On the Fly Self-Organized Base Station Placement

TL;DR

This paper proposes a novel method for on-the-fly self-organized placement of base stations in a one-dimensional network, optimizing user coverage and system performance using random matrix theory and game-theoretic approaches.

Contribution

It introduces a new random matrix theory-based technique for approximating the MMSE sum rate and models base station placement as a location game to enhance network performance.

Findings

Cooperative decoding significantly outperforms non-cooperative decoding.

Optimal BS placement involves a trade-off in position to maximize sum rate.

The proposed approach adapts to user distribution for improved deployment efficiency.

Abstract

In this paper, we address the deployment of base stations (BSs) in a one-dimensional network in which the users are randomly distributed.In order to take into account the users' distribution to optimally place the BSs we optimize the uplink MMSE sum rate. Moreover, given a massive number of antennas at the BSs we propose a novel random matrix theory-based technique so as to obtain tight approximations for the MMSE sum rate in the uplink. We investigate a cooperative (CP) scenario where the BSs jointly decode the messages and a non-cooperative (NCP) scheme in which the BS can only decode its own users. Our results show that the CP strategy considerably outperforms the NCP case. Moreover, we show that there exists a trade off in the BS deployment regarding the position of each BS. Thus, through location games we can optimize the position of each BS in order to maximize the system performance.