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Cellular Backhauling Optimization
Yaakov (J) SteinChief Scientist
RAD Data Communications, Ltd.
Cellular communications
To most people cellular communications means only the air interface
This is the Radio Frequency link between MS and BTS
Mobile StationBase Transmitter Station
air interface
cell site
Cellular networks
But there is a lot more to the cellular network than that !
Using GSM (2G) terminology :All the Base Transmitter Stations are to Base Station ControllersThe BSCs are connected to Mobile Switching CentersMSCs are interconnected,
and also connected to the Public Switched Telephony Network
PSTN
MSC
BTS
BTS
BTS
BTS
BTS
BTS
BTSBTS
BTS
BSC
BSC
BSC
MSC
HLR VLR
Cellular backhauling
We (informally) call all of the network except the air interfacethe cellular backhaul network
Backhauling of 2G cellular traffic uses TDM (E1/T1) links over :• Copper• Fiber• Microwave
Due to rapid worldwide increase in cellular penetrationbackhauling is one of the hottest topics in the telecommunications industry
To reduce operational expenses, cellular operators want to :• reduce bandwidth consumption• migrate to (less expensive) Packet Switched Networks (IP/MPLS/Ethernet)• employ less expensive transport types, for example
– Metro Ethernet Networks – DSL links
Reduction of bandwidth (optimization) for 2G GSM is the main topic of this talk
Cellular backhaul optimization
Voice traffic is already compressed by the mobile stationSo why can cellular traffic be optimized at all ?
• TDM transport mechanisms can not reduce bandwidth• standard user traffic (TRAU) formats are extremely inefficient• nonactive user channels are sent• silence/idle frames in active channels are sent• signaling channels (HDLC-based) are inefficient• data can be compressed by lossless data compression• additional mechanisms (e.g. stronger compression) may sometimes be used
ACE-3xxx
Cellular backhaul transport
When TDM transport (e.g. E1 links) is used– optimization enables use of fewer E1s to carry the same amount of user traffic– reduced operational expense at dense portions of network– however, compressed traffic formats are not standardized
When TDM transport is replaced with Packet Switched Networks– service less expensive to begin with– service often charged by bandwidth used– optimization enables using only the minimum BW needed– operational expense reduced
GSM 2G architecture
GSM formally separates the Public Land Mobile Network into subsystemsand defines the interfaces / protocols between each two pieces of equipment
A-type interfaces carry the voice traffic in the backhaul portion of the network• A interface is a standard TDM link divided into 64 kbps timeslots• Abis interface connects the BTS to the BSC and carries FR or HR channels• Ater interface connects the BSC to the MSC and carries FR or HR channels
A-type interfaces also carry control information
BTS BSC MSCBase StationSubsystem
Network and Switching Subsystem
Um interface
Abisinterface
A / Aterinterface
B … Finterfaces
RF TDM TDM
serversand
other networks
Carrying A-type interfaces over PSN
Cellular operators can transport Abis/Ater over PSNs instead of TDM
To do this without forklift upgrade of their equipment to 3Gthey can use pseudowire (PW) technology
A PW emulates a native service by building a tunnel through the PSN
Bandwidth reduced as compared to TDM
with optimization, bandwidth can be further reduced
BTS BSC
AbisinterfaceTDM
AbisinterfaceTDM
PSN
pseudowire (PW)
cellopt GW cellopt GW
Voice channelsAlthough over time new services were added• Fax• Short Message Service• Multimedia Message Service• Wireless Application Protocol• Internet and WWW access• Video streamingthe cellular network was originally designed for voice trafficA GSM transmitter segments voice into 20 millisecond framesAnd applies compression to place voice traffic into one of two channel types• Full Rate channel - 16 kbps = 2 bits every 1/8000 sec. = 320 bits per 20 ms.• Half Rate channel - 8 kbps = 1 bit every 1/8000 sec. = 160 bits per 20 ms.There are various compression algorithms• Full Rate codec - 13 kbps (FR channel)• Enhanced Full Rate codec - 12.2 kbps (FR channel)• Half Rate codec - 5.6 kbps (HR channel)• Adaptive MultiRate - 4.75, 5.15, 5.9, 6.7, 7.4, 7.95 (HR or FR channels) - 10.2, 12.2 kbps (FR channel)
TRAU framesThe compressions and format conversions in the network are performed by the
Transcoder and Rate Adaptation Unit
Information on the A bis and A ter interfaces is encoded in TRAU frames
TRAU voice frames represent 20 ms. of audio • FR channels - TRAU frames are 320 bits = 40 bytes• HR channels - TRAU frames are 160 bits = 20 bytes
The TRAU frames are transported over FR and HR channels
……
…
...
