Fine grained spectrum adaptation in wifi networks
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Fine-grained Spectrum Adaptation in WiFi Networks. Sangki Yun , Daehyeok Kim and Lili Qiu University of Texas at Austin. ACM MOBICOM 2013, Miami, USA. Current trend in WiFi. Wireless applications increasing throughput demand Channel width is increasing

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Fine-grained Spectrum Adaptation in WiFi Networks

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Fine grained spectrum adaptation in wifi networks

Fine-grained Spectrum Adaptation in WiFi Networks

Sangki Yun, Daehyeok Kim and Lili Qiu

University of Texas at Austin

ACM MOBICOM 2013, Miami, USA


Current trend in wifi

Current trend in WiFi

  • Wireless applications increasing throughput demand

  • Channel width is increasing

  • Benefit of wide channel: higher throughput

802.11a/b/g

20MHz

802.11n

40MHz

802.11ac

160MHz

Is wide channel always better?


Disadvantage of wideband channel

Disadvantage of wideband channel

  • High framing overhead

  • High energy consumption

  • Lower spectrum efficiency due to frequency diversity

channel access

channel access

SIFS

SIFS

preamble

preamble

data

wide channel

data

ACK

ACK

idle

period

idle

period

wide channel

transmission

transmission


Lessons

Lessons

  • Static spectrum access (wide or narrow spectrum exclusively) is insufficient

  • Need dynamic spectrum access to get the best of both worlds


Ideal case per frame adaptation

Ideal case: per-frame adaptation

  • Clients select channel based on their preference

  • AP needs per-frame spectrum adaptationto communicates with different clients

  • Preferred channel may change over time -> further increase the need for per frame adaptation

20MHz

5MHz

time

Spectrum efficiency

Energy efficiency

10MHz

20MHz


Challenges

Challenges

  • Enable per-frame spectrum adaptation

  • Sender and receiver agree on the spectrum

  • Dynamically allocate spectrum efficiently


Related work

Related work

  • Dynamic spectrum access (WiMAX, LTE, FICA)

    • Requires tight synchronization among clients

    • Significant signaling overhead

  • Spectrum adaptation (SampleWidth, FLUID)

    • Focus on spectrum allocation and ignore spectrum agreement

    • Slow to adjust the channel width

  • WiFi-NC

    • Channel width is fixed to 5MHz

    • Requires longer CP to reduce guard bandwidth

  • IEEE 802.11ac

    • RTS/CTS for dynamic bandwidth management

    • Not fine grained (minimum channel width 20MHz)


Fsa fine grained spectrum adaptation

FSA: Fine-grained spectrum adaptation

  • Per-frame spectrum access

    • Change spectrum per-frame

    • Communicate with multiple nodes on different subbands using one radio

  • In-band spectrum detection using existing preamble

  • Efficient spectrum allocation


Transmitter design

Transmitter design

Interpolation &

remove images

Center frequencyshifting

Reduces

bandwidth

20MHz bandwidth

OFDM signal

LPF

CF shift

PHY encoder

upsampler

RF

. . .

. . .

. . .

mixer

LPF

CF shift

PHY encoder

upsampler


Generating narrowband signals

Generating narrowband signals

  • Convert 5 or 10MHz signal based on 20MHz signal through upsampling and low pass filtering

LPF

upsampling

frequency

frequency

20MHz

20MHz

frequency

20MHz

Narrowband signal

20MHz signal

Upsampling generates images outside tx band


Sending signals together

Sending signals together

  • Center frequency shifting is performed and the signals in different spectrum are added

20Hz

20Hz

Center frequency shifting

adding another narrowband signal

Shifted signal

Narrowband signal

20Hz

RF

20Hz

Deliver to RF

Mixed signal


Receiver design

Receiver design

down-sampler

PHY

decoder

CF shift

LPF

Spectrum detector

RF

. . .

. . .

. . .

down-sampler

PHY

decoder

CF shift

LPF


Receiver design1

Receiver design

down-sampler

PHY

decoder

CF shift

LPF

Spectrum detector

RF

. . .

. . .

