Synthesis of Mimo System With Scattering Using Binary Whale Optimization Algorithm With Crossover Operator

Abstract

In a MIMO system, scattering is always an important problem since it is closely related to the channel capacity of system. In most of previous works, scattering was usually neglected so as to simplify the process of analysis. Therefore, it is really necessary to investigate and understand the scattering effect on capacity. To this end, scattering is taken into consideration in terms of channel capacity in this paper. From the antenna point of view, antenna element layout can be viewed as an optimization problem. To resolve this problem, a binary whale optimization algorithm (BWOA) is proposed. We investigate the effect of scattering environment on the capacity of a MIMO system and make comparison with an existing method in performance. The simulated results demonstrate that the nonuniform sampling method is able to efficiently improve the capacity of system even for poor scattering environment. SYSTEM MODEL AND PROBLEM FORMULATIONConsider a narrow-band MIMO system, which consists of N t transmitter and N r receiver antennas. Assume that X ∈ C Nt×1 represents the vector of transmit signals and that N ∈ C Nr×1 denotes the Algorithm 1: Pseudo code of the BWOA Input: input parameters t, t max , l, r Output: X * Initialize the whales population X i (i = 1, 2, · · · , n) 1 Calculate the fitness of each search agent 2 X * =the best search agent 3 while t < t max do 4 for each search agent do 5 Update α, A, C, l and p 6 if p < 0.5 then 7 if |A| ≤ 1 then 8 Update the position of the current search agent by D = |C · x * (t) − X(t)| 9 X(t + 1) = X * (t) − A · D else 10 Update the position of the current search agent by the D = |C · x rand − X(t)| 11 X(t + 1) = x rand − A · D else 12 Update the position of the current search agent by D = |X * (t) − X(t)| 13 X(t + 1) = D · e bl + cos(2πl) + X(t) Calculate the probabilities using a transfer function taking Eqs. (12) and (13) 14 Crossover operator between x i and x i−1 by Eqs. (10) and (11) 15 Calculate the fitness of each search agent 16 Update X * if there is a better solution 17 t = t + 1 18

Hybrid Feature Selection Approach for Power Transformer Fault Diagnosis Based on Whale Optimization Algorithm and Extreme Learning Machine

“…When |A| ≥ 1, the whale will then perform a random search for food in the current state; otherwise, the whale will move towards the optimal position. The next process in the whale search is to carry out the foraging process, which is mainly divided into shrinking envelope and spiral update position [28]. The encircling process is represented in mathematical model as shown in Equations ( 9) and (10).…”

Emerging Swarm Intelligence Algorithms and Their Applications in Antenna Design: The GWO, WOA, and SSA Optimizers

“…The problem of scattering in a MIMO system is also of importance since it is related to the system channel capacity. The authors in [71] designed and optimized an antenna element of a MIMO system by applying a binary WOA with a crossover operator. Numerical results demonstrated the improvement of system capacity even for poor scattering environments.…”