TDM (E1) frame (256 bits)
t8 bit TDM timeslots1 bit HR timeslots2 bit FR timeslots
…
Note that a full E1 (2 Mbps) must be used even when thereare very few channels
idle = 01
alarm = 00
TRAU framingThe TRAU frames have a specific frame structure that must be detected
For example, this is the framing of the generic FR (40 byte) TRAU frame :
And this is the generic HR (20 byte) TRAU frame :
Note: there are other frame formats as well
00000000 00000000 1xxxxxxx xxxxxxxx 1xxxxxxx xxxxxxxx 1xxxxxxx xxxxxxxx
1xxxxxxx xxxxxxxx 1xxxxxxx xxxxxxxx 1xxxxxxx xxxxxxxx 1xxxxxxx xxxxxxxx
1xxxxxxx xxxxxxxx 1xxxxxxx xxxxxxxx 1xxxxxxx xxxxxxxx 1xxxxxxx xxxxxxxx
1xxxxxxx xxxxxxxx 1xxxxxxx xxxxxxxx 1xxxxxxx xxxxxxxx 1xxxxxxx xxxxxxxx
1xxxxxxx xxxxxxxx 1xxxxxxx xxxxxxxx 1xxxxxxx xxxxxxxx 1xxxxxxx xxxxTTTT
00000000 1xxxxxxx 01xxxxxx 1xxxxxxx
1xxxxxxx 1xxxxxxx 1xxxxxxx 1xxxxxxx
1xxxxxxx 1xxxxxxx 1xxxxxxx 1xxxxxxx
1xxxxxxx 1xxxxxxx 1xxxxxxx 1xxxxxxx
1xxxxxxx 1xxxxxxx 1xxxxxxx 1xxxxxTT
x bits are data / control and are not part of the framing
T bits are for time alignment (justification)
Abis signaling channels
It is very important not to delay or corrupt special signaling channelsAter signaling channels are based on SS7Abis signaling channels are not completely standardized
each equipment vendor has its own signaling formatAbis Signaling channels can be• 16 kbps (2 bits per TDM frame)• 32 kbps (4 bits per TDM frame)• 64 kbps (a full 8 bit TDM timeslot)
Signaling is usually HDLC based, with a frame format :
The frame between flags (7E hex) is bit-stuffedBetween frames there may be flags or other filling
flag address ctrl DATA CRC flag
Backhauling dataUser data can be transported over the Abis interface in various ways
Low rate data (up to 9.6 or 14.4 kbps) is transported in TRAU frames
Intermediate rates (up to 114 kbps) are available via GPRS (2.5G)
Higher rates (theoretically up to 384 kbps) via EDGE (2.75G)GPRS / EDGE are carried over G-type interfaces
which may share the same TDM link as A-type interfaces
GPRS/EDGE bandwidth allocation may be dynamic it takes over bits not used by the A-type interfaces
In 3G networks data can be much higher rate (over 2 Mbps, e.g. 10 Mbps)
carried over I-type interfacesthat use separate transport media
GSM 2.5G architecture (GPRS/EDGE)
The first high-speed GSM data (WAP, PTT, MMS, WWW) service was the Generalized Packet Radio Service
It provides 56 kbps - 114 kbps packet data for IP communicationsThe air interface is enhanced, but won't be discussed hereTo the GSM backhaul architecture is adds• Serving GPRS Support Node• Gateway GPRS Support Node• G interfacesThe next stage is Enhanced Data for Global Evolution (AKA Enhanced GPRS)
BTS
MSCUm
A bis A / A ter
BSC
Gb
BSS
SGSN
Gn
NSS-CS
GGSNNSS-PS
3+G architectures
In initial 3G releases Iu interfaces are based on ATM (Iu-CS:AAL2, Iu-PS:AAL5)
In the final phases, the network becomes IPand the protocols become VoIP
At that point the window of opportunity for optimization closes
Node B RNC
Uu Iub
Iu - CS
RF
User Equipment
3G-MSC
3G-SGSN
Iu - PS PDN
PSTN
UTRAN Core
1st challenge - channel detectionVoice/data/signaling information appears at various places in the frame
Were we to understand the proprietary signaling – we would know where to look for the various channels– but this signaling is vendor-dependent– and the formats are not always known
So we need to employ an intelligent detector/classifier/deframer– detect channel framing and return field positions– classify channel as voice/data/signaling/idle/unknown– maintain relative synchronization
Matching framer at egress needs to recreate the original frames
signalingHR voiceFR voice64K dataTDM sync FR voice 32K data
…
