A Review of The State of the Art of Beamforming Techniques and AI

The primary problem in today's world of rapidly advancing technology and rapidly growing data quantities is to reduce interference and maximize the potential of wireless communication networks. Beamforming, which is a real-time process that can produce several zeros in the direction of the interfering signal and a major lobe matching to the intended signal direction, has become very well-known in the field of modern wireless communications in recent years. Although these methods are useful for determining ideal weights and determining the arrival direction, they are particularly challenging to apply regularly in dynamic contexts where transmitters move and weights must be determined on a continuous basis. For this reason, there has recently been a growing demand for new optimisation techniques based on artificial intelligence, such as metaheuristics, ML and DL. The purpose of this review paper is to offer a brief summary of the latest research on traditional and AI-based beamforming optimisation algorithms.