Downlink Multicell Processing with Limited-Backhaul Capacity

Multicell processing in the form of joint encoding for the downlink of a cellular system is studied under the assumption that the base stations (BSs) are connected to a central processor (CP) via finitecapacity links (finite-capacity backhaul). To obtain analytical insight into the impact of finite-capacity backhaul on the downlink throughput, the investigation focuses on a simple linear cellular system (as for a highway or a long avenue) based on theWyner model. Several transmission schemes are proposed that require varying degrees of knowledge regarding the system codebooks at the BSs. Achievable rates are derived in closed-form and compared with an upper bound. Performance is also evaluated in asymptotic regimes of interest (high backhaul capacity and extreme signal-to-noise ratio, SNR) and further corroborated by numerical results. The major finding of this work is that even in the presence of oblivious BSs (that is, BSs with no information about the codebooks) multicell processing is able to provide ideal performance with relatively small backhaul capacities, unless the application of interest requires high data rate (i.e., high SNR) and the backhaul capacity is not allowed to increase with the SNR. In these latter cases, some form of codebook information at the BSs becomes necessary.

[1]  H. Vincent Poor,et al.  Downlink capacity of interference-limited MIMO systems with joint detection , 2004, IEEE Transactions on Wireless Communications.

[2]  Shlomo Shamai,et al.  Local Base Station Cooperation Via Finite-Capacity Links for the Uplink of Linear Cellular Networks , 2009, IEEE Transactions on Information Theory.

[3]  Shlomo Shamai,et al.  Distributed MIMO systems with oblivious antennas , 2008, 2008 IEEE International Symposium on Information Theory.

[4]  Andrea J. Goldsmith,et al.  Coverage Spectral Efficiency of Cellular Systems with Cooperative Base Stations , 2006, 2006 Fortieth Asilomar Conference on Signals, Systems and Computers.

[5]  F. Boccardi,et al.  Network MIMO with reduced backhaul requirements by MAC coordination , 2008, 2008 42nd Asilomar Conference on Signals, Systems and Computers.

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

[7]  David Tse,et al.  Downlink Macro-Diversity in Cellular Networks , 2007, 2007 IEEE International Symposium on Information Theory.

[8]  Anthony J. Weiss,et al.  Generalized belief propagation receiver for near-optimal detection of two-dimensional channels with memory , 2004, Information Theory Workshop.

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

[10]  Shlomo Shamai,et al.  Sum Rate Characterization of Joint Multiple Cell-Site Processing , 2007, IEEE Transactions on Information Theory.

[11]  Shlomo Shamai,et al.  An information theoretic view of distributed antenna processing in cellular systems , 2007 .

[12]  Nihar Jindal,et al.  MIMO broadcast channels with finite rate feedback , 2006, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[13]  S. Venkatesan,et al.  Network MIMO: Overcoming Intercell Interference in Indoor Wireless Systems , 2007, 2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers.

[14]  Huaiyu Dai,et al.  Cochannel Interference Mitigation and Cooperative Processing in Downlink Multicell Multiuser MIMO Networks , 2004, EURASIP J. Wirel. Commun. Netw..

[15]  Ralf R. Müller,et al.  Hard Fairness versus Proportional Fairness in Wireless Communications: the Single-Cell Case , 2006, ISIT.

[16]  Giuseppe Caire,et al.  Hard fairness versus proportional fairness in wireless communications: The Multiple-Cell Case , 2008, 2008 IEEE International Symposium on Information Theory.

[17]  Reinaldo A. Valenzuela,et al.  Network coordination for spectrally efficient communications in cellular systems , 2006, IEEE Wireless Communications.

[18]  Jamie S. Evans,et al.  Distributed Downlink Beamforming in Cellular Networks , 2007, 2007 IEEE International Symposium on Information Theory.

[19]  Shlomo Shamai,et al.  A Linear Interference Network with Local Side-Information , 2007, 2007 IEEE International Symposium on Information Theory.

[20]  Shlomo Shamai,et al.  Enhancing the cellular downlink capacity via co-processing at the transmitting end , 2001, IEEE VTS 53rd Vehicular Technology Conference, Spring 2001. Proceedings (Cat. No.01CH37202).

[21]  Shlomo Shamai,et al.  Communication Via Decentralized Processing , 2005, IEEE Transactions on Information Theory.

[22]  Jamie S. Evans,et al.  Distributed Decoding in a Cellular Multiple-Access Channel , 2004, IEEE Transactions on Wireless Communications.

[23]  Honglin Hu,et al.  Distributed Antenna Systems: Open Architecture for Future Wireless Communications , 2007 .

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

[25]  Jeffrey G. Andrews,et al.  The capacity gain from intercell scheduling in multi-antenna systems , 2008, IEEE Transactions on Wireless Communications.

[26]  Aaron D. Wyner,et al.  Shannon-theoretic approach to a Gaussian cellular multiple-access channel , 1994, IEEE Trans. Inf. Theory.

[27]  Shlomo Shamai,et al.  Uplink Macro Diversity with Limited Backhaul Capacity , 2007, 2007 IEEE International Symposium on Information Theory.

[28]  David Gesbert,et al.  Optimal and Distributed Scheduling for Multicell Capacity Maximization , 2008, IEEE Transactions on Wireless Communications.

[29]  Sergio Verdú,et al.  Spectral efficiency in the wideband regime , 2002, IEEE Trans. Inf. Theory.

[30]  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.