Abstract
A novel beamforming technique based on Particle Swarm Optimization (PSO) algorithm and its subsequent implementation on Xilinx Virtex4 Field-Programmable Gate Arrays (FPGA) board is described. A prescribed limit in Side-Lobes Level (SLL) , Beamwidth between the First Nulls (FNBW) and depth of the nulls steered at various interfering directions are considered as beam controlling attributes in this work. All these criteria are included first in two dissimilar reference templates using Dolph–Chebyshev polynomial and Cosine function. Stochastic process is used next to optimize the physical and electrical parameters of a linear antenna array satisfactorily complying with the desired pattern features altogether. System design using Finite State Machine with Datapath (FSMD) modeling and suitable COordinate Rotation DIgital Computer (CORDIC) functional blocks are prepared for its final realization on a dedicated hardware. Its performance is then evaluated with several fixed-point simulations in terms of beamforming accuracy and computational overheads under both Additive White Gaussian Noise (AWGN) and Rayleigh fading channel conditions. These results corroborate its competency comparable to the existing beamforming methods of smart antennas.
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Biswas, R.N., Saha, A., Mitra, S.K., Naskar, M.K. (2019). Realization of PSO-Based Adaptive Beamforming Algorithm for Smart Antennas. In: Shandilya, S., Shandilya, S., Nagar, A. (eds) Advances in Nature-Inspired Computing and Applications. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-96451-5_6
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