Hybrid Genetic Crossover Based Swarm Intelligence Optimization for Efficient Resource Allocation in MIMO OFDM Systems

Rapid development of wireless services, leads to ubiquitous personal connectivity in the world. The demand for multimedia interactivity is higher in the world which leads to the requirement of high data transmission rate. Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) is a future wireless service which is used to overcome the existing service problems such as development of subscriber pool and higher throughput per user. Although it overcomes the problems in existing services, resource allocation becomes one of the major issues in the MIMO-OFDM systems. Resource allocation in MIMO-OFDM is the optimization of subcarrier and power allocation for the user. The overall performance of the system can be improved only with the efficient resource allocation approach. The user data rate is increased by efficient allocation of the subcarrier and power allocation for each user at the base station, which is subject to constraints on total power and bit error rate. In this study, the problem of resource allocation in MIMO-OFDM system is tackled using hybrid artificial bee colony optimization algorithm based on a crossover operation along with Poisson-Jensen in equation. The experimental results show that the proposed methodology is better than the existing techniques.