Sub-modularity and Antenna Selection in MIMO systems

TL;DR

This paper demonstrates that antenna selection in MIMO systems can be optimized efficiently using greedy algorithms due to sub-modularity, leading to near-optimal solutions with reduced computational complexity.

Contribution

The paper proves sub-modularity of the antenna selection problem in MIMO systems and introduces efficient greedy algorithms with provable guarantees for optimal or near-optimal solutions.

Findings

Greedy algorithms achieve (1 - 1/e) approximation for MIMO antenna selection.

Relay antenna selection is modular and optimally solved with linear complexity.

Sub-modularity enables efficient antenna subset optimization in MIMO systems.

Abstract

In this paper, we show that the optimal receive antenna subset selection problem for maximizing the mutual information in a point-to-point MIMO system is sub-modular. Consequently, a greedy step-wise optimization approach, where at each step an antenna that maximizes the incremental gain is added to the existing antenna subset, is guaranteed to be within a (1 - 1/e) fraction of the global optimal value. For a single antenna equipped source and destination with multiple relays, we show that the relay antenna selection problem to maximize the mutual information is modular, when complete channel state information is available at the relays. As a result a greedy step-wise optimization approach leads to an optimal solution for the relay antenna selection problem with linear complexity in comparison to the brute force search that incurs exponential complexity.