Asynchronous Downlink Massive MIMO Networks: A Stochastic Geometry Approach

TL;DR

This paper analyzes the performance of asynchronous downlink massive MIMO networks using stochastic geometry, revealing impacts on coverage, ergodic rate, and the influence of uplink power control and pilot symbols.

Contribution

It introduces a stochastic geometry framework for analyzing asynchronous massive MIMO systems, providing insights into their coverage and rate performance.

Findings

Asynchronous systems have different coverage probabilities compared to synchronous ones.

Optimal number of pilot symbols maximizes downlink ergodic rate.

Downlink ergodic rate is more sensitive to uplink power control in asynchronous mode.

Abstract

Massive multiple-input multiple-output (MIMO) is recognized as a promising technology for the next generation of wireless networks because of its potential to increase the spectral efficiency. In initial studies of massive MIMO, the system has been considered to be perfectly synchronized throughout the entire cells. However, perfect synchronization may be hard to attain in practice. Therefore, we study a massive MIMO system whose cells are not synchronous to each other, while transmissions in a cell are still synchronous. We analyze an asynchronous downlink massive MIMO system in terms of the coverage probability and the ergodic rate by means of the stochastic geometry tool. For comparison, we also obtain the results for the synchronous systems. In addition, we investigate the effect of the uplink power control and the number of pilot symbols on the downlink ergodic rate, and we observe that there is an optimal value for the number of pilot symbols maximizing the downlink ergodic rate of a cell. Our results also indicate that, compared to the cases with synchronous transmission, the downlink ergodic rate is more sensitive to the uplink power control in the asynchronous mode.