Abstract
Beamforming is one of the most significant processes in smart antennas. To change the antenna beam pattern is the major function of beamforming for a given angle. The algorithm that is adaptive beamforming is utilized to choose the conventional weights of each array element from acquired data of array antenna to extract the desired source signal while cancelling noise and interference. A lot of algorithms are already existing for antenna beamforming technique but they all experience low convergence. So this paper deals with an iRLS algorithm for antenna beamforming technique with Particle Swarm Optimized (PSO) FFT filter. As a result, antenna beamforming based on iRLS shows fast convergence with reduced design complexity. The overall work is simulated in MATLAB. The parameters like amplitude, bit error rate, capacity, SINR and error function values are evaluated. Our work is compared with existing Applebaum, Recursive Least Squares (RLS) (with/without filter) and Least Mean Square (LMS) algorithm. Fast convergence is occurred by iRLS when compared with existing algorithms. The iRLS is converged at 90th iteration, whereas existing algorithms likewise RLS with pre-filter, RLS without pre-filter, LMS and Applebaum is converged at 200, 400, 600 and 850th iteration. So here, our proposed iRLS gives better performance when compared with others.
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Dighriri, M., Lee, G. M., & Baker, T. (2018). Measurement and Classification of Smart Systems Data Traffic Over 5G Mobile Networks (pp. 195–217). Cham: In Technology for Smart Futures Springer.
Niknejad, A.M., Thyagarajan, S.V and Venugopalan, S. (2018). Rf Pixels Inc, Multi-Antenna Beamforming and Spatial Multiplexing Transceiver. U.S. Patent Application 15/791,294.
Sharma, A., Mathur, S., & Gowri, R. (2018). Adaptive Beamforming for Linear Antenna Arrays Using Gravitational Search Algorithm. Intelligent Communication (pp. 1159–1169). Singapore: Control and Devices Springer.
Mohammadzadeh, S and Kukrer, O. (2018). Adaptive beamforming based on theoretical interference-plus-noise covariance and direction-of-arrival estimation. IET Signal Processing.
Zhang, X., He, Z., Liao, B., Zhang, X., & Peng, W. (2018). Robust Quasi-Adaptive Beamforming Against Direction-of-Arrival Mismatch. IEEE Transactions on Aerospace and Electronic Systems, 54(3), 1197–1207.
Qian, J., He, Z., Zhang, W., Huang, Y., Fu, N., & Chambers, J. (2018). Robust adaptive beamforming for multiple-input multiple-output radar with spatial filtering techniques. Signal Processing, 143, 152–160.
Zheng, Z., Zheng, Y., Wang, W. Q., & Zhang, H. (2018). Covariance Matrix Reconstruction With Interference Steering Vector and Power Estimation for Robust Adaptive Beamforming. IEEE Transactions on Vehicular Technology, 67(9), 8495–8503.
Tocca, V., Vigilante, D., Timmoneri, L and Farina, A. (2018). Adaptive beamforming algorithms performance evaluation for active array radars. In Radar Conference (RadarConf18), IEEE 0043–0048.
Castañeda, O., Jacobsson, S., Durisi, G., Goldstein, T and Studer, C. (2018). May. VLSI Design of a 3-bit Constant-Modulus Precoder for Massive MU-MIMO. In Circuits and Systems (ISCAS), 2018 IEEE International Symposium on IEEE, 1–5.
Zhang, M., Wang, X., Chen, X., & Zhang, A. (2018). The Kernel Conjugate Gradient Algorithms. IEEE Transactions on Signal Processing, 66(16), 4377–4387.
Parvathy, A and Narayanan, G. (2018). March. Comparative Study of Adaptive Algorithms Using Matlab and Verilog. In 2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET) IEEE, 1–6.
Lakshmi, T.J., Sivvam, S and Rajyalakshmi, V. (2018). January. Performance evaluation of smart antennas using non blind adaptive algorithms. In Signal Processing and Communication Engineering Systems (SPACES), 2018 Conference on IEEE. 66–71.
Khalaf, A.A., El-Daly, A.R.B and Hamed, H.F. (2018). A Hybrid NLMS/RLS Algorithm to Enhance the Beamforming Process of Smart Antenna Systems. Journal of Telecommunication, Electronic and Computer Engineering (JTEC), 10(1–4), 15–22.
Sun, D., Liu, L., & Zhang, Y. (2018). Recursive regularisation parameter selection for sparse RLS algorithm. Electronics Letters, 54(5), 286–287.
Kim, G., Lee, H., Chung, J., & Lee, J. (2018). A Delay Relaxed RLS-DCD Algorithm for Real-Time Implementation. IEEE Transactions on Circuits and Systems II: Express Briefs, 65(1), 61–65.
Chuku, P., Olwal, T and Djouani, K. (2018). Adaptive array beamforming using an enhanced RLS algorithm, International Journal on AdHoc Networking Systems (IJANS) 8 (1).
Sharma, R., Senapati, A and Roy, J.S. (2018). Beamforming of smart antenna in cellular network using leaky LMS algorithm. In 2018 Emerging Trends in Electronic Devices and Computational Techniques (EDCT) IEEE. 1–5.
Lu, L., Zhao, H., & Chen, B. (2018). Robust Adaptive Algorithm for Smart Antenna System With alpha -Stable Noise. IEEE Transactions on Circuits and Systems II: Express.
Biswas, R. N., Saha, A., Mitra, S. K., & Naskar, M. K. (2019). Realization of PSO-Based Adaptive Beamforming Algorithm for Smart Antennas (pp. 135–163). Cham: In Advances in Nature-Inspired Computing and Applications Springer.
Deepa, B., & Roopa, B. (2018). Adaptive Beam Steering of Smart Linear Array Using LMS and RLS Algorithms. Microelectronics (pp. 759–766). Singapore: Electromagnetics and Telecommunications Springer.
Abu-Ella, O and El-Jabu, B. (2010). Adaptive Beamforming Algorithm Using a Pre-filtering System. Aerospace Technologies Advancements, 417.
Zalawadia, K.R., Doshi, T.V and Dalal, U.D. (2011, October). Adaptive beam former design using RLS algorithm for smart antenna system. In 2011 International Conference on Computational Intelligence and Communication Networks, IEEE, 102–106.
Chuku, P., Olwal, T., & Djouani, K. (2018). Adaptive array beamforming using an enhanced RLS algorithm. Int J Ad Hoc Netw Syst, 8, 13–18.
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*Swapnil Manohar Hirikude & Dr.Suhas S. Patil have declared that there is no conflict of interest.
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Hirikude, S.M., Patil, S.S. Design of iRLS Algorithm With/Without Pre-Filter for Antenna Beam Forming Technique. Wireless Pers Commun 118, 2785–2805 (2021). https://doi.org/10.1007/s11277-021-08155-2
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DOI: https://doi.org/10.1007/s11277-021-08155-2