Finite-Length Analysis of Frameless ALOHA with Multi-User Detection

TL;DR

This paper provides a finite-length analysis of frameless ALOHA with multi-user detection capabilities, optimizing its performance and validating results through simulations, to improve understanding of collision resolution in wireless networks.

Contribution

It introduces a finite-length analysis method for frameless ALOHA with multi-user detection, enabling performance optimization and validation via simulations.

Findings

Optimized frameless ALOHA performance depends on multi-user detection capability.

Finite-length analysis accurately predicts system behavior.

Simulation results confirm analytical predictions.

Abstract

In this paper we present a finite-length analysis of frameless ALOHA for a k multi-user detection scenario, i.e., assuming the receiver can resolve collisions of size k or smaller. The analysis is obtained via a dynamical programming approach, and employed to optimize the scheme's performance. We also assess the optimized performance as function of k. Finally, we verify the presented results through Monte Carlo simulations.