Fairness awared joint sub-channel and power allocation via genetic algorithm in MIMO two-tier networks

Advanced interference coordination and resource management schemes are important in heterogeneous wireless networks in order to achieve a high network capacity and good user experience. In this paper, we present a joint consideration of the sub-channel allocation and power distribution in MIMO two-tier networks where the femtocells form clusters of equal size. All of the BSs have a multi-antenna configuration utilizing zero-forcing beamforming. The optimization objective maximizes the long-term system throughput and guarantees the fairness among Femto users (FUEs) in different tiers at the same time. After that, a modified genetic algorithm (GA) is addressed to resolve the mixed-integer nonlinear programming problem involved. Each chromosome in the proposed GA is divided into an integer string for sub-channel allocation, and a real number strings for power distribution. In addition, new initialization, crossover and mutation operations are employed for this new type of chromosomes. Conducted simulations show that the proposed GA can increase the throughput of the system and guarantee the fairness among the FUEs.