On the Impact of Channel Estimation on the Design and Analysis of IRSA based Systems

TL;DR

This paper investigates how channel estimation affects IRSA system performance, proposing new methods for estimation, analyzing throughput under errors, and providing insights into parameter impacts with simulations.

Contribution

It introduces a channel estimation approach exploiting IRSA sparsity, analyzes throughput with estimation errors, and characterizes asymptotic performance using density evolution.

Findings

Channel estimation errors can cause up to 70% throughput loss.

Non-orthogonal pilots are effective for large-scale IRSA systems.

System parameters like pilot length and SNR significantly influence throughput.

Abstract

Irregular repetition slotted aloha (IRSA) is a distributed grant-free random access protocol where users transmit multiple replicas of their packets to a base station (BS). The BS recovers the packets using successive interference cancellation. In this paper, we first derive channel estimates for IRSA, exploiting the sparsity structure of IRSA transmissions, when non-orthogonal pilots are employed across users to facilitate channel estimation at the BS. Allowing for the use of non-orthogonal pilots is important, as the length of orthogonal pilots scales linearly with the total number of devices, leading to prohibitive overhead as the number of devices increases. Next, we present a novel analysis of the throughput of IRSA under practical channel estimation errors, with the use of multiple antennas at the BS. Finally, we theoretically characterize the asymptotic throughput performance of IRSA using a density evolution based analysis. Simulation results underline the importance of accounting for channel estimation errors in analyzing IRSA, which can even lead to 70% loss in performance in severely interference-limited regimes. We also provide novel insights on the effect of parameters such as pilot length, SNR, number of antennas at the BS, etc, on the system throughput.