Channel detector/classifierThis detector/classifier needs to continually scan all• 1-bit positions for HR TRAU frames• even aligned 2-bit fields for FR TRAU frames• even aligned 2-bit fields for HDLC• nibble-aligned nibbles for HDLC• byte-aligned octets for HDLC• fields of idle bits• anything elseand then return the identifications and positions found
Unidentified non-idle information must be reliably transported
The processing involves • searching for specific bit combinations• performing bit correlationsand is extremely computationally intensive
Can be performed by a DSP with good bit-oriented operations
2nd challenge - optimization
Once the various components have been found
the information needs to be reduced in size and reliably transported
• Idle fields need not be sent, often accounting for a large BW reduction• TRAU framing overhead may be removed• Voice frames marked as silent (DTX) may be suppressed• Voice Activity Detection may be employed to suppress silence• HDLC flags are removed and the contents destuffed• Data may be compressed
We will deal with each of these in turn
3rd challenge - data compression
Data is typically transported over cellular networks in uncompressed form
Lossless data compression algorithms, e.g. • Ziv-Lempel variants• Huffman codes / arithmetic codes• Shannon-Fano coding• Burrows-Wheeler Transform• Prediction by Partial Match
can be an effective optimization method when there is a significant amount of data traffic
Text data, such as HTML or WML, can be significantly compressed
Compressed video, binary files, encrypted data, etc. can not be compressed
Using data compressionMany algorithms perform well when there is a lot of data
The problem is that the impact of packet loss must be taken into account
If we compress each packet separately• there is not enough data for efficient compression
If we keep history from previous packets • we need to separate flows• we need to store state• loss of single compressed packet causes multiple packets to be discarded
DSPs can be exploited to handle data compressionmain limitation - large amount of memory needed
Need a DSP with efficient bit/byte-oriented operations
4th challenge - trans-rating
Audio / video streams are already compressed
Further compression may not be possible
However, sometimes there are hard bandwidth limits (caps)and we must be able to survive short bandwidth peaks
In certain instances trans-rating may be useful• at the expense of reduced perceived quality • especially when exceeding the cap is expected to be extremely rare
For example• change compression rate for AMR family on a frame-by-frame basis• transcode EFR codec down to a lower AMR rates and transcode back up at network egress
Smart trans-rating
The simplest (but most computationally intensive) way to trans-rate is to cascade a decoder and an encoder
For a particular pair of codecs there may be better ways, with• lower computational complexity• lower delay• less perceptual degradation
For AMR, there are commonalities that may be exploited
However, reserving DSP computational resources is usually not economically justifiable for a process that will only be used for short bandwidth peaks
Other mechanisms may be more affordable, such as smart frame drop
5th challenge - smart frame drop
Sometimes transport traffic bandwidth has a hard cap
If this cap is exceeded, voice frames will be discarded
The TRAU will employ Packet Loss Concealment techniques– that cover up much of the effect– generally there will still be noticeable impact on the user experience
A smarter technique is smart selective frame drop (extended VAD)
Smart frame drop
Instead of dropping randomly chosen voice frames …we can carefully select the frames to dropusing a criterion of least perceptual quality degradation
The selection can be based on voice parameters in the TRAU framewithout full decoding of the voice coding
