum o thistemporal array, buffer, is the requency component . Tis can reach a maximum value o/ 1. Te memoryneeded orbufferis little; only elements have to be held.Te principle o the algorithm is also shown in Figure .Tis algorithm has a lower complexity than a ast Fouriertransorm and does not require oating point numbers as theGoertzel algorithm. ests by the author with a xed-point

implementation o the latter have not provided sufficientprecision or became too slow on the used hardware. Te

classication algorithm presented here uses the periodicityor detecting IEEE . and microwave ovens. Due to theact that the beacon rames are the periodic element or IEEE., but in between them the channel utilization can differextensively, only the busy channel samples have to correlate.Tus theperiodicityunction shown inFigure is modiedto unction+ by just considering samples o thesignal that are. Tereby, the idle channel sections osignaldo not have to align periodically. For the microwaveoven not only the busy channel durations but also the idledurations, which are roughly hal o a period long, have toalign periodically (unction:periodicity).

Tese eatures are calculated and checked while the sam-

pling o CCA request values is running. Te basic conditionsor each class are shown in Algorithm . In Algorithm and inthe ollowing, the classes o the algorithm are reerred to withshort labels: CLEAR or no intererence, BT or Bluetoothsingle-slot packets, BT or multislot packets, WLAN orIEEE .-based WLANs,MWOor microwave ovens, andUNKNOWN or a source o inerence that is not known.Te algorithm has a urther result calledINTERNAL, whichis returned i the sensor node receives a packet while per-orming the intererence classication algorithm. However,theINTERNALclass is not a classication result but is morean interruption o the classication process. Tereore, it doesnot appear in the ollowing test results and its use depends on

the nal application o the classication algorithm.

.. Algorithm Timing. An important requirement is toreceive an immediate result rom the algorithm, since thecommunication between the nodes o a WSN canbe recong-ured aster andenergy canbe saved.Te maximumalgorithmexecution (radio on) time is one second, which is needed todetect Bluetooth (BT,BT) or a clear channel (CLEAR). Techannel hopping o Bluetooth leads to little channel use andthus more time is needed to collect enough data or a reliabledecision. Other decisions can be made quicker. Especially themicrowave oven class (MWO), which is unique in using thechannel heavily with a high requency, can be classied in


11/25


t t + 1t 1t T t T + 1t T 1

T

T

Signal:

1 2 3Buffer:

Return

Buffer[t mod T] += signal[t T] && signal[t]

P = max(buffer)

Fort = T toN

F : Concept o a simple algorithm to detect periodicity/requency componentin a discrete, binary signalsignalor a given periodgiven in samples. Further,bufferis a temporal array o the length .

less time. For a reliable classication, this algorithm relies ona Hz periodicity greater than , which means that, afer completed periods, a sample can ulll the requirements,resulting in a 16 1/50 s= 320 ms minimum execution timeo the algorithm. IEEE . beacon rames (WLAN) have a

slower requency o1000 ms/102.4 ms 9.77 Hzor . tu1;hence the classication needs more time. o reach a thresholdo more than periods, it needs at least 6 102.4 ms =614.4 ms. Te ull algorithm with its conditions and timingsis shown inFigure .

Te algorithm presented here has the advantage that thenode is connected to the network all the time and, thereore,it still can receive messages i the intererence is nottoo heavy.Nevertheless, when a message is received in the samplingprocess, the algorithm is stopped and the INTERNAL classis returned, since the received message also affects theCCA sampling. Te problem o internal intererence canbe solved by an explicit sampling phase or the networkcoordinated by a central manager as it is suggested in [] orintererence reporting and resolution. Te nal application othe presented intererence classication algorithm is beyondthe scope o this work. However, as already mentionedin the literature review (see Section ), there are multipleapplications or the intererence classication algorithm (e.g.,effective intererence mitigation [, ] or deploymentplaning []) or or parts o it (e.g., low power WLANdetection []).

5. Algorithm Testing

An extensive measurement campaign was conducted to testthe algorithm: at rst, it was tested with selected devices andreproducible data traffic in a controlled environment, that is,a radio requency anechoic chamber (shown in Figure (b)).Secondly, the algorithm was tested in a real-world scenario.Te implementation o the algorithm used here classies achannel three times successively andthen changes to the next,higher channel. Afer channel is classied three times, theclassication restarts at channel . TeINTERNALclass was

not tested, since it is not a classication result but is more aninterruption o the classication process. Tereore, it doesnot appear in the ollowing results. Te hardware used inthe ollowing experiments is listed in detail inable . In theollowing, it is reerred to as the device names given in the rstcolumn (or instance, when the word Laptop is used startingwith an upper case letter, it stands or the model Dell LatitudeE).

