Distributing Complexity: A New Approach to Antenna Selection for Distributed Massive MIMO

TL;DR

This paper proposes a decentralized antenna selection algorithm for Massive MIMO systems that leverages environment awareness and self-organization to reduce complexity and enable real-time operation.

Contribution

It introduces a novel, simple, and computationally inexpensive decentralized antenna selection method based on self-organization and environment awareness.

Findings

The algorithm performs well with different power control rules.

It remains effective with varying numbers of users.

The method is suitable for real-time implementation.

Abstract

Antenna selection in Massive MIMO (Multiple Input Multiple Output) communication systems enables reduction of complexity, cost and power while keeping the channel capacity high and retaining the diversity, interference reduction, spatial multiplexity and array gains of Massive MIMO. We investigate the possibility of decentralised antenna selection both to parallelise the optimisation process and put the environment awareness to use. Results of experiments with two different power control rules and varying number of users show that a simple and computationally inexpensive algorithm can be used in real time. The algorithm we propose draws its foundations from self-organisation, environment awareness and randomness.