Fitness landscape analysis for dynamic resource allocation in multiuser ofdm based cognitive radio systems.” Submitted

Abstract — Cognitive Radio (CR) is a promising technique for improving the spectrum efficiency in future wireless network. The downlink transmission in a multiuser Orthogonal Frequency Division Modulation (MU-OFDM) based CR system is investigated. Optimal allocating transmit power, bits and subcarriers among cognitive radio users can achieve high throughput while satisfying the given quality of services (QoS) requirements. The problem of dynamic allocation of transmit power, bits and secondary users in multiuser OFDM systems is a combinatorial optimization problem and is computationally complex. Accordingly, a simple while efficient algorithm is needed. It has been shown that memetic algorithms (MAs) outperform other traditional algorithms for many combinatorial optimization problems. On the other hand, the performance of MAs is highly dependent on specific problems. In order to achieve better performance, we need to select appropriate local search method and evolutionary operators for a memetic algorithm. Fitness landscape is an important technique for analyzing the behavior of combinatorial optimization problems. We apply the fitness landscape to analyze the optimization problem proposed in this paper. Accordingly, we derive a simple while efficient memetic algorithm with appropriate local search method and evolutionary operators for the resource allocation problem. Numerical experiments show that the performance of the proposed memetic algorithm is better than other existing algorithms. I