. . .

down-sampler

PHY

decoder

CF shift

LPF

Spectrum detector is key component


Spectrum detector

Spectrum detector

  • Goal: Receiver identifies the spectrum used by the transmitter

  • Possible solutions

    • Use control channel or frame

      • Too much overhead

      • Target for attack

      • Control channel may not be always available  further increase overhead

    • Design special preamble [Eugene,12]

      • Deployment issue


Spectrum detection using stf

Spectrum detection using STF

  • It is ideal to detect spectrum using existing 802.11 frame detection preamble (STF)

  • One solution: Spectral and Temporal analysis of the detection preamble (STD)

    • Power spectral density to detect the total spectrum width

    • Temporal analysis to identify exact spectrum allocation

    • Costly and inaccurate especially in noisy channel

  • Our approach

    • Exploit special characteristics of STF for spectrum detection


Characteristic of 802 11 stf

Characteristic of 802.11 STF

  • Time domain: 10 repetitions of 16 signals

  • Frequency domain: 12 spikes out of 64 subcarriers with 4 subcarrier intervals

t1

t2

t3

t4

t5

t6

t7

t8

t9

t10

We exploit the subcarrier interval for the spectrum detection!


Spectrum detector design cont

Spectrum detector design (Cont.)

  • Depending on the transmitter spectrum width, the received STF has various subcarrier intervals

20MHz

Subcarrier interval: 4

10MHz

Subcarrier interval: 2

5MHz

Subcarrier interval: 1


Spectrum detection using stf1

Spectrum detection using STF

  • 20MHz transmitter to 20MHz receiver

20MHz

20MHz receiver

20MHz transmitter

STF in the frequency domain at the 20MHz receiver


Spectrum detection using stf2

Spectrum detection using STF

  • 10MHz transmitter to 20MHz receiver

20MHz

20MHz receiver

10MHz transmitter

Two subcarriers of 10MHz transmitter is merged into one subcarrier of 20MHz receiver

STF in the frequency domain at the 20MHz receiver


Spectrum detection using stf3

Spectrum detection using STF

  • 5MHz transmitter to 20MHz receiver

20MHz

20MHz receiver

5MHz transmitter

STF in the frequency domain at the 20MHz receiver


Spectrum detection using stf4

Spectrum detection using STF

  • The subcarrier interval difference let us easily identify the spectrum

20MHz

20MHz receiver

20MHz transmitter

20MHz

20MHz receiver

STF in the frequency domain at the 20MHz receiver


Spectrum detector design cont1

Spectrum detector design (Cont.)

10MHz

Transform spectrum detection into pattern matching.

5MHz

10MHz

10MHz

10MHz

5MHz

5MHz


Spectrum detector design

Spectrum detector design

Cross-correlationcheck

Maximum likelihood

pattern matching

  • Optimal Euclidean distance based spectrum detection

  • Binary detection

RF-frontend

802.11 preamble detection

FFT-64

spectrum detection

Received signal sampled in 20MHz rate

Magnitude of64 subcarriers

.


Spectrum allocation

Spectrum Allocation

Controller

buffer

AP

AP

AP

client

client

client

client


Spectrum allocation cont

Spectrum Allocation (Cont.)

  • Input

    • Destinations of buffered frames

    • CSI between APs and clients

    • Conflict graph

  • Goal: Minimize finish time

    • Avoid interference

    • Harness frequency diversity

  • Knobs

    • Spectrum

    • Schedule

    • AP used for transmission


Spectrum allocation cont1

Spectrum allocation (Cont.)

  • Break a frame into mini-frames

  • Break the entire spectrum into mini-channels

  • Greedily assign a mini-frame to a mini-channel that minimizes the overall finish time while avoiding interference

  • Find a swapping with an assigned mini-frame that leads to the largest improvement, go to step 3


Evaluation methodology

Evaluation methodology

  • Implemented testbed in Sora

    • 2.4GHz

    • 20MHz maximum bandwidth

  • Evaluates detection accuracy and latency, spectrum allocation performance in testbed

  • Trace based simulation for spectrum allocation in large-scale network


Spectrum detection accuracy

Spectrum detection accuracy


Spectrum detection delay

Spectrum detection delay

Median detection delay 4.2 us < detection delay budget


Throughput evaluation no interference

Throughput evaluation – no interference

FSA improves throughput by exploiting frequency diversity


Throughput evaluation interference

Throughput evaluation – interference

With narrowband interference, the gain grows larger


Summary

Summary

  • FSA – a step towards enabling dynamic spectrum access

    • Flexible baseband design

    • Fast and accurate channel detection method

    • Spectrum adaptation


Fine grained spectrum adaptation in wifi networks

Q & A

Thank you!


Comparison with wifi nc

Comparison with WiFi-NC

Simulation in fading channel width RMS of delay spread = 100 ns

WiFi NC incurs lower SNR due to sharp filtering


Discussion

Discussion

  • Detection accuracy

  • Antenna gain control

  • Bi-directional traffic


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