.. Controlled Environment. In the controlled environment,a radiorequency anechoic chamber, experiments with repro-ducible traffic patterns were conducted. First the WLANclassication is tested, starting with high channel utilization

(i.e., low data rate traffic), which makes the beacon ramessent by the AP harder to distinguish rom the rest o thetraffic. Te medium channel utilization used next might havesimilarities to the pattern generated by microwave ovens.Ten, a less utilized channel is researched (i.e., high data ratetraffic), where the beacon rames stand out more, but themodulation schemes change between beacon rames and datatraffic. For this, the channel utilization might be so low that amisclassication asBTcould happen.

Te next batch o experiments deals with the classicationo Bluetooth, where the unexpected, irregular channel selec-tion o the Laptop is uncovered. Additionally, a real WLANand a mixed environment o IEEE . and Bluetooth are

tested.Finally, the detection o theMWOclass is evaluated.

... IEEE Standard .b, g, and n. Te IEEE Standard. affects at least our IEEE .. channels (seeFigure ). Te setup shown in Figure (a)was used to testthe presented algorithms ability to classiy IEEE . inter-erence. Te intererers, Access Point and the Laptop, wereplaced m away rom each other. Tree mote Sky sensornodes running the intererence classication algorithm wereplaced in the middle between Access Point and the Laptop.Te Netbook that generated the data was connected to AccessPoint via Ethernet, which then transmitted the data to the


12/25


INTERNAL: IEEE 802.15.4 packet received

Timet (ms)

10000 320 400 615

MWO:(periodicity (20 ms) > 15)

and(30% < cu < 70%)

UNKNOWN: // (no WLAN) and (no BT)((tmaxi > 102.4 ms) or

WLAN:

(periodicity+ (102.4 ms) > 5) and (tmaxi < 102.4 ms)

((9-floor (t/102.4 ms)) < (5-periodicity+ (102.4 m))))And

(tmaxb > 3.125 ms)

BT1:

(tmaxb < 0.625 ms) and

(periodicity+ (102.4 ms) 5) and(txBT > txnonBT)

BT2:

(tmaxb < 3.125 ms) and

(periodicity+ (102.4 ms) 5) and(txBT > txnonBT)

CLEAR:

(cu = 0%)

UNKNOWN:

else

F : Flow and timing o the algorithm: the gray parts show the time windows when different classes can be detected and the algorithmcan return beore the maximum execution time.

2 m

Sensornodes

Interferer1

2 m

Interferer2

(a) Setup o the singletechnologyexperiments

(b) Radio requency anechoic chamber

F : Experiment setup.

: Equipment used in the course o this work.

Device rade name Specication

Laptop Dell Latitude E IEEE .n (Intel WiFi Link AGN)Bluetooth . EDR (Dell Wireless Bluetooth)

Netbook Lenovo Se IEEE .g (Broadcom adapter)

Bluetooth . EDR (Broadcom adapter)

Access Point Netgear N wireless router (WNR) IEEE .n

Access Point AVM FRIZ!Box Fon WLAN IEEE .g

Headset Samsung WEP- Bluetooth . EDR

Mobile Phone Motorola Razr vi Bluetooth .

Wireless Keyboard Logitech diNovoMini Bluetooth .

Microwave Oven Matsui W

Microwave Oven Quelle-Schickedanz AG W

EDR: enhanced data rate.


13/25


Laptop via IEEE .. Te WLAN traffic patterns generatedto test the algorithm are described in the ollowing.

Heavy Channel Utilization.o get an idea on how the algo-rithm reacts under heavy channel loads, the tool JPer ..[] was used. Te heaviest congestion on the channel was

generated using the slowest data rate, that is, IEEE .b.Note that, although higher data rates are ofen supported bytodays hardware, the link can all back to a lower data rate (asused in IEEE .b) in bad radio requency conditions dueto automatic data rate scaling (see Section .). Furthermore,with higher data rates, the theoretical, maximum channelutilization decreases []. With high channel utilization theactual beacon ramessent by the AP are less outstanding romthe data traffic.

