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Drive Towards Spectral Efficiency

Modern Wireless Communication: When Shannon Meets Marconi David Tse Wireless Foundations, University of California, Berkeley ICASSP 2006 Toulouse, France May 16, 2006. Drive Towards Spectral Efficiency . Huge surge in air interface research in the past decade, driven by:

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Drive Towards Spectral Efficiency

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  1. Modern Wireless Communication:When Shannon Meets MarconiDavid TseWireless Foundations, University of California, BerkeleyICASSP 2006Toulouse, FranceMay 16, 2006

  2. Drive Towards Spectral Efficiency Huge surge in air interface research in the past decade, driven by: • explosive demand for tetherless connectivity • dramatic progress in implementation technology • success of second-generation cellular standards, esp. CDMA (IS-95) Significant impact has already been made. Eg. IS-95 (mid 90’s)  CDMA 2000 1x EV-DO (mid 00’s)4 to 8 fold increase in spectral efficiency …….and more to come.

  3. Historical Perspective Gugliemo Marconi Claude Shannon • Wireless communication has been around since 1900’s. • Ingenious system design techniques……. • but somewhat adhoc 1948 1901 • Information theory says every channel has a capacity. • Many recent advances based on understanding wireless channel capacity. New points of views arise.

  4. Multipath Fading 16dB Classical view: fading channels are unreliable Modern view: multipath fading can be exploited to increase spectral efficiency.

  5. Talk Outline Two stories: I: opportunistic communication (implemented in most 3G standards) II multiple antenna (MIMO) communication (emerging standards) Real advances based on integration of theory and system considerations.

  6. I: Opportunistic Communication

  7. Traditional Approach to Wireless System Design Compensates for deep fades via diversity techniques over time, frequency and space. (Glass is half empty.)

  8. 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.

  9. Multipath Fading: Another Look • Multipath fading provides high peaks to exploit. • Channel capacity is achieved by such an opportunistic strategy. (Goldsmith & Varaiya 93) • Point-to-point performance benefits mainly in the energy-limited rather than the bandwidth-limited regime.

  10. Multiuser Opportunistic Communication

  11. 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)

  12. 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.

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

  14. 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.

  15. Proportional Fair Scheduler Schedule 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.

  16. Performance

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

  18. 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?

  19. Dumb Antennas (Viswanath,Tse & Laroia 02) The information bearing signal at each of the transmit antenna is multiplied by a time-varying phase.

  20. Slow Fading Environment: Before

  21. After

  22. Beamforming Interpretation Antenna array: Beamforming Omni-directional antenna • Beamforming direction is controlled by the relative • phase (t). • Dumb antennas sweeps a beam over all directions.

  23. Dumb Antennas in Action: One User Most of the time, the beam is nowhere near the user.

  24. 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.

  25. Performance Improvement Mobile environment: 3 km/hr, Rayleigh fading Fixed environment: 2Hz Rician fading with Efixed/Escattered =5.

  26. 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.

  27. 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.

  28. II: MIMO Communication

  29. Channel Resources • Two fundamental resources: • Power (SNR) • Bandwidth (W) • Shannon’s famous capacity formula: • In high SNR (high spectral efficiency) regime, degree of • freedom gain has a much larger impact than power gain. • MIMO is an approach to yield such gain.

  30. Line-of-Sight Environment Energy is focused along a narrow beam. Power gain but no degree-of-freedom gain.

  31. Multipaths Comes to the Rescue A scattering environment provides multiple degrees of freedom a line-of-sight environment doesn’t have. (Foschini 96)

  32. Performance Limits Given a scattering environment and antenna arrays, what is maximal degrees of freedom achievable? Does not grow unbounded with number of multipaths due to limit in angular resolution.

  33. Angular Resolution Antenna array of length L lambdas provides angular resolution of 1/L: paths that arrive at angles closer are not very distinguishable. (Sayeed 02, Poon,Broderson & Tse 05)

  34. Clustered Model How many degrees of freedom are there in this channel?

  35. Dependency on Antenna Size

  36. Clustered Model device environment For Lt,Lr large, number of d.o.f.: where t, r are the total angular spreads of the scatterers at the transmitter and the receiver. (Poon,Brodersen,Tse 05)

  37. Spatial Channel Resource • Single-antenna: T seconds of transmission over a channel of bandwidth W yields WT degrees of freedom (Nyquist). • MIMO: Antenna array of size L over a channel with angular spread  yields L spatial degrees of freedom per second per Hz.

  38. Diversity and Multiplexing:Old Meets New • MIMO allows spatial multiplexing • But MIMO provides diversity as well. • In a richly scattered environment, there are resolvable angular paths. • This is the maximum amount of diversity available. • Increasing the amount of spatial multiplexing reduces the amount of diversity.

  39. Diversity-Multiplexing Tradeoff (Zheng & Tse 03) Richly scattered environment: Ltt = nt , Lrr = nr

  40. System Considerations • MIMO makes sense in indoor environments with high SNR and rich scattering. • MIMO-based products have started to appear in the WiFi space. (emerging 802.11n standard) • In wide-area cellular networks, users have wide ranges of SNR’s and angular spreads, so system design becomes more challenging. • How to get spatial degrees of freedom gain even when there is limited angular spread?

  41. Space-Division Multiple Access • SDMA exploits the geographical separation of users. • Increase system throughput. • But how to get high per-user peak rate when there is limited angular spread? • Idea: cooperation.

  42. Infrastructure Cooperation BS Base-stations cooperate to form a macro-array with large angular spread at each mobile. BS MIMO MIMO BS

  43. User Cooperation Users relay information for each other and act as virtual scatterers to increase the effective angular spread.

  44. Distributed MIMO • Node cooperation can increase effective angular spread. • Can it also be used to overcome device limitation? • Each single-antenna source node wants to talk to a specific destination node. • Without cooperation, total capacity is bounded irrespective of n. (interference-limited) • With joint processing, capacity grows linearly with n. (MIMO gain) • Interestingly, cooperation can achieve a capacity scaling of at least n2/3. (Aeron & Saligrama 06) n destination nodes n source nodes

  45. Conclusions • Modern wireless communication theory exploits fading to increase spectral efficiency. • Real advances require marriage of theory with understanding of system issues. • The new point of view even suggests that fading can be induced by appropriate system design.

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