design issues for wireless networks across diverse and fragmented spectrum

All Rights Reserved © Alcatel-Lucent 2006, #####

Design Issues for Wireless Networks Across Diverse and Fragmented Spectrum

Collaborators:Bell Labs India: Supratim Deb, Kanthi NagarajBell Labs USA: Piyush Gupta

All Rights Reserved © Alcatel-Lucent 20092 | Connecting the Next Billion 2010 |

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


Research Goal

PHY + Sensing

MAC + Spectrum

Selection

Routing + Flow

Control

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

New Design Perspective

Lot of research


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

log fc

Rece

ived P

ow

er

at

fixed d

ista

nce

, pow

er

(dB

)

slope = － 20

Pow

er

Sp

ectr

al

Den

sit

y

All traditional network stack design issues require a fresh look.


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)

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Agile and Efficient MAC forUnlicensed Access in TV

Whitespaces and ISM Bands


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


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)

20 dBm

DTV

Chann

el

DTV

Chann

el

Freq

16 dBm

DTV

Chann

el

DTV

Chann

el

Freq


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


Joint Spectrum Selection and Client Allocation

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)

(1,2,3,4,5,6,7)

Joint Spectrum Selection and Client Assignment is a non-trivial problem


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

Client-1

Client-2 ASE = Data rate averaged over all clients / Hz

= a × (SNR averaged over all clients in dB) – bSNR(f1) － SNR(f2) ＝ 20 log(f2/f1)ASE in f1 can be generated for ASE in f2

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.


Proportional Fairness is Key for Whitespaces

6Mbps

2.4GHz

6Mbps600MHz

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


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!


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

design issues for wireless networks across diverse and fragmented spectrum

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