Resource allocation using Genetic Algorithm in Heterogeneous Network

In this research work resource allocation for femto cell users (FUEs) formulated using genetic algorithm. Here two tier heterogeneous cellular Network is considered which includes macro cell and femto cell. The resources can also segregate for both the tiers. As macro Base station (MBS) Transmission power is large, hence wider coverage area and more users can be accommodated. Whereas, femtocell is an indoor solution having less transmitted power and small coverage area with limited user admission and guaranteed QoS. Some of the resources of macro cell can be dedicated for FUEs by putting Absolute blank subframe (ABS). It will minimize the intra tier interference between the macro cell and femto cell. As frequency resource is valuable and proper allocation should be done among the users in proportional fair manner for getting better throughput. In this research work along with system model resource allocation using genetic algorithm is derived. The obtained genetic algorithm results are compared with heuristic method (knapsack problem) and it is observed that genetic algorithm provides 42% better performance in comparison to the conventional heuristic method.