providing unlimited wireless capacity bob brodersen berkeley wireless research center adaptrum, inc...
TRANSCRIPT
Providing Unlimited Wireless Capacity
Bob Brodersen
Berkeley Wireless Research CenterAdaptrum, Inc and SiBEAM, Inc.
Univ. of California, Berkeley
More Capacity – Do we really need it ?? Major bandwidth driver is moving from voice to
video and data – a 1000-10,000 fold requirement increase
User base is moving to be a significant fraction of the 6 Billion world population
Devices (without an attached human) will communicate wirelessly » Source to HD display with uncompressed video => 4
Gbit/sec» A home will have a 1000 radios
This is not going to be addressed by improving any radio system we have now
Looks like we need it ….
Claim: There are technological solutions to providing this capacity which is based on abandoning the property rights model of “owning” frequency spectrum
Assertions: » The concept of fixed frequency spectrum allocation has
become fundamentally flawed» We need to exploit wireless communication strategies
that exploit the time, space and frequency degrees of freedom
» Exploiting these new approaches could allow essentially “unlimited capacity”
Why has Frequency Allocation become a Flawed Concept?
The applications are continually changing and allocation doesn’t mean use
Frequency is only one of the 3 degrees of freedom to use to avoid interference - time and space are actually more effective
UWB, 60 GHz and Cognitive radios individually exploit the 3 DOF
Frequency » Separate users by using different frequency bands
– traditional method using analog filtering» Exploit wide bandwidths and DSP» Exploit higher frequencies
– present CMOS technology allows use up to 100GHz Space and Angle
» Reduce transmit power – decreases radius of omni-directional cells
» Exploit the angular nature of the spatial channel– Multiple antennas
Time» Impulse filtering» Sense interference and avoid
UWB, 60 GHz and Cognitive radios individually exploit the 3 DOF
Frequency » Separate users by using different frequency bands
– traditional method using analog filtering» Exploit wide bandwidths and DSP (UWB) » Exploit higher frequencies
– present CMOS technology allows use up to 100GHz (60 GHz) Space and Angle
» Reduce transmit power – decreases radius of omni-directional cells (UWB)
» Exploit the angular nature of the spatial channel– Multiple antennas (60 GHz)
Time» Impulse filtering (UWB)» Sense interference and avoid (Cognitive Radio)
Talk Organization
A discussion of the emerging techniques that are exploiting the three degrees of freedom in new ways» UWB» Cognitive Radios» 60 GHz
How these can be combined to achieve “unlimited capacity”
Lets start with UWB…
Breakthrough! For the first time the regulators allowed sharing of the frequency spectrum» Underlay – Allow sharing of the spectrum if the
interference is negligible » Ultrawide bandwidths were allowed
Fundamental choices remain on how to best to use the wide bandwidth» Stay with conventional frequency domain
thinking» Or exploit the time degree of freedom
UWB Frequency and Time domain strategies
Time Frequency
FrequencyTime
TimeUWB Impulse
FrequencyTime
FrequencyUWB OFDM(multiple sine waves)
Traditional user(narrowband)
Noise
Pow
erP
ower
Pow
er
Time domain filters (block the impulse in time) can be easily made adaptive (unlike frequency domain)
Time domain interference
Interference in frequency domain
UWB is allowed in over 11 GHz of spectrum
0 20 40
UWBUWB
UWB
60 80 100 GHz
Comm Vehicular
Limited power allows a high level of spatial reuse Chip sets are available for both OFDM and
Impulse approaches But ….. If this is such a good idea why
has it not been commercially successful
What happened …
Two competing approaches were attempted which resulted in a standards battle which was waged without good technical input
The (comfortable) frequency domain approach (OFDM) had too high a complexity and too low a performance
The time domain (impulse) approach is too different and needs much more R&D in theory and implementation
Cognitive Radios
Basic idea » Exploit the time degree of freedom by sensing if
a signal is present » Then take steps to assure there isn’t
interference This is quite restricted, others use a more
expanded definition
A Cognitive Radio using Time and Frequency
Sense the spectral environment over a wide bandwidth Transmit in “White Space” Detect if primary user appears Move to new white space Adapt bandwidth and power levels to meet QOS requirements
Pow
er
Frequency
PU1
PU2
PU3
PU4
Cognitive Radio system level view
Network coordination
Medium Access
Sensing Signal Processing
Sensing radio
Resource Allocation
Wideband signaling
Wideband radio
Physical Layer
