SpringerOpen Newsletter

Receive periodic news and updates relating to SpringerOpen.

Open Access Research

Interference mitigation techniques for clustered multicell joint decoding systems

Symeon Chatzinotas1* and Björn Ottersten12

Author Affiliations

1 Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, 6, rue Richard Coudenhove-Kalergi, 1359 Luxembourg, Luxembourg

2 Royal Institute of Technology (KTH), Osquldas v. 10, 100 44, Stockholm, Sweden

For all author emails, please log on.

EURASIP Journal on Wireless Communications and Networking 2011, 2011:132  doi:10.1186/1687-1499-2011-132

Published: 14 October 2011

Abstract

Multicell joint processing has originated from information-theoretic principles as a means of reaching the fundamental capacity limits of cellular networks. However, global multicell joint decoding is highly complex and in practice clusters of cooperating Base Stations constitute a more realistic scenario. In this direction, the mitigation of intercluster interference rises as a critical factor towards achieving the promised throughput gains. In this paper, two intercluster interference mitigation techniques are investigated and compared, namely interference alignment and resource division multiple access. The cases of global multicell joint processing and cochannel interference allowance are also considered as an upper and lower bound to the interference alignment scheme, respectively. Each case is modelled and analyzed using the per-cell ergodic sum-rate throughput as a figure of merit. In this process, the asymptotic eigenvalue distribution of the channel covariance matrices is analytically derived based on free-probabilistic arguments in order to quantify the sum-rate throughput. Using numerical results, it is established that resource division multiple access is preferable for dense cellular systems, while cochannel interference allowance is advantageous for highly sparse cellular systems. Interference alignment provides superior performance for average to sparse cellular systems on the expense of higher complexity.