Modified Adaptive Beamforming Algorithms for 4G-LTE Smart-Phones

Abstract

Recently, a huge demand for wireless communication, especially for cellular communication, has raised increased expectations. Current and future cellular communications demand wide coverage, high date transmission, very high quality, and spectrum utilization. These expectations will continue to increase because from the last few years use of mobile phones has reached more than one billion worldwide. Hence, effective spectrum utilization is indeed required to meet all these expectations. One of the most promising technologies for future mobile communication is the ‘adaptive antenna.’ The adaptive antenna is also known as ‘smart antenna.’ Smart antenna uses adaptive beamforming algorithms to detect and track the mobile user. One of the most commonly used beamforming algorithms is least mean square algorithm. This LMS algorithm is well known for its low complexity, fast tracking, and less prone to numerical errors. It requires only O(L) flops to calculate array weights, where ‘L’ is the number of antenna elements used. The use of LMS algorithm in wireless communication is widespread. It is used in many fields including cellular communication and surveillances. Standard LMS algorithm requires at least 90 iterations for the satisfactory performance. But this corresponds to almost half cycle of signal of interest (SOI). Due to this, LMS algorithm is not suitable for many wireless communication applications, particularly for 4G LTE, 5G, and beyond. This paper proposes two computationally efficient modified LMS algorithms, namely sign data LMS (SDLMS) and sign error LMS (SELMS). These SDLMS and SELMS algorithms require only 50 and 40 iterations to produce required beamforming in cellular communication. Hence, these algorithms have convergence improvement of 44.45 and 55.56% over standard LMS algorithm. Hence, the proposed SLMS and SELMS beamforming algorithms are most suitable for 4G LTE and beyond mobile communication.