Distributed inter-cluster interference management for CoMP-based cellular networks

This paper proposes distributed inter-cluster interference management procedures for 1 Coordinated Multi-Point (CoMP) Time Division Duplexing (TDD) cellular networks, in which a set of base stations (BSs), that form a cluster, cooperate in the downlink (DL) and uplink (UL) transmissions to communicate with a group of users while causing interference to users in neighbor clusters. In order to reduce the complications associated to the estimation of the interfering channels, we describe new iterative procedures based on channel reciprocity that avoid such estimation by exploiting the received signal in the UL, provided that transmit and receive filters in DL and UL are properly designed. Simulations show that proposed techniques attain significant DL and UL spectral efficiency gains. Furthermore, an analysis of imperfect channel state information (CSI) at both ends is included, evidencing the robustness of the proposed procedures. Considerations on convergence are included.

[1]  Holger Boche,et al.  Downlink MMSE Transceiver Optimization for Multiuser MIMO Systems: Duality and Sum-MSE Minimization , 2007, IEEE Transactions on Signal Processing.

[2]  Jeffrey G. Andrews,et al.  Spectral efficiency limits in pilot-assisted cooperative communications , 2012, 2012 IEEE International Symposium on Information Theory Proceedings.

[3]  José Vidal Manzano,et al.  Distributed inter-cluster interference management for CoMP-based cellular networks , 2013, GLOBECOM 2013.

[4]  John M. Cioffi,et al.  Weighted sum-rate maximization using weighted MMSE for MIMO-BC beamforming design , 2008, IEEE Trans. Wirel. Commun..

[5]  Wei Yu,et al.  Iterative water-filling for Gaussian vector multiple-access channels , 2001, IEEE Transactions on Information Theory.

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

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

[8]  Björn E. Ottersten,et al.  Statistically Robust Design of Linear MIMO Transceivers , 2008, IEEE Transactions on Signal Processing.

[9]  Satoshi Nagata,et al.  LTE-advanced: an operator perspective , 2012, IEEE Communications Magazine.

[10]  Francisco Facchinei,et al.  Distributed dynamic pricing for MIMO interfering multiuser systems: A unified approach , 2011, International Conference on NETwork Games, Control and Optimization (NetGCooP 2011).

[11]  Jeffrey G. Andrews,et al.  Networked MIMO with clustered linear precoding , 2008, IEEE Transactions on Wireless Communications.

[12]  Gerhard Fettweis,et al.  Coordinated Multi-Point in Mobile Communications: From Theory to Practice , 2011 .

[13]  Martin Haardt,et al.  Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels , 2004, IEEE Transactions on Signal Processing.

[14]  Wolfgang Utschick,et al.  Distributed Interference Pricing for the MIMO Interference Channel , 2009, 2009 IEEE International Conference on Communications.