NetworkLink Layers
Spectrum sensing is the key enabling functionality and
must be very sensitive to limit unwanted interference
Sensing Weak Signals
A new radio functionality – requires new algorithms and understanding
A/D N pt. FFT
x(t)Averageover T
Energydetect
Threshold
High SNR Low SNR
Spectrum density
Energy Detector
A/D N pt. FFTCorrelate
X(f+a)X*(f-a)Averageover T
x(t)Featuredetect
Spectral correlation
Cyclostationary Feature Detector
Sensing Performance (Danijela Cabric)
Incoherent sensing time goes as 1/(SNR2)
Coherent sensing time goes as 1/SNR
Log
Tim
e
(Cyclostationary)
Incoherent processing
Coherent sensing
Cyclostationary
Coherent sensing - ATSC signal
Correlation of fixed header is used by Adaptrum in FCC trials being held now – highest performing results
Adaptrum TV-band CR prototype
CR Transceiver
CR Baseband/MAC FPGA (Altera)
Bowtie wideband UHF antenna
ATSC sensitivity measurement result
-122 -121.5 -121 -120.5 -120 -119.5 -119 -118.5 -118 -117.50
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Input Signal Power (dBm/6 MHz)
Pro
babi
lity
of S
ucce
ssfu
l Det
ectio
n
Channel 21 (515 MHz)
Channel 59 (743 MHz)
Planned Bay Area Cognitive Radio - 400 MHz experimental testbed
Using the Space Degree of Freedom to improve sensing
Spatially separated sensing radios can make independent measurements
Single radio sensitivity can be improved by the use of multiple antennas using beamforming
Spatially separated sensing radios
Expected result for independent measurements:
Primary System
Tx
Rx
Decoding SNR
Exploit spatial diversity in Sensing SNRs
Pd, network=1-(1-Pd, radio)N
Experimental SetupLocation (11,9)
Location (16,3)
Central combining and processing
Fiber provides 1/3 mile separation between radios and platform
controlledPHY and MAC
integration
Sensing radio
Sensing radio
Sensing PHY/MAC processors
Network Spectrum Sensing Results
Prob. of false alarm
Prob
. of d
etec
tion
1 radio
5 radios
If spacing >> λ/2 a few cooperative radios give big improvements
Danijela Cabric, Mubaraq Mishra and Anant Sahai
Dynamic range problem in wideband sensing P
SD
Freq.
A/DLNA AGC
Fixed LOBand of interest
Wideband sensing is required to quickly sense the open bands» Small signals need to be sensed in the presence of strong
interference and then processed digitally» Places difficult requirements on RF front end and A/D
Multi-antenna spatial processing provides two solutions
Multi-antenna spatial processing to improve sensing
Primary user f1 Phased antenna array
Improvements with N antennas » allow suppression of up to N-1 large
signals» provide up to an N times increase in
sensitivity We’ll find more uses for these arrays
Primary user f2
Time DomainWideband Signal
Interference Estimation
A/DDigital
Processing
Attenuate Strong Interferenceand Reduce DR to ADC
+-
RX
One possible implementation
Time Domain Interference Cancellationto address the dynamic range problem (Jing Yang)
Adaptive Filter
+-
r
ADC
DAC
AGC( )I S N
ADCAGCProgrammable Analog Delay LineProgrammable Analog Delay Line
ADC
Cancellation ADCN Bits
ADC
Residue ADCM Bits
DAC
Yields N+M equivalent bits of dynamic range
Simulated interference attenuation
Attenuate the strong interference and reduce the dynamic range to the Residue Attenuate the strong interference and reduce the dynamic range to the Residue ADC by 35dBADC by 35dB
Extending the effective number of bits for this system by nearly 6 bitsExtending the effective number of bits for this system by nearly 6 bits
10
0
-10
-20
-30
-40
-50
-60
Mag
nit
ud
e (d
B)
190 192 194 196 198 200 202 204 206 208 210
Frequency (MHz)
20
10
0
-10
-20
-30
-40
Mag
nit
ud
e (d
B)
190 192 194 196 198 200 202 204 206 208 210
Frequency (MHz)
Strong FSK modulated interfering signal
Moderate sinusoidal interfering signal
Before After
Attenuated strong interfering signal
CR signal
The opportunity of higher frequencies
0 20 40 60 80 100 GHz
Effectively no use above 5 GHz Antenna arrays require only a small area Absolutely necessary to get to gigabit/sec rates
0-3 GHz >> 99% of all wireless transmission
7 GHz of unused and unlicensed spectra
Use of Higher Frequencies (e.g. 60 GHz)
Conventional wisdom is that lower frequencies are better » Only line of sight operation is possible and can’t
penetrate materials» The technology to process signals is expensive» As you go up in frequency there is an inherent
“path loss” that reduces range
Not True!!!
Material Penetration – actually not so bad
60 GHz 2.5 GHz
Pine board – ¾ ” 8 db 1.5dB
Clay Brick 9 dB 2 dB
Glass with wire mesh 10.2 dB 7.7 dB
Asphalt Shingle 1.7 dB 1.5 dB
Plywood – ¾ ” 7 dB 1.5 dB
Clear Glass 6.4 dB 3.6 dB
Atmosphere per 100m
1.5 dB 0 dB
What about Oxygen absorption?
