Interference Alignment for Clustered Multicell Joint Decoding

TL;DR

This paper investigates various strategies for mitigating intercluster interference in multicell joint decoding, including interference alignment and resource division, using advanced mathematical tools to analyze their capacity limits.

Contribution

It introduces a comprehensive analysis of four intercluster interference scenarios using Free Probability theory, providing new theoretical insights into their capacity performance.

Findings

Interference alignment can significantly improve sum-rate capacity.

Resource division reduces intercluster interference at the cost of spectral efficiency.

Analytical expressions for eigenvalue distributions are derived for different scenarios.

Abstract

Multicell joint processing has been proven to be very efficient in overcoming the interference-limited nature of the cellular paradigm. However, for reasons of practical implementation global multicell joint decoding is not feasible and thus clusters of cooperating Base Stations have to be considered. In this context, intercluster interference has to be mitigated in order to harvest the full potential of multicell joint processing. In this paper, four scenarios of intercluster interference are investigated, namely a) global multicell joint processing, b) interference alignment, c) resource division multiple access and d) cochannel interference allowance. Each scenario is modelled and analyzed using the per-cell ergodic sum-rate capacity as a figure of merit. In this process, a number of theorems are derived for analytically expressing the asymptotic eigenvalue distributions of the channel covariance matrices. The analysis is based on principles from Free Probability theory and especially properties in the R and Stieltjes transform domain.