A Pareto Elite Selection Genetic Algorithm for Random Antenna Array Beamforming With Low Sidelobe Level

Abstract

Abstract-Random antenna array (RAA) that uses the conventional beamforming method produces a poor beam pattern with high sidelobe level. This greatly reduces the performance and the efficiency of the antenna. The use of Genetic Algorithm (GA) to find the best positions for the antenna elements in RAA to lower the sidelobes has been widely researched. However, there has been no solution proposed for the reduction of sidelobes when the user has no autonomy over the position of the radiating elements, for instance in cases such as emergency communications. This paper proposes a novel Pareto Elite Selection Genetic Algorithm (PESGA) optimization method to reduce the sidelobes in an RAA that has fixed elements' position. The proposed method uses a single fitness function (peak sidelobe level) for parent selection while an additional function (number of sidelobes above a threshold level) is introduced to select the elitist in every generation via Pareto Front (PF) selection. Results indicate that the proposed PESGA method is best used for scenarios where the array size is small. In such cases, the proposed method provides much reduced sidelobe compared to the conventional RAA beamforming method and up to 200% improvements in terms of mainlobe to peak sidelobe ratio compared to GA weight optimized beamforming method.

PSOGSA-Explore: A new hybrid metaheuristic approach for beampattern optimization in collaborative beamforming

“…However, it has been noted in [25]that the minimization of PSL comes at the cost of wider beamwidth.…”

“…PSL minimization in distributed beamforming has also been adopted by using GA based weight synthesis method [25,26]. However, it has been noted in [25]that the minimization of PSL comes at the cost of wider beamwidth.…”

Beampatten optimization in distributed beamforming using multiobjective and metaheuristic method

“…Moreover, in contrast to the conventional uniform array, the secondary maxima of the array factor is not necessarily the highest peak sidelobe (PSL) in distributed beamforming [11]. It is important to form a transmit beam with low sidelobes since in many practical scenarios, the directions of unintended receivers that might be interrupted by the power from these sidelobes are unknown [12].…”

“…It has been shown in [11] that reducing the sidelobes could cause increase in the beamwidth of the mainlobe. Moreover, reduced sidelobes do not guarantee higher directivity.…”

“…Therefore, it is desirable to treat the design problem of beampattern optimization as a multiobjective one. Common design objectives in both centralized and distributed beamforming include directivity maximization [13], PSL minimization [3,6,11,13,14], first null beamwidth minimization [14,15] and energy reduction [6]. Suitable tradeoff between these characteristics has to be achieved to attain the best beampattern.…”