Millimeter wave radios
Misconception: Implementing millimeter wave radios requires exotic materials» Conventional state-of-the-art digital CMOS can
be used to implement integrated radios up to 100 GHz
» Future technology scaling will allow even higher frequency operation (research is beginning into Terahertz operation)
60-GHz CMOS operation (130 nm)
1 mm
1.3 mm
Use of transmission line interconnect allows control of electrical and magnetic fields
Better control than at lower frequencies!
11-dB Gain@ 60 GHz
60-GHz CMOS Receiver front-end
CMOS integration means even a 60 GHz receiver will eventually cost about the same as a WiFi
Millimeter wave radios
Misconception: As you go up in frequency there is an inherent “path loss” that reduces range » This comes from only considering omnidirectional
antennas which have a size that is inverse with carrier frequency
» Solution is to keep area constant using directional antennas - then the received signal increases with frequency
Tx
Rx
Low Gain Tx Antenna
Area of sphere = 4r2
Captured energy
Antenna fundamentals: Receive Antenna Energy
2r4
rA
spherea of Area
antennareceive ofArea
Ar = Area of receiveantenna
Fraction of power received from an omnidirectional transmission
=
Effective transmit antenna power
Maximum increase in power in direction of beam
= (wavelength of carrier)
Effective maximum power as if it came from an omnidirectinal antenna = Pt Gt
Rx
Pt Gt
Tx
2
tt
A4G
At = Area of transmitter
The link budget with directional antennas
2t
t
A4G
2tr
2t2r
ttr r
AA1P
r4
AGPP
Receive power improveswith frequency!!
Rx
Captured energyIn Area Ar
Wasted energyTx
22 dB more gain at 60 GHz over 5 GHz if antenna size is kept constant
(Compare to Friis “path loss” formula ) 2tr2
trr4
GGPP
Millimeter wave radios
Misconception: Only line of sight transmission is possible» millimeter waves reflect like lower frequency
waves, so adaptive directional antenna arrays can choose strongest signal
» millimeter waves have higher material penetration loss, but this can be compensated for with the higher power and antenna gain
Non line of sight transmission
Transmitter in Source
Phased Array Antennas» Power used more efficiently for better reception, longer distance,
higher bandwidth» Dynamically steers beam to specific receiving station
SiBEAM Module
Phased array circuitry
N antennas allow N power amps to transmit in parallel Phase accuracy requirement is very low as the number
of antennas go up (2 bits for 16 antennas)
1 2 3 4 5
x 104
0
2
4
6
8
10
12
Number of Symbols
Eig
en
valu
es
Algorithms for adaptive beamforming
1
2
3
4
0 0 0
0 0 0' '
0 0 0
0 0 0
y x
Separate the multipath into separate channels through an SVD
Choose the strongest one and put all the energy into it
σ1
σ2
σ3
σ4
Blind tracking
)(ty
ArrayProcessing
)(tx
ArrayProcessing
1st path, σ1=10
2nd path, σ2=6
As beams get narrow the capacity increases (Ada Poon)
Capacity 2 A -2W T log SNR
Carrier frequency
Cumulative scattering solid angle
Transmit Array area
Polarization
The old (Shannon) Formula:
Capacity W T log SNR
With spatial processing:
Transmission interval
Bandwidth
New “spatial” degreesof freedom provide multiplicative increases
The time frequency degrees of freedom
How do we get to “unlimited capacity”?
Two ways – probably more» Angular isolation of beamformed signals
requires not only co-location but the same angle
– This essentially eliminates interference – Add in “UWB-like” spectrum sharing and cognitive
techniques to achieve essentially “unlimited”
» Increasing the number of users with multiple antennas provides an unlimited increase if frequency or antenna area is increased
Angular isolation
A transmits towards B with phased array B only receives in direction of A Transmitter C doesn’t interfere with B
C
A B
Angular isolation
Interference between beamformed signals has to not only be in the same space, but also have the same angle
C
A B
Another solution to aligned receivers
Start with link AB Add aligned link CD What do we do now….
DC A B
Use a reflection
Usually at least 2-3 reflections This is requiring more resolution in the
phase shifters to control sidelobes
Capacity increases with number of RX&TX=N
Scheme No.ofAntennas
CapacityIncrease
Frequency/Time Subdivision N 1
Packet Multihop N N1/2
Cooperative Diversity (Tse) N N
MIMO at each user (Chung) N2 N2
MIMO with reflections N A/2 (N A/2)2
Back to our Frequency Allocation Chart
If we use all 3 degrees of freedom then a chart like this really is meaningless
A future allocation chart…
Now how do we get to this!!
Shared Spectrum
Shared Spectrum
Shared Spectrum
Shared Spectrum
Shared Spectrum
Shared Spectrum
Shared Spectrum