Distributed Multicell and Multiantenna Precoding: Characterization and Performance Evaluation

This paper considers downlink multiantenna communication with base stations that perform cooperative precoding in a distributed fashion. Most previous work in the area has assumed that transmitters have common knowledge of both data symbols of all users and full or partial channel state information (CSI). Herein, we assume that each base station only has local CSI, either instantaneous or statistical. For the case of instantaneous CSI, a parametrization of the beamforming vectors used to achieve the outer boundary of the achievable rate region is obtained for two multi-antenna transmitters and two single-antenna receivers. Distributed generalizations of classical beamforming approaches that satisfy this parametrization are provided, and it is shown how the distributed precoding design can be improved using the so-called virtual SINR framework [1]. Conceptually analog results for both the parametrization and the beamforming design are derived in the case of local statistical CSI. Heuristics on the distributed power allocation are provided in both cases, and the performance is illustrated numerically.

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

[2]  David Gesbert,et al.  Distributed Multicell-MISO Precoding Using the Layered Virtual SINR Framework , 2010, IEEE Transactions on Wireless Communications.

[3]  O. Somekh,et al.  Distributed MIMO in multi-cell wireless systems via finite-capacity links , 2008, 2008 3rd International Symposium on Communications, Control and Signal Processing.

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

[5]  Robert W. Heath,et al.  Shifting the MIMO Paradigm , 2007, IEEE Signal Processing Magazine.

[6]  Björn E. Ottersten,et al.  Utilizing the Spatial Information Provided by Channel Norm Feedback in SDMA Systems , 2008, IEEE Transactions on Signal Processing.

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

[8]  Kwang Bok Lee,et al.  Interference-Aware Decentralized Precoding for Multicell MIMO TDD Systems , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[9]  Björn E. Ottersten,et al.  Modeling of wide-band MIMO radio channels based on NLoS indoor measurements , 2004, IEEE Transactions on Vehicular Technology.

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

[11]  E.A. Jorswieck,et al.  Parameterization of the MISO interference channel with transmit beamforming and partial channel state information , 2008, 2008 42nd Asilomar Conference on Signals, Systems and Computers.

[12]  Jamie S. Evans,et al.  Distributed Downlink Beamforming With Cooperative Base Stations , 2008, IEEE Transactions on Information Theory.

[13]  David Gesbert,et al.  Distributed Beamforming Coordination in Multicell MIMO Channels , 2009, VTC Spring 2009 - IEEE 69th Vehicular Technology Conference.

[14]  B. Ottersten,et al.  On the principles of multicell precoding with centralized and distributed cooperation , 2009, 2009 International Conference on Wireless Communications & Signal Processing.

[15]  Emil Björnson,et al.  Post-user-selection quantization and estimation of correlated Frobenius and spectral channel norms , 2008, 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications.

[16]  Randa Zakhour,et al.  Coordination on the MISO interference channel using the virtual SINR framework , 2009 .

[17]  R. Valenzuela,et al.  Multiple input multiple output measurements and modeling in Manhattan , 2002, Proceedings IEEE 56th Vehicular Technology Conference.

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