6: Opportunistic Communication and Multiuser Diversity
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Transcript of 6: Opportunistic Communication and Multiuser Diversity
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Fundamentals of Wireless Communication: Tse&Viswanath1
6: Opportunistic Communication and Multiuser Diversity
6: Opportunistic Communication and Multiuser Diversity
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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.)
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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.
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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.
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6: Opportunistic Communication and Multiuser Diversity
Multiuser Opportunistic Communication
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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)
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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.
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Symmetric Users
Serving the best user at each time is also fair in terms of long term throughputs.
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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.
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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.
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Performance
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Channel Dynamics
Channel varies faster and has more dynamic range in mobile environments.
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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.
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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?
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Dumb Antennas
The information bearing signal at each of the transmit antennais multiplied by a time-varying phase.
(Viswanath,Tse & Laroia 02)
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Slow Fading Environment: Before
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After
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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.
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Dumb Antennas in Action: One User
Most of the time, the beam is nowhere near the user.
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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.
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Performance Improvement
Mobile environment: 3 km/hr, Rayleigh fading
Fixed environment: 2Hz Rician fading with Efixed/Escattered =5.
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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.
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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.
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Conventional vs Opportunistic Communication