Novel Bee Colony Optimization with Update Quantities for OFDMA Resource Allocation

In recent years, large usage of wireless networks puts forward challenge to the utilization spectrum resources, and it is significant improve system sum data rates in premise fairness. However, existing algorithms have drawbacks efficiency maximize orthogonal frequency division multiple access (OFDMA) systems fairness threshold. To address issue, a novel artificial bee colony algorithm with update quantities nectar sources proposed for OFDMA resource allocation this paper. Firstly, population divided into several groups, different quantity set each group. Secondly, based on these are initialized by greedy subcarrier method. Thirdly, neighborhood searches updates performed dimensions corresponding preset quantities. The can not only make maintain high levels through but also use reduce be optimized algorithm, thereby making full both local optimization method global algorithm. simulation results show that, just equal-power stage, achieve required threshold effectively rates.