Comparison of self‐adaptive dynamic differential evolution and particle swarm optimization for smart antennas in wireless communication

Abstract

In this paper, ultrawide band (UWB) communication systems with eight transmitting and receiving ring antenna arrays are implemented to test the bit error rate and capacity performance. By using the ray-tracing technique to compute any given indoor wireless environment, the impulse response of the system can be calculated. The synthesized beamforming problem can be reformulated into a multiobjective optimization problem. Self-adaptive dynamic differential evolution (SADDE) and particle swarm optimization (PSO) are used to find the excitation current and the feed line length of each antenna to form the appropriate beam pattern. This pattern can then reduce the bit error rate and increase the channel capacity and receiving energy. Numerical results show that the fitness value and the convergence speed by the SADDE are better than those by the PSO. Moreover, the SADDE had better results for both line-ofsight and nonline-of-sight cases. In other words, compared with PSO, SADDE has improved more effectively the main beam radiation energy and reduced the multipath interference.

Optimization of Spreading Code Using Modified Differential Evolution for Wireless Communication

“…The implementation of ultra-wideband (UWB) communication systems with eight transmitting and receiving ring in antenna arrays are done in [10], to test the bit error rate and capacity performance. Calculation of the impulse response of the system is done by using the ray-tracing technique to compute any given indoor wireless environment.…”

“…Again optimization is a technique by which we can find the best solution among all the solutions. Here, differential evolutionary algorithm is used as a stochastic algorithm [10], [24]. Stochastic algorithms are generally nature-inspired algorithms, they have flexible behavior to adapt to a changing environment [25].…”

Differential Evolution in Wireless Communications: A Review

“…Also, DE was used to minimize the BER in Multi-User Multiple Input Multiple Output (MU-MIMO) [135] and in general, solving the beamforming problems subjected to different variables and constraints [136]. DE was used in the optimum allocation of bandwidth in Cellular IP network, thereby improving the QoS [137].…”