A Novel Efficient Initial Access Method for 5G Millimeter Wave Communications Using Genetic Algorithm

Initial Access (IA) in millimeter wave (mmWave) communications, i.e., the mechanism by which the Base Station (BS) and the User Equipment (UE) establish a directional communication link, is a challenging problem. A significant delay can be incurred when the BS and the UE try to find the appropriate beam alignment for obtaining a directional link, and solving this problem efficiently has become an important research topic. In this work, we propose a new beam refinement method based on Genetic Algorithms (GAs) which is particularly advantageous when the number of antennas is large. In particular, we consider a scenario where both the BS and the UE are equipped with a single RF chain and multiple antennas, i.e., a single beam analog beamforming is considered at the BS and UE. The efficiency of the proposed method and the effect of several parameters, such as the number of transmit and receive antennas, codebook size, and transmission power are investigated. In the case of small parameters, it is shown that the proposed method achieves the same capacity of Exhaustive Search (ES) but with a much lower complexity. Moreover, in comparison with existing methods, our method has a superior performance in terms of capacity, outage probability, and power consumption.