In the WLAN that was used here, the beacon ramessent by Access Point had a length o bytes at a datarate o Mb/s and were sent at the deault, preset interval o. ms. Te communication between the two IEEE .bcommunication partners took place on channel , whichoverlaps with the IEEE .. channels , , , and .Te theoretical maximal data rate is Mb/s. In the setupused here, a throughput o up to roughly , kbit/s wasachieved. Te test included CP and UDP connections. Tewindow sizes or CP were , ,, and , KBytes. Tewindow size hasan effect on the number o acknowledgmentsand thereore tunes the channel utilization. With eweracknowledgments, ewer responses rom the network partnerhave to be transmitted. Additionally, each test was run ina unidirectional, dual (i.e., alternating directions) and trade(i.e., at rst in one direction, then in the other) mode. ForUDP traffic a MB/s and a MB/s bandwidth links wereused, where the second setup saturated the channel. Tis led

to a maximum airtime-based channel utilization o up to.% over one second on IEEE .. channel mea-sured by the mote Sky sensor node. Tis measured channelutilization is greater than the given theoretical maximum in[], but the ED-based measurements o the mote Sky arenot ast enough to reect the channel utilization ully correct.

Eleven different IEEE .b data traffic settings wereused in total, which resulted in classications (compo-sition: ull spectrum sweep interered with by CPwindow size (WS) KBytes, CP WS KBytes, CP WS KBytes, CP WS KBytes dual, CPWS KBytes dual, CP WS KBytes dual, CP WS KBytes trade, CP WS KBytes trade,

CP WS KBytes trade, UDP Bandwidth MByte,and UDP Bandwidth Mbytes).

Te classication o IEEE . on the our ully overlap-ping channels achieved very good rates, always greater than.% with an average o .%.

However, the adjacent channels and suffered rommisclassications and were only classied with .% and.% asCLEAR. Tese two channels were mainly classiedas UNKNOWN, which can be explained as ollows. Tedata traffic and the beacon rames have different modulationschemes even within the IEEE .b standard. Te beaconrames, sent with Mbit/s, use baseband modulation oDBPSK and the data traffic, sent with Mbit/s, uses the

so-called higher rate -chip complementary code keying(CCK) modulation scheme [].able shows the differentmodulations o different standard versions. Vanheel et al.[] report similar observations, claiming that OFDM has awider spectrum than DSSS. Tis effect will become clearerin the ollowing experiments (seeable ). Due to the close

proximity owing to the limited physical dimensions o theradio requency anechoic chamber, the effect o the differentkeyings/modulations observed here is worse than in mostreal-world setups with greater distances between the devices.With greater distance between the IEEE .. node andthe IEEE . device, the out-o-band energy o the latteris decreased and thus the problem o misclassication onadjacent channels is minimized. Tis decrease can be seeninable showing the results o a setup in which AccessPoint is arther away rom the node in an uncontrolledenvironment.

Also, thevariance between the nodes was very high on theadjacent channels. Tis is due to the act that the nodes were

not synchronized. Tereore, the nodes might have slightlydifferent sampling windows in time.Te rest o the channels which should not be affected by

IEEE . were classied almost alwayscorrectly as CLEAR.Te ew misclassications, decreasing with more distanceo the WLAN center requency, can only be explained dueto out-off-band emissions o the IEEE . devices orerroneous CCA readings.

Medium Channel Utilization. o evaluate the algorithm ormedium channel utilization, different traffic patterns wereused as suggested in []. Te IEEE .b traffic wasgenerated by D-IG [], while the hardware and spatialsetup stayed the same. Rates o , , , , and

CP packets per second, each bytes long, were sent,resulting in theoretical data rates o , , , ,and kbit/s, respectively. Whereas the rate o kbit/shas not been achieved in our setup, only a rate o kbit/scould be measured, which is an acceptable perormance oran IEEE .b network (taking into consideration that thelatterhas only a theoretical data rate o Mbit/s). For all threemote Sky sensor nodes in all ve test cases, the classicationoWLANworked awlessly on channels , , , and .Only a single experiment on a single node had a classicationrate below % being an outlier with .%. Tis results in.% o correctly classied channels , , , and overall experiments. Te adjacent channels, and, showed the

same problem as described in the previous experiment.

Low Channel Utilization. o investigate low channel uti-lization (


14/25


: Controlled environment IEEE . experiments or low channel utilization summarized by channels. Classication results (%) o classications or each channel or different IEEE . versions. Low IEEE . traffic generated by D-IG. Te given result is the meano three nodes and the standard deviation between nodes is in parentheses.

