Aspects of limited feedback, cooperation and coordination in multi-antenna cellular systems

Multi-antenna schemes have been shown to provide remarkable gains in terms of spectral efficiency and extensive research has been dedicated to studying those in detail, discovering new setups in which multi-input multioutput (MIMO) schemes can be used and making them practical. This thesis is concerned with certain aspects of two particular setups in which MIMO techniques may be implemented, which we summarize below. Limited feedback in the MIMO broadcast channel: We consider the downlink of a single cell where the base station (BS) has multiple antennas. A particular issue when dealing with such a system is that of channel state information at the transmitter (CSIT): this has been shown to play a cardinal role, particularly in the case when users are equipped with single antennas. Given the importance of acquiring that CSIT, and the fact that this acquisition comes at the cost of using resources on the uplink direction and introducing delays, a large body of literature has been concerned with limited feedback schemes for this setup. In this thesis, we contribute two ideas to try to make the most of the available feedback resource. Coordination and Cooperation in multicell systems: The above model of a single cell corresponds roughly to current cellular designs where frequency planning is used to separate cells that use the same frequency resources so that inter-cell interference is limited. This is however not very efficient and MIMO techniques may be used to allow for increased performance at full reuse. Thus incorporating more antennas at a given BS gives it the possibility to mitigate the interference it causes at users in other cells. This is one of the topics we deal with in this thesis and propose a scheme which, while requiring local CSI only, is shown to perform quite well. MIMO techniques in a multicell environment can moreover extend to multicell processing (MCP), whereby several BSs pool their antennas to essentially act as a giant MIMO transmitter. This, however, has significant costs in terms of backhaul for data and CSI sharing, which threatens the scalability of MCP. We start investigating how to deal with limitations related to both these aspects. i pa st el -0 00 06 16 2, v er si on 1 25 J un 2 01 0

[1]  Andrea J. Goldsmith,et al.  Duality, achievable rates, and sum-rate capacity of Gaussian MIMO broadcast channels , 2003, IEEE Trans. Inf. Theory.

[2]  Shlomo Shamai,et al.  On the achievable throughput of a multiantenna Gaussian broadcast channel , 2003, IEEE Transactions on Information Theory.

[3]  David Gesbert,et al.  Efficient Metrics for Scheduling in MIMO Broadcast Channels with Limited Feedback , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[4]  Nihar Jindal MIMO broadcast channels with finite rate feedback , 2005, GLOBECOM.

[5]  Shlomo Shamai,et al.  The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel , 2006, IEEE Transactions on Information Theory.

[6]  Gregory W. Wornell,et al.  MIMO Broadcast Scheduling with Quantized Channel State Information , 2006, 2006 IEEE International Symposium on Information Theory.

[7]  Raymond Knopp,et al.  Information capacity and power control in single-cell multiuser communications , 1995, Proceedings IEEE International Conference on Communications ICC '95.

[8]  David Gesbert,et al.  Enhanced multiuser random beamforming: dealing with the not so large number of users case , 2008, IEEE Journal on Selected Areas in Communications.

[9]  E. Visotsky,et al.  Optimum beamforming using transmit antenna arrays , 1999, 1999 IEEE 49th Vehicular Technology Conference (Cat. No.99CH36363).

[10]  Jamie S. Evans,et al.  Multiuser Transmit Beamforming via Regularized Channel Inversion: A Large System Analysis , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[11]  David Tse,et al.  Linear Multiuser Receivers: Effective Interference, Effective Bandwidth and User Capacity , 1999, IEEE Trans. Inf. Theory.

[12]  David Tse,et al.  Downlink-uplink duality and effective bandwidths , 2002, Proceedings IEEE International Symposium on Information Theory,.

[13]  Helmut Bölcskei,et al.  Interference alignment with limited feedback , 2009, 2009 IEEE International Symposium on Information Theory.

[14]  G. Wornell,et al.  MIMO Broadcast Scheduling with Limited Channel State Information , 2005 .

[15]  Jamie S. Evans,et al.  Large system performance of linear multiuser receivers in multipath fading channels , 2000, IEEE Trans. Inf. Theory.

[16]  Shlomo Shamai,et al.  Cooperative Multicell Zero-Forcing Beamforming in Cellular Downlink Channels , 2009, IEEE Transactions on Information Theory.

[17]  Philippe Loubaton,et al.  On the Capacity Achieving Covariance Matrix for Rician MIMO Channels: An Asymptotic Approach , 2007, IEEE Transactions on Information Theory.

[18]  Howard C. Huang,et al.  Optimum power allocation for the MIMO-BC zero-forcing precoder with per-antenna power constraints , 2006, 2006 40th Annual Conference on Information Sciences and Systems.

[19]  Antonia Maria Tulino,et al.  Random Matrix Theory and Wireless Communications , 2004, Found. Trends Commun. Inf. Theory.

[20]  Babak Hassibi,et al.  On the capacity of MIMO broadcast channels with partial side information , 2005, IEEE Transactions on Information Theory.

[21]  Robert W. Heath,et al.  An overview of limited feedback in wireless communication systems , 2008, IEEE Journal on Selected Areas in Communications.

