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

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 chance‐constrained 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.