(a) IEEE .b (mainly overlapping channels are bold)

Channel Predicted class (%)

1 2

. (.) . (.) . (.) () () . (.)

. (.) . (.) . (.) () () . (.)

() () () () () ()

() () () () () ()

() () () () () ()

() () () () () ()

. (.) . (.) . (.) . (.) () . (.)

. (.) () () () () . (.)

(b) IEEE .g (mainly overlapping channels are bold)

Channel Predicted class (%) 1 2

. (.) () . (.) () () . (.)

. (.) . (.) . (.) () () . (.)

() () () . (.) () . (.)

() () () . (.) () . (.)

() () () . (.) () . (.)

() () () () () ()

. (.) () . (.) . (.) () . (.)

() () () () () ()

(c) IEEE .n (mainly overlapping channels are bold)


1 2

. (.) . (.) . (.) () () . (.)

. (.) () . (.) () () . (.)

() . (.) . (.) . (.) () . (.)

() () () () () ()

() () () () () ()

() () . (.) . (.) () . (.)

. (.) () . (.) . (.) () . (.)

. (.) () () () () . (.)

(d) IEEE .n channel bonding (mainly overlapping channels are bold)


1 2

. (.) () . (.) () () . (.)

. (.) . (.) () () () . (.)

() . (.) . (.) () () . (.)

() . (.) . (.) () () . (.)

. (.) . (.) . (.) () () . (.)

() . (.) () () () . (.)

() () () . (.) () . (.)


15/25


(d) Continued.


1 2

() () () . (.) () . (.)

() () () . (.) () . (.)

() () () . (.) () . (.)

. (.) () () . (.) () . (.)

. (.) . (.) () () () . (.)

: Controlled environment IEEE . experiments or real-world utilization summarized by channels. Classication results (%) o classications or each channel. IEEE . video streaming with two clients (mainly overlapping channels are bold). Te given resultis the mean o three nodes and the standard deviation between nodes is in parentheses.


1 2

. (.) . (.) . (.) () () . (.)

. (.) () . (.) () () . (.)

. (.) . (.) . (.) . (.) () . (.)

() () () () () ()

() () () . (.) () . (.)

. (.) () () . (.) () . (.)

. (.) . (.) . (.) () () . (.)

. (.) () () () () . (.)

good, only in the IEEE .n experiment (see able (c));a node struggled or the CP experiment on channel or an unknown reason, dragging the average classicationrate down and increasing the standard deviation given inparentheses. For MHz wide channels, the already dis-cussed phenomena o misclassications on adjacent channels

occurred or all versions o IEEE .. able (d) showsanother difficulty regarding IEEE .n using the MHzwide channel bonding. Besides the act that the MHz widechannel jams almost all the available requencies, including,or example, the orthogonal IEEE .. channel (seeFigure ), the second channel cannot be identied by thisalgorithm. Tisis due to the act that the second IEEE .nchannel is not used or beacon rames and actually is onlyconnected or the data exchange between communicationpartners. Te issue o the secondary channel o a MHzwide IEEE .n channel bonding is very challenging and,to the best o the authors knowledge, it has not ound greaterrecognition in theWSNs communityyet andremainsan openresearch question.

Real-World Channel Utilization. Additional to the articiallygenerated data traffic, the algorithm was tested in a morerealistic setup in the radio requency anechoic chamber. woclients were connected to the Access Point : the Netbookwas connected with an IEEE .g ( Mbit/s) connectionand the Laptop with an IEEE .n connection using asingle channel (Mbit/s). Both clients streamed a video. Tespatial setup, which is shown inFigure , was as ollows: theAccess Point was placed . m above the ground, whilethe Netbook was placed m and the Laptop was placed min distance to the Access Point on the ground. Te sensornodes were spread between the Netbook and the Laptop. Te

Heightdifference

1.2 m

3 m

Netbook Laptop

2 m

Access

point1

Sensor

nodes

F : Setup o the experiment real-world channel utilization.

classication results were again compelling, as can be seeninable , showing that the data traffic had no inuence onthe reliability o the AP classication. However, again, onchannel , the results vary mostly between the nodes. Teout-off-band energy leading to misclassications on adjacent

channels increased slightly, since the sensor node was veryclose to the clients, which also transmit to the AP.