[22]  D. Slepian,et al.  A coding theorem for multiple access channels with correlated sources , 1973 .

[23]  Jeffrey G. Andrews,et al.  Multi-user Aware Limited Feedback for MIMO Systems , 2007 .

[24]  Stephen V. Hanly,et al.  Base Station Cooperation on the Downlink: Large System Analysis , 2010, IEEE Transactions on Information Theory.

[25]  Wei Yu,et al.  Coordinated beamforming for the multi-cell multi-antenna wireless system , 2008, 2008 42nd Annual Conference on Information Sciences and Systems.

[26]  Dirk T. M. Slock,et al.  Interference alignment limits for K-user frequency-flat MIMO interference channels , 2009, 2009 17th European Signal Processing Conference.

[27]  Gerhard Fettweis,et al.  On Base Station Cooperation Schemes for Downlink Network MIMO under a Constrained Backhaul , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[28]  Shlomo Shamai,et al.  Downlink Multicell Processing with Limited-Backhaul Capacity , 2009, EURASIP J. Adv. Signal Process..

[29]  Wei Yu,et al.  Uplink-downlink duality via minimax duality , 2006, IEEE Transactions on Information Theory.

[30]  John N. Tsitsiklis,et al.  On the complexity of decentralized decision making and detection problems , 1985 .

[31]  A. Lee Swindlehurst,et al.  A vector-perturbation technique for near-capacity multiantenna multiuser communication-part II: perturbation , 2005, IEEE Transactions on Communications.

[32]  Leandros Tassiulas,et al.  Transmit beamforming and power control for cellular wireless systems , 1998, IEEE J. Sel. Areas Commun..

[33]  David Tse,et al.  Opportunistic beamforming using dumb antennas , 2002, IEEE Trans. Inf. Theory.

[34]  M. J. Gans,et al.  On Limits of Wireless Communications in a Fading Environment when Using Multiple Antennas , 1998, Wirel. Pers. Commun..

[35]  David Gesbert,et al.  Decentralising Multicell Cooperative Processing: A Novel Robust Framework , 2009, EURASIP J. Wirel. Commun. Netw..

[36]  Robert W. Heath,et al.  What is the value of limited feedback for MIMO channels? , 2004, IEEE Communications Magazine.

[37]  T. Sälzer,et al.  From Single User to Multiuser Communications : Shifting the MIMO Paradigm , 2007 .

[38]  William Equitz,et al.  Successive refinement of information , 1991, IEEE Trans. Inf. Theory.

[39]  Roy D. Yates,et al.  Optimum Zero-forcing Beamforming with Per-antenna Power Constraints , 2007, 2007 IEEE International Symposium on Information Theory.

[40]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[41]  R. Radner,et al.  Team Decision Problems , 1962 .

[42]  Nihar Jindal,et al.  Multi-Antenna Broadcast Channels with Limited Feedback and User Selection , 2006 .

[43]  Alexander M. Haimovich,et al.  CTH11-2: Distributed Multi-Cell Zero-Forcing Beamforming in Cellular Downlink Channels , 2006, IEEE Globecom 2006.

[44]  Giuseppe Caire,et al.  Joint Beamforming and Scheduling for a Multi-Antenna Downlink with Imperfect Transmitter Channel Knowledge , 2007, IEEE Journal on Selected Areas in Communications.

[45]  Ami Wiesel,et al.  Linear precoding via conic optimization for fixed MIMO receivers , 2006, IEEE Transactions on Signal Processing.

[46]  Ami Wiesel,et al.  Zero-Forcing Precoding and Generalized Inverses , 2008, IEEE Transactions on Signal Processing.

[47]  Roy D. Yates,et al.  On the Maximum Common Rate Achievable in a Coordinated Network , 2006, 2006 IEEE International Conference on Communications.

[48]  Roy D. Yates,et al.  Adaptive transmission with finite code rates , 2006, IEEE Transactions on Information Theory.

[49]  Andrea J. Goldsmith,et al.  On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming , 2006, IEEE Journal on Selected Areas in Communications.

[50]  N.D. Sidiropoulos,et al.  On downlink beamforming with greedy user selection: performance analysis and a simple new algorithm , 2005, IEEE Transactions on Signal Processing.

[51]  J. W. Silverstein,et al.  On the empirical distribution of eigenvalues of a class of large dimensional random matrices , 1995 .

[52]  Erik G. Larsson,et al.  Competition Versus Cooperation on the MISO Interference Channel , 2008, IEEE Journal on Selected Areas in Communications.

[53]  Giuseppe Caire,et al.  Multiuser MIMO Downlink Made Practical: Achievable Rates with Simple Channel State Estimation and Feedback Schemes , 2007, ArXiv.

[54]  Wei Yu,et al.  Transmitter Optimization for the Multi-Antenna Downlink With Per-Antenna Power Constraints , 2007, IEEE Transactions on Signal Processing.

[55]  G.B. Giannakis,et al.  Quantifying the power loss when transmit beamforming relies on finite-rate feedback , 2005, IEEE Transactions on Wireless Communications.

[56]  Yu-Chi Ho,et al.  Team decision theory and information structures , 1980 .

