Optimization of ARQ Protocols in Interference Networks with QoS Constraints

TL;DR

This paper develops an optimization framework for ARQ protocols in interference networks with QoS constraints, using Markov Decision Processes and linear fractional programming to improve packet delivery.

Contribution

It introduces a novel optimization approach for transmission strategies in interference networks with QoS, leveraging Markov Decision Processes and linear fractional programming.

Findings

Optimal strategies depend on QoS constraints

Numerical results demonstrate strategy effectiveness

Framework applicable to dynamic wireless networks

Abstract

We study optimal transmission strategies in interfering wireless networks, under Quality of Service constraints. A buffered, dynamic network with multiple sources is considered, and sources use a retransmission strategy in order to improve packet delivery probability. The optimization problem is formulated as a Markov Decision Process, where constraints and objective functions are ratios of time-averaged cost functions. The optimal strategy is found as the solution of a Linear Fractional Program, where the optimization variables are the steady-state probability of state-action pairs. Numerical results illustrate the dependence of optimal transmission/interference strategies on the constraints imposed on the network.