... Bluetooth. Te classication quality o Bluetooth wasevaluated in multiple experiments. Te distance between thetwo Bluetooth communication partners was m in all exper-iments described in the ollowing. Te sensor nodes wereplaced in the middle between them, as shown in Figure (a).Te traffic o the Bluetooth connection was monitored onthe LCAP Layer with hcidump [] on the Laptop runningLinux. Te LCAP Layer roughly corresponds to the DataLink Layer o the OSI Reerence Model. Te Netbook usedWindows XP as an operating system.


16/25


: Controlled environment Bluetooth experiments summarized by experiments and details o experiment with the worst classicationrate.

(a) Bluetooth summarized by experiments. Classication results (%) o different Bluetooth experiments classied by single nodes. Te number oclassications is given in brackets. Channel details o the worst results in row Laptop to Netbook (ACL) are shown inable (b)

Experiment Predicted class (%)

1 2 Laptop to Headset

. . . . . .(eSCO)[16 39]

Netbook to Headset. . . . . .

(eSCO)[16 69]

Laptop to Mobile. . . . . .

(ACL)[16 57]

Mobile to Laptop. . . . . .

(ACL)[16 45]

Netbook to Mobile . . . . .

(ACL)[16 66]

Mobile to Netbook . . . . .

(ACL)[16 57]Laptop to Netbook

. . . . . .(ACL)[16 33]

Netbook to Laptop. . . . . .

(ACL)[16 36]

(b) Worst Bluetooth results by channels revealing unused requencies o the Laptop. Detailed classication results (%) o classications per channel.Bluetooth FP traffic (ACL packets) rom Laptop to Netbook. Tis experiment has the worst average classication result o all Bluetooth classications,since some channels (, , , , , and ) are clear all the time


1 2

. .

. .

. .

. .

. .

. .

Mean . . . .

In the rst experiment, an audio le was streamed romthe Laptop to the Headset. Te stream was based on eSCOlinks with inormation bytes packed into an extended

voice (EV) packet sent with an EDR. Te resulting packetsstayed in the time limitation under s. Hence, theaccording algorithm return is BT; the results are shown in therow Laptop to Headset (eSCO) in able (a). Te secondexperiment Netbook to Headset (eSCO) was equal to the

previous, but this time the Netbook was used instead o theLaptop.

Te third experiment was a data transer rom the Laptopto the Mobile Phone. Tis experiment was ollowed by atranser in the opposite direction. Te experiments are shownin the rows Laptop to Mobile (ACL) and Mobile to Laptop(ACL). Again, these two experiments have been repeatedwith the Netbook instead o the Laptop. Finally, the data was


17/25


transerred between the Laptop and the Netbook, with theNetbook supporting a newer version o Bluetooth than theMobile Phone and, hence, the transer was different rom theone in the previous setup. Again, both directions were testedand are shown inable (a).

Although able (a)merely shows theexample results o a

single node orbetter clarity, the results o other nodes didnotvary signicantly. Since the results are already averaged over channels, only a single node with no standard deviation ispresented. However, or cases with a high variance betweendifferent channels, it is discussed in the ollowing.

Te eSCO packets were classied well in Experiment .Inable (a), the sum over all channels is shown or theexperiment, but a detailed view reveals that most channelshad a % classication rate, while other channels had alower rate (down to .%). On these channels, the trafficwas misclassied as UNKNOWN. Experiment reaches anearly % classication rate. Te channels in Experiment are more equally used as by the Laptop. Te phenomenono the unequal channels or all connections with the Laptopoccurs in all the ollowing experiments.

In the remaining experiments, ACL packets were trans-mitted, using one, three, or ve time slots and, hence, makingthe traffic more difficult to identiy. However, as shown inable (a), the classication rates were still satisactory. Notethat almost no misclassications as WLANand no MWOmisclassications were made.

When the Laptop was used as sender, some channelswere unused. Te worst case, occurring in the experimentLaptop to Netbook (ACL), is shown in more detail inable (b). Channels , , , , , and are idle, classiedas CLEAR, most o the time. Since the authors used off-the-shel hardware and driver sofware, the reason or thisis not ully clear. Although the Wi-Fi card o the Laptopwas deactivated during the experiments, a WLAN-Bluetoothcoexistence mechanism possibly could have blocked chan-nels. Te Netbook-based connections show more uniormspread results with all channels being equally, correctlyclassied (with 1 + 2 being .% and .% orexperiments Netbook to Mobile (ACL) and Mobile toNetbook (ACL)).

