Energy Efficient Distributed Worst Case Robust Power Allocation in Massive MIMO

TL;DR

This paper introduces a distributed robust power allocation method for massive MIMO systems that maximizes energy efficiency while accounting for bounded CSI errors, using convex optimization techniques.

Contribution

It presents a novel energy-efficient distributed power allocation scheme for massive MIMO with worst-case robustness against CSI errors, employing fractional programming and SCA methods.

Findings

Algorithm converges quickly in simulations.

Robust power allocation improves energy efficiency.

Optimal number of antennas for maximum efficiency identified.

Abstract

This letter proposes an energy efficient distributed worst case robust power allocation in massive multiple input multiple output (MIMO) system. We assume a bounded channel state information (CSI) error and all channels lie in some bounded uncertainty region. The problem is formulated as max-min one with infinite constraint. At first, we solve the inner problem with triangle and Cauchy-Schwarz inequality, then by fractional programming and successive convex approximation (SCA) technique problem transfers to a convex optimization. Finally closed form transmit power is obtained with distribution way. Simulation results demonstrate proposed algorithm convergence and validate robust power allocation. Also, the appropriate number of transmit antenna to have maximum energy efficiency in simulation result is shown.