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Design Issues for Wireless Networks Across Diverse and Fragmented Spectrum

Design Issues for Wireless Networks Across Diverse and Fragmented Spectrum. Collaborators: Bell Labs India : Supratim Deb, Kanthi Nagaraj Bell Labs USA: Piyush Gupta. Mobile Data Explosion Will Result in Diverse & Fragmented Spectrum. Examples:

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Design Issues for Wireless Networks Across Diverse and Fragmented Spectrum

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  1. Design Issues for Wireless Networks Across Diverse and Fragmented Spectrum Collaborators: Bell Labs India: Supratim Deb, Kanthi Nagaraj Bell Labs USA: Piyush Gupta

  2. Mobile Data Explosion Will Result in Diverse & Fragmented Spectrum • Examples: • AT&T Spectrum in New York – 700MHz band, 800MHz, 1.7GHz and 2.1GHz • Unlicensed Spectrum in US – DTV Whitespaces (500-700MHz), 2.4GHz and 5.1GHz

  3. Research Goal Design a network stack that operates across 1) Fragmented and spatially varying spectrum with diverse propagation 2) Devices with different tunable center freq. and b/w range Routing + Flow Control New Design Perspective MAC + Spectrum Selection PHY + Sensing Lot of research

  4. Received Power at fixed distance, power (dB) slope = －20 log fc Designing MAC and above: Unique Challenges • Devices can tune frequency and bandwidth • Non-channelized system  complex MAC • No fixed interference graph • Frequency dependent propagation • Complicates spectrum allocation and MAC design • No fixed communication graph • Next-hop (hence, routing) depends on frequency • Leakage power at a distance depends on frequency • Adjacent channel interference (hence, guard band) varies with frequency • Cross layer optimization is highly complex Power Spectral Density  All traditional network stack design issues require a fresh look.

  5. Interference Management • Standard Approach: • Measurement based interference map • But, if the spectrum is diverse … • Two devices may interfere only in certain frequency bands Design Principle: • Generate different interference maps for different bands • Ideally a single/small number of control channels • Can use measurements over a single control channel • Pr(f1) － Pr(f2) ＝ 20 log(f2/f1) Interference maps in a higher freq. band can be deduced from interference map in a lower band (and knowledge of ambient interference)

  6. Agile and Efficient MAC forUnlicensed Accessin TV Whitespaces and ISM Bands

  7. Gist of FCC Mandate • Usable Free Spectrum: Unused TV channels between 500-698 MHz for unlicensed portable access • Varies from city to city • Limit Interference to DTV receiver: • Tx power: 16 dBm in adjacent band, 20 dBm elsewhere • Out of Band Emission: Has to fall by 55 dB in the adjacent 6 MHz band • Spectrum Mask

  8. Freq  Freq  DTV Channel DTV Channel DTV Channel DTV Channel 20 dBm 16 dBm Single Link Capacity With ACI Constraints • Fundamental Question: What’s the optimal transmit power anyway? • High power-> lower bandwidth • Guard band required to prevent interference to the TV channel • Low power -> reduced system capacity Observations: • Optimal capacity is independent on center frequency • For FCC’s spectrum mask, the power cap is not too sub-optimal Design Implications: • Choose fixed power (marginal loss in capacity) • Ensure a minimum bandwidth (leakage depends on PSD)

  9. MAC Design Considerations • Fragmented spectrum + limitations on maximum tunable bandwidth of a radio implies • Multi radio AP, single radio client (for cost considerations) • Need to account for frequency dependent propagation • Resilient to disruptions • E.g. wireless microphones • Evolution over WiFi • Easy adoption path, quick time to market, can interoperate with ISM bands • IEEE 802.11af standard already in progress

  10. (1,2,3,4,5,6,7) (1,2,3,4,5,6,7) (1,2,3,4,5,6,7) (1,2,3,4,5,6,7) Joint Spectrum Selection and Client Allocation 7 4 5 6 3 2 1 Joint Spectrum Selection and Client Assignment is a non-trivial problem

  11. Client-1 Client-2 Capturing the Utility of a Band Important Observation: • For most technologies, data rate/Hz depends on SNR as Data Rate / Hz = a × (SNR in dB) - b Design Implication: • Two step ASE generation: • Each AP generates ASE in control channel band. • Use frequency dependence and ambient interference measurements to compute ASE in all bands. ASE = Data rate averaged over all clients / Hz = a × (SNR averaged over all clients in dB) – b • SNR(f1) － SNR(f2) ＝ 20 log(f2/f1) • ASE in f1 can be generated for ASE in f2

  12. Proportional Fairness is Key for Whitespaces More likely that far away client will bring down performance of system Very simple design with minimal information overhead on top of 802.11 ensures proportional fairness 6Mbps 600MHz 6Mbps 2.4GHz

  13. Simulation Results • Comparison scheme • White space selection algorithm is optimal • Number of clients assigned per band is proportional to number of clients • 60-90% improvement in total throughput • Proportionally fair • Frequency agnostic schemes do not work well!

  14. Making it Work in Practice • Designed frequency translator with < 2 microsecond switching delay • Dynamic range of 100- 900 MHz • Integrates with a WiFi card on Sokeris box • Extensive indoor trials done • Waiting for experimental license for outdoor trials

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