Distortion Minimization for Relay Assisted Wireless Multicast

TL;DR

This paper proposes an optimization framework for minimizing end-to-end mean square error distortion in relay-assisted wireless multicast of scalable source symbols, demonstrating improved performance through case studies.

Contribution

It introduces a novel power allocation optimization for scalable source multicast in relay-assisted networks using a generalized programming approach.

Findings

Optimized power allocation reduces distortion effectively.

Relay assistance improves multicast quality.

Proposed methods outperform baseline strategies.

Abstract

The paper studies the scenario of wireless multicast with a single transmitter and a relay that deliver scalable source symbols to the receivers in a decode-and-forward (DF) fashion. With the end-to-end mean square error distortion (EED) as performance metric, we firstly derive the EED expression for the $L$-resolution scalable source symbol for any receiver. An optimization problem in minimizing the weighted EED is then formulated for finding the power allocations for all resolution layers at the transmitter and the relay. Due to nonlinearity of the formulations, we solve the formulated optimization problems using a generalized programming algorithm for obtaining good sub-optimal solutions. Case studies are conducted to verify the proposed formulations and solution approaches. The results demonstrate the advantages of the proposed strategies in the relay-assisted wireless networks for scalable source multicast.