Effects of Mobility on User Energy Consumption and Total Throughput in a Massive MIMO System

TL;DR

This paper introduces a methodology to analyze long-term energy consumption and throughput in massive MIMO systems considering user mobility, using stochastic models and PDE solutions, with potential extensions to multiple users and base stations.

Contribution

The paper presents a novel analytical approach to evaluate long-term performance metrics in mobile massive MIMO networks using stochastic mobility models and PDE eigenvalue solutions.

Findings

Energy consumption distribution can be derived analytically for Brownian motion mobility.

Throughput analysis accounts for fixed SINR and rate with channel inversion.

Method can be extended to Levy random walk and multi-user scenarios.

Abstract

Macroscopic mobility of wireless users is important to determine the performance and energy effciency of a wireless network, because of the temporal correlations it introduces in the consumed power and throughput. In this work we introduce a methodology that obtains the long time statistics of such metrics in a network. After describing the general approach, we present a specific example of the uplink channel of a mobile user in the vicinity of a massive MIMO base-station antenna array. To guarantee a fixed SINR and rate, the user inverts the path-loss channel power, while moving around in the cell. To calculate the long time distribution of the consumed energy of the user, we assume his movement follows a Brownian motion, and then map the problem to the solution of the minimum eigenvalue of a partial differential equation, which can be solved either analytically, or numerically very fast. We also treat the throughput of a single user. We then discuss the results and how they can be generalized if the mobility is assumed to be a Levy random walk. We also provide a roadmap to use this technique when one considers multiple users and base stations.