A performance analysis of multi-hop ad hoc networks with adaptive antenna array systems

TL;DR

This paper analyzes the performance of multi-hop ad hoc networks using adaptive antenna arrays, demonstrating that spatial progress scales with the square root of user density and quantifying the benefits of adaptive antennas.

Contribution

It introduces a stochastic geometry-based analysis of MSR-Aloha with adaptive antennas and derives bounds on spatial progress, highlighting the impact of antenna systems on network performance.

Findings

Spatial density of progress scales as the square root of user density.

Optimal contention density is independent of user density.

Adaptive antenna arrays improve spatial progress in ad hoc networks.

Abstract

Based on a stochastic geometry framework, we establish an analysis of the multi-hop spatial reuse aloha protocol (MSR-Aloha) in ad hoc networks. We compare MSR-Aloha to a simple routing strategy, where a node selects the next relay of the treated packet as to be its nearest receiver with a forward progress toward the final destination (NFP). In addition, performance gains achieved by employing adaptive antenna array systems are quantified in this paper. We derive a tight upper bound on the spatial density of progress of MSR-Aloha. Our analytical results demonstrate that the spatial density of progress scales as the square root of the density of users, and the optimal contention density (that maximizes the spatial density of progress) is independent of the density of users. These two facts are consistent with the observations of Baccelli et al., established through an analytical lower bound and through simulations.