It could be argued that a longer classication timeimproves the results o the algorithm, but, rom a theoreticalpoint o view, this is unnecessary. A time slot, which isnormally the time the requency is kept, is 1/1600 s. Since themaster has to poll data in a piconet, in the rst time slot, a

packet is requested and then the client keeps the channel or amaximum o ve time slots to send the multislot ACL packet.Tisresults in twochannel changes in six time slots.In theory,this means that at least2 (1/79) (1600/6) 6.75times asecond; the same requency should be used. Additionally, theIEEE .. channel covers three Bluetooth channels and,thereore, the channel should be used sufficiently to detectBluetooth. I the channel is utilized less than that (which canbe the case or some Bluetooth packet types with negotiabletransmit intervals), the sense o intererence classication isquestionable, since the effect o intererence is negligible.

Te last IEEE . experiment, real-world channelutilization, was redone with an additional Bluetooth audio

link generating eSCO traffic. Te video streaming Laptopclient used the Bluetooth Headset to listen to the sound. Allother setup properties, including the Netbook, stayed thesame. Te WLAN was already established and used whenthe Bluetooth connection was established and thus the AFHmechanism or the method used by the Laptop to choose the

channel or Bluetooth had enough time to adapt its channelchoice beore the classication was started. Te results areshown inable and attest the expected behavior: Bluetoothis not detected on the channels used by IEEE . (,, , and ). Tis behavior is expected since the IEEE.requenciesare blacklisted by Bluetoothdue to the usedAFH. AFH works as ollows: Afer each transmission, thechannel changes according to a pseudorandom pattern. I thetransmission ails on a channel, AFH will avoid using thischannel or a predened time. I AFH had not been used, theWLAN traffic would dominate on the overlapping channels,which would make the Bluetooth traffic hard to detect.

... Microwave Ovens. o test the classication rate othe algorithm or microwave ovens, mL o water in aplastic bowl were placed inside Microwave Oven and heatedwith ull power or minutes. In ront o the microwave,nodes were placed . m, . m, . m, and m away. Teclassication results o the most affected channels (, ,, and ) are shown inable (a). Tese channels aroundthe center requency o the microwave oven were classiedmainly correctly.

As or IEEE ., channels arther away rom the centerrequency o the intererer are much harder to classiy sincethey do not suffer rom the typical intererence patternbut rom harmonics. able (b) shows the results o ull

spectrum sweeps or the . m setup, where the node wasclosest to the microwave. On channels arther away romthe center requency, it might happen that the energy is justaround the CCA threshold and only very ew CCA requestsreport a busy channel, which can be mistaken with Bluetooth,since Hz are a divisor o Hz.

.. Uncontrolled Environment. In addition to the testsin the radio requency anechoic chamber, which deliveredresults rom an ideal environment, tests were also conductedin a detached house. Tis added effects as reections andmultipath propagation to the setup. Additionally, the devicesused in these experiments have not been part o any training

set used to develop the algorithm. Tereore, the ollowingtests can be considered to be challenging and ar beyond thetesting reported or the reviewed algorithms inSection .

... IEEE Standard .g. Access Point was in anotherroom on the secondoor; thus the received signal was around dBm at the Laptop next to the sensor nodes on the rstoor. Te distance between the two devices was around mon the plane and roughly . m in height with multiplerooms between them. Te beacon rames were sent in thedeault interval o tu at a data rate o Mbit/s and were bytes long. Te classication algorithm ran or min,resulting in ull channel sweeps. For urther details, see


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: Controlled environment IEEE . and Bluetooth experiment summarized by channels. Classication results (%) o classications or each channel. IEEE . video streaming with two clients, Bluetooth audio streaming (eSCO) rom the Laptop to theHeadset (expected classications are bold). Te given result is the mean o three nodes and the standard deviation between nodes is inparentheses.


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able . Since IEEE .g used channel , the IEEE ..channels , , , and were supposed to be affected. Terewas notably less misclassication on adjacent channels, whichis due to the act that the power spectral density (PSD) othe beacon rames sent with a low data rate modulation hasa distinct maximum at the center requency. Furthermore,

the distance and, thereore, the attenuation in this scenariowere much higher than in the measurementsin the controlledenvironment (see Section ..). Even channels and ,which are ully overlapped by the MHz wide IEEE .channel were less interered and thus less ofen classied asWLAN.

