Time-Fractional User Association in Millimeter Wave MIMO Networks

TL;DR

This paper proposes a load-aware user association scheme for mmWave MIMO networks that accounts for interference dependency on user association, leading to improved network throughput.

Contribution

It introduces a novel load-aware user association method considering interference effects, formulated as a MINLP and solved via genetic algorithms.

Findings

Enhanced network throughput with the proposed scheme

Effective load balancing among base stations

Better interference management in mmWave MIMO networks

Abstract

User association determines which base stations a user connects to, hence affecting the amount of network interference and consequently the network throughput. Conventional user association schemes, however, assume that user instantaneous rates are independent of user association. In this paper, we introduce a new load-aware user association scheme for millimeter wave (mmWave) MIMO networks which takes into account the dependency of network interference on user association. This consideration is well suited for mmWave communications, where the links are highly directional and vulnerable to small channel variations. We formulate our user association problem as a mixed integer nonlinear programming (MINLP) and solve it using the genetic algorithm. We show that the proposed method can improve network performance by moving the traffic of congested base stations to lightly-loaded base stations and adjusting the interference accordingly. Our simulations confirm that our scheme results in a higher network throughput compared to conventional user association techniques.