Sub-Stream Fairness and Numerical Correctness in MIMO Interference Channels

TL;DR

This paper introduces a distributed power control algorithm to achieve sub-stream fairness in MIMO interference channels, analyzes the impact of algorithm parameters on performance, and proposes group filtering schemes for improved stream design.

Contribution

It presents a novel distributed power control method for sub-stream fairness, analyzes parameter effects on numerical correctness, and proposes group filtering for joint stream design.

Findings

Sub-stream fairness can be achieved with the proposed algorithm.

Algorithm parameters significantly influence SINR and rate metrics.

Group filtering schemes outperform separate stream design methods.

Abstract

Signal-to-interference plus noise ratio (SINR) and rate fairness in a system are substantial quality-of-service (QoS) metrics. The acclaimed SINR maximization (max-SINR) algorithm does not achieve fairness between user's streams, i.e., sub-stream fairness is not achieved. To this end, we propose a distributed power control algorithm to render sub-stream fairness in the system. Sub-stream fairness is a less restrictive design metric than stream fairness (i.e., fairness between all streams) thus sum-rate degradation is milder. Algorithmic parameters can significantly differentiate the results of numerical algorithms. A complete picture for comparison of algorithms can only be depicted by varying these parameters. For example, a predetermined iteration number or a negligible increment in the sum-rate can be the stopping criteria of an algorithm. While the distributed interference alignment (DIA) can reasonably achieve sub-stream fairness for the later, the imbalance between sub-streams increases as the preset iteration number decreases. Thus comparison of max-SINR and DIA with a low preset iteration number can only depict a part of the picture. We analyze such important parameters and their effects on SINR and rate metrics to exhibit numerical correctness in executing the benchmarks. Finally, we propose group filtering schemes that jointly design the streams of a user in contrast to max-SINR scheme that designs each stream of a user separately.