Design and performance analysis of live model of Bessel beamformer for adaptive array system

Purpose – The purpose of this paper is to design and analyze the performance of live model of Bessel beamformer for thorough comprehension of beamforming in adaptive environment and compared with live model of least mean square (LMS) in terms of gain and mean square error (MSE). It presents the principal elements of communication system. The performance of designed live model is tested for its efficiency in terms of signal recovery, directive gain by minimizing MSE using the “wavrecord” function to bring live audio data in WAV format into the MATLAB workspace. These adaptive techniques are illustrated by appropriate examples. Design/methodology/approach – The proposed algorithm framework relies on MATLAB software with the goal to obtain high efficiency in terms of signal recovery, directive gain by minimizing MSE using the “wavrecord” function to bring live audio data in WAV format. It is assumed that this audio signal is only the message or the baseband signal received by the computer. Here the authors c...

[1]  Daniel J. Ryan,et al.  QAM and PSK codebooks for limited feedback MIMO beamforming , 2009, IEEE Transactions on Communications.

[2]  Kah-Seng Chung,et al.  Adaptive array beam forming using a combined RLS-LMS algorithm , 2008, 2008 14th Asia-Pacific Conference on Communications.

[3]  Rameshwar Kawitkar Issues in Deploying Smart Antennas in Mobile Radio Networks , 2008 .

[4]  Lajos Hanzo,et al.  Iterative Multiuser Minimum Symbol Error Rate Beamforming Aided QAM Receiver , 2008, IEEE Signal Processing Letters.

[5]  L. Godara Application of antenna arrays to mobile communications. II. Beam-forming and direction-of-arrival considerations , 1997, Proc. IEEE.

[6]  Kaliappan Gopalan,et al.  A comparison of speaker identification results using features based on cepstrum and Fourier-Bessel expansion , 1999, IEEE Trans. Speech Audio Process..

[7]  David H. Covarrubias,et al.  Design of Beam-Forming Networks for Multibeam Antenna Arrays Using Coherently Radiating Periodic Structures , 2012 .

[8]  Ali Ozen A comparative study of blind and nonblind trainings in a single-carrier WiMAX (IEEE 802.16-2004) radio , 2012 .

[9]  John A. Stine,et al.  Exploiting smart antennas in wireless mesh networks using contention access , 2006, IEEE Wireless Communications.

[10]  Jalal Abdulsayed Srar,et al.  Adaptive Array Beamforming Using a Combined LMS-LMS Algorithm , 2010, IEEE Transactions on Antennas and Propagation.

[11]  Dirk T. M. Slock,et al.  On the convergence behavior of the LMS and the normalized LMS algorithms , 1993, IEEE Trans. Signal Process..

[12]  T. Mohammad,et al.  MI-NLMS adaptive beamforming algorithm for smart antenna system applications , 2006 .

[13]  L. C. Godara,et al.  Applications Of Antenna Arrays To Mobile Communications, Part I: Performance Improvement, Feasibility, And System Considerations , 1997, Proceedings of the IEEE.

[14]  Robina Farooq,et al.  Sequential Studies of Beamforming Algorithms for Smart Antenna Systems , 2009 .

[15]  D. H. Covarrubias,et al.  Optimization on RF devices design applied in wireless communications , 2003 .

[16]  P. Philippe,et al.  One microphone singing voice separation using source-adapted models , 2005, IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2005..

[17]  George A. Kyriacou,et al.  Development of an Adaptive and a Switched Beam Smart Antenna System for Wireless Communications , 2006 .

[18]  Kah-Seng Chung,et al.  Performance of RLMS algorithm in adaptive array beam forming , 2008, 2008 11th IEEE Singapore International Conference on Communication Systems.

[19]  Vahid Tarokh,et al.  A practical transmit beamforming strategy for closed‐loop MIMO communication , 2012, Int. J. Commun. Syst..