... Bluetooth. o evaluate the Bluetooth classication rate,again, a new untested device was used: the Wireless Keyboardwas connected to the Laptop and placed on the same tableas the sensor nodes and the Laptop. Te classication ranor min resulting in ull channel sweeps. Te testresults were acceptable: over all channels, the1 + 2

classication rate showed an average o .%, .%, and.% or the three different nodes and almost all o theseclassications were the expected BTclass. All misclassica-tionswere CLEAR or UNKNOWNwith no particularchanneldifferences. Since there is not much data to transmit or theWireless Keyboard, it can be assumed that the traffic was

very low and, thereore, hard to detect. However, it is unclearwhy the channel selection was more homogeneous than inprevious tests.

... Microwave Ovens. For this experiment, MicrowaveOven was used to heat mL o water in a plasticbowl or min and the sensor nodes were placed . m

away rom the ront side o the oven. As it can be seeninable , the classication results were only modest. Tebest classication rate was achieved on channel (centerrequency o MHz), while channel ( MHz) wasexpected.

However, these results reect what the channel utilization

shows. Te average value increases at rst rom .%or channel to .% or channel and reaches itsmaxima with .% and .% or channels and .Ten, the value drops to .% on channel . Te actthat microwave ovens are not standardized communicationdevices is reected in the values o these measurements.

... Long-Term IEEE Standard .g. Since all exper-iments described so ar were limited in time duration, a-hour long-term experiment was conducted in the sameresidential environment as all the uncontrolled environmentexperiments in this section. Te channel sweep was timed tostart every two minutes and a channel classication started

every two seconds, with three classications on the samechannel beore the channel was changed. Tus, the earlyreturns did not affect the timing and ull channel sweepswere perormed resulting in , classications per channel.

Access Point was operating on IEEE . channel ,which overlaps with IEEE .. channels , , , and .Duringthe experiment, multiple laptops,a desktop computer,and a smartphone have been active as clients. Additionally,Bluetooth traffic was generated by the Wireless Keyboard,which was connected to a generic Bluetooth dongle pluggedinto the desktop computer.

Tis experiment generated a trace o the algorithmoutput over a long time. However, since this experiment was


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: Controlled environment microwave oven experiment summarized by distance and details o node closest to the oven.

(a) Microwave oven summarized by distance.Summedup classication results (%) o IEEE .. channels , ,, and . Microwave Oven heating mL water at ull power. Te number o samples per channel is = average over results shown per setup. Channel details o the nearest node inrow . m are shown inable (b)

Distance Predicted class (%)

1 2 . m . . .

. m . . .

. m . . .

. m . . .

(b) Microwave oven summarized by channels. Detailed classication results (%) o the node being . m away rom Microwave Oven . Detailedclassication results (%) o classications per channel. For a better evaluation, the measured channel utilization cu or the classications are alsogiven


1 2 cu

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: Uncontrolled environment IEEE . experiments summarized by channels. Classication results (%) o classications perchannel or low, real-world IEEE . traffic (mainly overlapping channels are bold). Te given resultpresents the mean o three nodesand the standard deviation between nodes in parentheses.


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perormed in a live environment, there is no ground truthdata. Tereore, only the results or the WLAN class canbe evaluated, since the WLAN was, as in common practice,permanently announced. Te Wireless Keyboard was justused during a time span in the evening. Te WLANclassi-cation worked reliably with .%, .%, .%,and .% correct classications on channel to .

InFigure (a), the channel utilization is shown, which iscommonly used to categorize channels (e.g., in []). When

Figures (a) and(b) are compared, it can be seen thatthe presented classication algorithm delivers much moreinormation than the simple channel utilization. Due to thebeacon detection, a WLAN is detected as a possible sourceo intererence, although it might be idle at the moment andthe IEEE . channel is not used. A simple threshold othe channel utilization cannot detect IEEE . or most othe time and, thereore, channels , , , and would beconsidered as good choices. In the late evening rom :


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: Uncontrolled environment microwave oven summarized by channel. Classication results (%) o classications per channel . maway rom Microwave Oven in an uncontrolled residential environment. Te given resultpresents the mean o three nodes and the standarddeviation between nodes is in parentheses. For a better evaluation, the measured channel utilizationor the classications are also given.