The resulting DSP code• is codec-dependent• requires saving of state information per channel• but does not require large amounts of memory
The smart frame drop mechanismshould be tightly coupled controlled to the main control functionso that only the minimal percentage of frames are dropped
6th challenge - timing recovery
TDM's physical layer transfers accurate frequency (sync) informationGSM BTSs use the accurate frequency recovered from the TDM link to• generate accurate radio frequencies• generate symbol timing• send time offset information to mobile stations• ensure short handover when moving from cell to cellCDMA and 3G cellular systems also need accurate Time Of DayRequirements are stringent :• absolute frequency accuracy must be better than 50 ppb• jitter and wander need to conform to ITU TDM standards• 3G stations need time accuracy of better than 3 s • 3G TDD mode requires time accuracy of better than 1.25 s from UTC
When replacing TDM links with PWs over PSNs we lose timing information
Frequency measuresFrequency needs to be stable and accurate
and there may be both frequency jitter and wander
jitter is easy to filter out - the real problem is wander
f f
time
f
time
f
timetime
stablenot accurate
not stablenot accurate accurate
but not stable stable andaccurate
Jitter = short term timing variation (i.e. fast jumps - frequency > 10 Hz)
Wander = long term timing variation (i.e. slow moving - frequency < 10 Hz)
PSN - Delay and PDV
TDM frequency distribution is based on constant bit rate
Packets in PSNs may be sent at a constant rate
but PSNs introduce Packet Delay Variation
PDV makes frequency recovery difficult
PSN
but arrival times are not uniform
transmission times may be uniform
Jitter Buffer
Data from arriving packets are written into a jitter buffer
Once buffer is 1/2 filled, we read from buffer and output to Abis interface
Data is read from jitter buffer at a constant rate - so no jitter
But how do we know the correct rate ?
How do we guard against buffer overflow/underflow ?
We need a frequency recovery algorithm
Jitter Buffer
PSN
but arrival times are not uniform
transmission times may be uniform
Frequency recoveryPackets are injected into network ingress at times Tn
The source packet rate R is constant
Tn = n / R
The PSN delay Dn can be considered to be the sum oftypical delay d and random delay variation Vn
The packets are received at network egress at times tn
tn = Tn + Dn = Tn + d + Vn
By proper averaging/filtering tn = Tn + d = n / R + d
and the original packet rate R has been recovered
Unfortunately, simple averaging would be much too slow
By the time the accuracy would be sufficient, the rate would have wandered
In such cases control loops (PLL, FLL) are commonly usedbut the noise is much higher here than in usual cases where PLLs are usedand changing frequency to compensate for inaccuracy causes wander
Frequency recovery algorithms
Early solutions relied on :– linear regression– augmented PLLs – FLL - PLL hybrids
More sophisticated implementations exploit :– parameter estimation and tracking– oscillator modeling– network modeling– system separation
Although the algorithms may be complex– they run at a relatively low rate (tens of times per second)– and can thus be run on a DSP
SummaryCellular backhaul optimization enables
– more efficient use of overloaded transport infrastructures– lowering of OPEX
Cellular optimization is applicable to 2G and 2.5G networks
There are many challenges to building an operational system– channel detection, classification, and deframing– packet-loss-tolerant data compression– smart trans-rating– smart selective frame drop– timing recovery
DSPs provide a good platform for meeting these challenges
For more information, visit www.RAD.com