[57]  Mohamed-Slim Alouini,et al.  How much feedback is multi-user diversity really worth? , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[58]  Yeheskel Bar-Ness,et al.  Asymptotic Analysis of Reduced-Feedback Strategies for MIMO Gaussian Broadcast Channels , 2008, IEEE Transactions on Information Theory.

[59]  Björn E. Ottersten,et al.  Acquiring Partial CSI for Spatially Selective Transmission by Instantaneous Channel Norm Feedback , 2008, IEEE Transactions on Signal Processing.

[60]  David Tse,et al.  Resource pooling and effective bandwidths in CDMA networks with multiuser receivers and spatial diversity , 2001, IEEE Trans. Inf. Theory.

[61]  A. Edelman Eigenvalues and condition numbers of random matrices , 1988 .

[62]  Jamie S. Evans,et al.  Scaling results on the sum capacity of cellular networks with MIMO links , 2006, IEEE Transactions on Information Theory.

[63]  Thomas L. Marzetta,et al.  Fast transfer of channel state information in wireless systems , 2006, IEEE Transactions on Signal Processing.

[64]  John M. Cioffi,et al.  Opportunistic Feedback Protocol for Achieving Sum-Capacity of the MIMO Broadcast Channel , 2007, 2007 IEEE 66th Vehicular Technology Conference.

[65]  Gerhard Fettweis,et al.  A Framework for Optimizing the Uplink Performance of Distributed Antenna Systems under a Constrained Backhaul , 2007, 2007 IEEE International Conference on Communications.

[66]  Andrea J. Goldsmith,et al.  Finite-Rate Feedback MIMO Broadcast Channels with a Large Number of Users , 2006, 2006 IEEE International Symposium on Information Theory.

[67]  Syed Ali Jafar,et al.  Interference Alignment and Spatial Degrees of Freedom for the K User Interference Channel , 2007, 2008 IEEE International Conference on Communications.

[68]  Emre Telatar,et al.  Capacity of Multi-antenna Gaussian Channels , 1999, Eur. Trans. Telecommun..

[69]  Mérouane Debbah,et al.  Outage efficient strategies for network MIMO with partial CSIT , 2009, 2009 IEEE International Symposium on Information Theory.

[70]  Erik G. Larsson,et al.  Complete Characterization of the Pareto Boundary for the MISO Interference Channel , 2008, IEEE Transactions on Signal Processing.

[71]  Roy D. Yates,et al.  A Framework for Uplink Power Control in Cellular Radio Systems , 1995, IEEE J. Sel. Areas Commun..

[72]  S. Barbarossa,et al.  Asynchronous Iterative Waterfilling for Gaussian Frequency-Selective Interference Channels: A Unified Framework , 2007, 2007 Information Theory and Applications Workshop.

[73]  Gerhard Kramer,et al.  Topics in Multi-User Information Theory , 2008, Found. Trends Commun. Inf. Theory.

[74]  Erik G. Larsson,et al.  The MISO Interference Channel : Competition versus Collaboration , 2007 .

[75]  Jeffrey G. Andrews,et al.  Orthogonal Beamforming for SDMA Downlink with Limited Feedback , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

[76]  Antonia Maria Tulino,et al.  Impact of antenna correlation on the capacity of multiantenna channels , 2005, IEEE Transactions on Information Theory.

[77]  Allen Gersho,et al.  Vector quantization and signal compression , 1991, The Kluwer international series in engineering and computer science.

[78]  Erik G. Larsson,et al.  The MISO interference channel from a game-theoretic perspective: A combination of selfishness and altruism achieves pareto optimality , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.

[79]  Zhi-Quan Luo,et al.  Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem , 2003, IEEE Trans. Signal Process..

[80]  Emil Björnson,et al.  Cooperative Multicell Precoding: Rate Region Characterization and Distributed Strategies With Instantaneous and Statistical CSI , 2010, IEEE Transactions on Signal Processing.

[81]  John M. Cioffi,et al.  Optimized transmission for fading multiple-access and broadcast channels with multiple antennas , 2006, IEEE Journal on Selected Areas in Communications.

[82]  Holger Boche,et al.  Effective bandwidth maximization for uplink/downlink multi-antenna systems , 2003, IEEE International Conference on Communications, 2003. ICC '03..

[83]  David Gesbert,et al.  Spectrum sharing in multiple-antenna channels: A distributed cooperative game theoretic approach , 2008, 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications.

[84]  O. Somekh,et al.  Joint multi-cell processing for downlink channels with limited-capacity backhaul , 2008, 2008 Information Theory and Applications Workshop.

[85]  J. Tsitsiklis Decentralized Detection' , 1993 .

[86]  R. Berry,et al.  Pricing Algorithms for Power Control and Beamformer Design in Interference Networks , 2009 .

[87]  H. Vincent Poor,et al.  Asymptotic spectral efficiency of multicell MIMO systems with frequency-flat fading , 2003, IEEE Trans. Signal Process..

[88]  David Tse,et al.  Multicell Downlink Capacity with Coordinated Processing , 2008, EURASIP J. Wirel. Commun. Netw..