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(a) Channel utilization (%) over time

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(b) Classication results over time

F : Results o a -hour long-term evaluation o the classication algorithm in a real-world environment (trace o a single node).

to :, the channels are under heavy intererence, becausethe WLAN was used by multiple clients. In this case, anearlier detection and avoidance o the IEEE . channelswould prevent intererence, which would lead to a channelchange. Tus, especially the detection o IEEE . is useulor a long-term channel planning. Since the algorithm alsomeasures the channel utilization internally, the resulting classcanbe urtherjudged by the actual medium use. Tis example

shows the potential o the presented algorithm or real-worldWSN deployments.

6. Results and Discussion

In this work, an algorithm is introduced to classiy onesecondor, in most cases, a shorter trace o CCA samples into one osix classes, namely, idle channel (CLEAR), Bluetooth single-slot packets (BT), Bluetooth multislot packets (BT), IEEE.-based WLANs (WLAN), microwave ovens (MWO),or an unknown source o intererence (UNKNOWN). I theclassication is interrupted by receiving an IEEE ..packet, the classication o the source o intererence is not

nalized and theINTERNALclass is returned. Furthermore,the algorithm classes and the algorithm implementation aredescribed and, nally, the algorithm was tested in multiplescenarios. In the ollowing, the test results are discussed andcompared to the state-o-the-art.

.. Classication Results. Te extensive testing o the algo-rithm conducted in the previous section allows the ollowing

conclusion o the classication perormance: Te WLANclassication worked well or MHz wide channels. Tephenomena that adjacent channels were ofen interered butmisclassied can, as already mentioned, be explained withthe different modulations and the close distance. Due tothe different modulations, the data traffic might still affectan IEEE .. channel, on which the beacon rames arereceived below the CCA limit. Nevertheless, the experimentsalso showed that the data traffic in the WLAN has little to noeffect on the classication rate.

Te Bluetooth classication here represented by twoclassesBT and BT works satisactorily. On the used Laptop,some channels were avoided, which decreased the overall


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classication rate. However, i a channel is not used by Blue-tooth, it cannot be classied as such; thus, the sometimes lowclassication rate is a pessimistic measure. Also, Bluetoothintereres only very little on a single IEEE .. channeland thereore there is little to measure.

Te MWO class delivered only moderate classication

results, especially in the uncontrolled environment. Sincemicrowave ovens have no standards nor specications or theemission o radiation as communication technologies have,this problem is not ully solvable, although in countries witha different electrical system providing a different requency,or example, North America, the algorithm has to be slightlyadapted.

o give an overall classication rate or a comparisonto methods suggested in literature is difficult, since multi-ple actors inuence the classication rate, including tra-c/modulation o intererer, spectral overlap, distance, andCCA threshold. However, the reported rates and the testsetups are shortly reviewed in the ollowing to provide arough possibility o comparison.

Zhou et al. [] evaluate their AP beacon detectionwith our different APs and traffic generated by D-IG.Additionally, they check their approach or cross-sensitivitywith IEEE .. traffic. Tey report a detection rate o %;the requency offset is not mentioned, but the runtime o thealgorithm is given. I only the two IEEE .. channelsnext to the center requency o the used IEEE . AP areused, the algorithm presented here has a higher detection ratein the controlled environment and a comparable rate in theuncontrolled environment.

Chowdhury and Akyildiz [] evaluate their approachwith simulations anddo not state a classication rate orIEEE. or microwave ovens. Similarly no statement is made byBloessl et al. [] and Nicolas and Marot [].

Ansari et al. [] state a % detection rate o IEEE .,but they only detect a single class in a near-ideal environmentwithout any cross-sensitivity or control group.

Te publications o Hermans et al. [], Renselt et al.[], and Hermans et al. [] developing SoNIC are the mostcomparable to the algorithm presented here and since thelatter publication is the most recent and best evaluated one,the authors will reer to it. Hermans et al. [] claim todetect the predominant source o intererence in an officeenvironment with %. However, conusion matrices givenin their work show that especially the IEEE . detectionis relatively low with .%. Due to unclear requency offsets

and different devices used, the rates cannot be directlycompared to the work presented here. As already mentionedinSection , the algorithm presented here is, to the best othe authors knowledge, the only one distinguishing betweensingle-slot (BT) and multislot (BT) Bluetooth packets. Teauthors believe that the Bluetooth packet length has effectson the pattern o the corrupted bits. Further, it is not only the

varying airtime o Bluetooth, but also the modulation changewithin Bluetooth packets o higher data rate [].

Additionally, the detection o bonded channels used byIEEE .n has not been discussed

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