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.