Joint User and Beam Selection in Millimeter Wave Networks

TL;DR

This paper addresses the complex problem of joint user and beam selection in millimeter wave networks, proposing algorithms that achieve near-optimal performance and outperform existing methods.

Contribution

It introduces two asymptotically optimal algorithms and two fast greedy algorithms for joint user and beam selection in mmWave networks, with proven effectiveness.

Findings

Greedy algorithms outperform prior methods in simulations.

Proposed algorithms achieve near-optimal solutions.

NP-completeness of the problem is established.

Abstract

We study the problem of selecting a user equipment (UE) and a beam for each access point (AP) for concurrent transmissions in a millimeter wave (mmWave) network, such that the sum of weighted rates of UEs is maximized. We prove that this problem is NP-complete. We propose two algorithms -- Markov Chain Monte Carlo (MCMC) based and local interaction game (LIG) based UE and beam selection -- and prove that both of them asymptotically achieve the optimal solution. Also, we propose two fast greedy algorithms -- NGUB1 and NGUB2 -- for UE and beam selection. Through extensive simulations, we show that our proposed greedy algorithms outperform the most relevant algorithms proposed in prior work and perform close to the asymptotically optimal algorithms.