Resource Allocation in LTE OFDMA Systems Using Genetic Algorithm and Semi-Smart Antennas

Orthogonal frequency division multiplexing (OFDMA) offers great spectrum efficiency and flexible frequency allocation to users without intra-cell interferences in LTE system. However, the cell edge users will experience high interferences from neighbouring cells. Many frequency reuse schemes have been proposed for improving the Signal to Interference and Noise Ratio (SINR) performance for cell edge users, most of them dividing available frequencies into groups for cell centre and cell edge users. In this research, we combine the traditional frequency scheme with novel semi-smart antennas and learning algorithm - Genetic Algorithm (GA). The semi-smart antennas can produce flexible coverage patterns for base stations (BSs) and the learning algorithm can coordinate the coverage patterns between BSs to minimise interferences for mobile units (MUs). A system level simulation contains 25 BSs and 1000 MUs has been developed. Simulation results show that the proposed scheme improves the total traffic load and reduces antenna propagation power for all cells compares to system with fixed coverage patterns.