Hybrid-genetic-algorithm-based resource allocation for slow adaptive OFDMA system under channel uncertainty

7Citations
Citations of this article
10Readers
Mendeley users who have this article in their library.

Abstract

A resource allocation algorithm for the slow adaptive orthogonal frequency division multiple access system under channel uncertainty is considered. The optimisation objective maximises the long-term system throughput over subcarrier assignment and the constraint condition satisfies the short-term data rate requirements of individual users, except occasional outage. Such an objective has a natural chance-constrained programming formulation. To solve the chanceconstrained optimisation, the neural network and the genetic algorithm (GA) are integrated to develop a hybrid GA (HGA) which could satisfy the user data rate requirement with the target outage probability. The simulation tests verify that the HGA yields a higher long-term system throughput than the Li algorithm with the Bernstein approximation. © The Institution of Engineering and Technology 2014.

Cite

CITATION STYLE

APA

Xu, L., Li, Y., & Tang, Z. M. (2014). Hybrid-genetic-algorithm-based resource allocation for slow adaptive OFDMA system under channel uncertainty. Electronics Letters, 50(1), 30–32. https://doi.org/10.1049/el.2013.2697

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free