Link Quality-Guaranteed Minimum-Cost Millimeter-Wave Base Station Deployment

TL;DR

This paper proposes a cost-effective millimeter-wave base station deployment strategy for urban environments that guarantees user outage constraints by leveraging macro diversity and solving a complex optimization problem.

Contribution

It introduces a novel approach to mmWave BS deployment that minimizes costs while ensuring outage constraints, using a decomposition method for an integer non-linear programming problem.

Findings

Optimal deployment solutions with guaranteed UE outage performance.

Distinct macro-diversity distribution compared to benchmarks.

Simulation results validate cost savings and reliability.

Abstract

Today's growth in the volume of wireless devices coupled with the promise of supporting data-intensive 5G-&-beyond use cases is driving the industry to deploy more millimeter-wave (mmWave) base stations (BSs). Although mmWave cellular systems can carry a larger volume of traffic, dense deployment, in turn, increases the BS installation and maintenance cost, which has been largely ignored in their utilization. In this paper, we present an approach to the problem of mmWave BS deployment in urban environments by minimizing BS deployment cost subject to BS association and user equipment (UE) outage constraints. By exploiting the macro diversity, which enables each UE to be associated with multiple BSs, we derive an expression for UE outage that integrates physical blockage, UE access-limited blockage, and signal-to-interference-plus-noise-ratio (SINR) outage into its expression. The minimum-cost BS deployment problem is then formulated as integer non-linear programming (INP). The combinatorial nature of the problem motivates the pursuit of the optimal solution by decomposing the original problem into the two separable subproblems, i.e., cell coverage optimization and minimum subset selection subproblems. We provide the optimal solution and theoretical justifications for each subproblem. The simulation results demonstrating UE outage guarantees of the proposed method are presented. Interestingly, the proposed method produces a unique distribution of the macro-diversity orders over the network that is distinct from other benchmarks.