On the Performance of Variable-Rate HARQ-IR over Beckmann Fading Channels

TL;DR

This paper analyzes the performance of variable-rate HARQ-IR over Beckmann fading channels, deriving closed-form expressions for outage probability and throughput, and proposing an efficient rate optimization algorithm.

Contribution

It provides the first asymptotic analysis of variable-rate HARQ-IR over Beckmann channels with closed-form outage and throughput expressions, enabling rate optimization under outage constraints.

Findings

Closed-form outage probability and throughput expressions derived.

The proposed algorithm effectively maximizes throughput with lower complexity.

Asymptotic analysis offers clear insights into HARQ-IR performance over complex channels.

Abstract

This paper thoroughly investigates the performance of variable-rate hybrid automatic repeat request with incremental redundancy (HARQ-IR) over Beckmann fading channels, where Beckmann channel model is used to characterize the impacts of line-of-sight (LOS) path, time correlation between fading channels and unequal means & variances between the in-phase and the quadrature components. The intricate channel model and variable-rate transmission strategy significantly complicate the performance analysis. The complex form of the joint distribution of channel coefficients makes the exact analysis rather difficult. Hence, the asymptotic analysis of HARQ-IR is conducted to obtain tractable results. The outage probability and the long term average throughput (LTAT) are then derived in closed-form with clear insights. Furthermore, the simplicity of the obtained expressions enables the maximization of the LTAT given an outage constraint through choosing appropriate transmission rates. Particularly, the increasing monotonicity and the convexity of outage probability with respect to transmission rates allow us to solve the problem suboptimally by combining together alternately iterating optimization and concave fractional programming, and the proposed suboptimal algorithm has a lower computational complexity than the exhaustive search algorithm.