A Novel Modified Artificial Bee Colony for DOA Estimation

Aims: We consider the Direction of Arrival (DOA) estimation for code division multiple access (CDMA) signals. Background: Solving this problem requires non-linear optimization and thus the speed of convergence becomes crucial. Objective: A novel Modified Artificial Bee Colony (MABC) has been proposed. We use secondorder Taylor series expansion of the cost function to ameliorate the searchability of artificial bee colony (ABC) for finding the globally optimal solution. Methods: The main idea is to harness the exploration and exploitation features. The optimum point of second-order Taylor expansion of cost function is used as a velocity factor of the ABC algorithm. Results: The proposed technique is used for solving the DOA estimation problem of a CDMA system. Simulation results confirm the performance improvement of our proposed algorithm. Conclusion: The cost function of the DOA estimation usually leads to a non-linear optimization problem. Using evolutionary algorithms can improve convergence rate of such problems.