Optimal Link Adaptation for Multicarrier Communication Systems

TL;DR

This paper introduces a multiobjective optimization approach for link adaptation in multicarrier systems, balancing throughput maximization and power minimization simultaneously, leading to significant performance improvements.

Contribution

It proposes novel algorithms that optimize both throughput and power concurrently using multiobjective optimization, with adaptive weighting to reduce computational complexity.

Findings

Significant throughput gains over single-objective methods

Reduced transmit power while maintaining quality-of-service

Algorithms operate with no additional computational complexity

Abstract

Link adaptation is the terminology used to describe techniques that improve multicarrier communication systems performance by dynamically adapting the transmission parameters, i.e., transmit power and number of bits per subcarrier, to the changing quality of the wireless link. The research literature has focused on single objective optimization techniques to optimize the multicarrier communication systems performance, e.g., maximizing the throughput/capacity or minimizing the transmit power subject to a set of constraints. In this dissertation, we adopt a novel optimization concept, namely multiobjective optimization, where our objective is to simultaneously optimize the conflicting and incommensurable throughput and power objectives. More specifically, in some of the following Chapters, we propose novel algorithms that jointly maximize the multicarrier system throughput and minimize its total transmit power subject to quality-of-service, total transmit power, and maximum allocated bits per subcarrier constraints. The proposed algorithms require prior knowledge about the importance of the competing objective functions in terms of pre-determined weighting coefficients, or they can adapt the weighting coefficients during the solution process while meeting the constraints, in order to reduce the computational complexity. Simulation results show significant performance gains in terms of the achieved throughput and transmit power when compared to single optimization approaches, at the cost of no additional complexity.