6: opportunistic communication and multiuser diversity

Fundamentals of Wireless Communication: Tse&Viswanath1

6: Opportunistic Communication and Multiuser Diversity




Traditional Approach to Wireless System Design

Compensates for deep fades via diversity techniques over time, frequency and space.(Glass is half empty.)



Example: CDMA

• frequency diversity via Rake combining• time diversity via interleaving and coding• macro-diversity via soft handoff • transmit/receive antenna diversity• interference diversity: averaging of interference from

many users.



Multipath Fading: Another Look

• Multipath fading provides high peaks to exploit.• Channel capacity is achieved by such an opportunistic

strategy. • Point-to-point performance benefits mainly in the energy-

limited rather than the bandwidth-limited regime.



Multiuser Opportunistic Communication



Multiuser Diversity

• In a large system with users fading independently, there is likely to be a user with a very good channel at any time.

• Long term total throughput can be maximized by always serving the user with the strongest channel (Knopp&Humblet 95)



Application to CDMA 2000 1x EV-DO

• Multiuser diversity provides a system-wide benefit.• Challenge is to share the benefit among the users in a

fair way.



Symmetric Users

Serving the best user at each time is also fair in terms of long term throughputs.



Asymmetric Users: Hitting the Peaks

Want to serve each user when it is at its peak.A peak should be defined with respect to the latency time-scale tc of the application.



Proportional Fair SchedulerSchedule the user with the highest ratio

Rk = current requested rate of user k

Tk = average throughput of user k in the past tc time slots.

(Tse 99)

De-facto scheduler in Ev-DO and similar algorithms used in HSDPA.



Performance



Channel Dynamics

Channel varies faster and has more dynamic range in mobile environments.



Why No Gain with High Mobility?

3 km/hr 30 km/hr 120 km/hr

Can only predict the average of the channel fluctuations,not the instantaneous values.



Inducing Randomness

• Scheduling algorithm exploits the nature-given channel fluctuations by hitting the peaks.

• If there are not enough fluctuations, why not purposely induce them?



Dumb Antennas

The information bearing signal at each of the transmit antennais multiplied by a time-varying phase.

(Viswanath,Tse & Laroia 02)



Slow Fading Environment: Before



After



Beamforming Interpretation

Omni-directional antenna Antenna array:Beamforming

• Beamforming direction is controlled by the relative phase (t).• Dumb antennas sweeps a beam over all directions.



Dumb Antennas in Action: One User

Most of the time, the beam is nowhere near the user.



Many users: Opportunistic Beamforming

•In a large system, there is likely to be a user near the beam at any one time.•By transmitting to that user, close to true beamforming performance is achieved, without knowing the locations of the users.



Performance Improvement

Mobile environment: 3 km/hr, Rayleigh fading

Fixed environment: 2Hz Rician fading with Efixed/Escattered =5.



Smart vs Dumb Antennas

• Space-time codes improve reliability of point-to-point links but reduce multiuser diversity gain.

• Dumb antennas add fluctuations to point-to-point links but increases multiuser diversity gains.



Cellular Systems: Opportunistic Nulling

• In a cellular systems, users are scheduled when their channel is strong and the interference from adjacent base-stations is weak.

• Dumb antennas provides opportunistic nulling for users in other cells.

• In practice, performance may be limited by interference averaging:

a user may be within range of several base-stations.



Conventional vs Opportunistic Communication

6: opportunistic communication and multiuser diversity

Documents