Mathematical Model of Smart Antenna Beamforming using Adaptive Methods and Algorithms in a Dynamic Environmen

Abstract

The paper presents the results of a comprehensive simulation analysis of adaptive algorithms for controlling the directivity pattern (DP) of Smart antennas in a dynamic environment, taking into account the influence of the interference environment and the mobility of objects. The relevance of the study is due to the need to ensure stable communication between mobile platforms in conditions of multipath, frequent changes in the direction of the signal and the influence of intentional interference. The paper forms a mathematical model of a ring antenna array (RAA) of eight elements, which is used to analyze the effectiveness of known algorithms and methods for controlling the DP — NLMS, RLS, Levenberg – Marquardt, PSO, GA and MUSIC–WAA/MVDR. The developed model takes into account realistic radio channel parameters, including, as well as spatiotemporal dynamics of mobile users according to the Random Waypoint (RWP) model. For each algorithm, a comparative evaluation was carried out on the SINR metrics, interference suppression depth, main lobe width, side lobe level and convergence time. Experimental results confirmed that the classical NLMS and RLS algorithms provide an acceptable balance between accuracy and speed, while metaheuristic methods (PSO, GA) are characterized by high time costs and a tendency to local minima. The MUSIC–WAA/MVDR algorithm demonstrates high resolution and interference suppression depth, but is unstable in dynamic conditions. Based on the obtained results, a concept for creating a hybrid adaptive control algorithm for the MVD is proposed, which combines the stability of gradient methods with the accuracy of subspace approaches, which is a promising direction for further research in the field of Smart antennas in MANET systems