Author(s)

Ranganathan Vignesh, K. A. Narayanankutty

Department of Electronics and Communication Engineering, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham (Amrita University), Coimbatore, India.

Blind adaptive beamforming is getting appreciated for its various applications in contemporary communication systems where sources are statistically dependent or independent that are allowed to formulate new algorithms. Qualitative performance and time complexity are the main issues. In this paper, we propose a technique for constant modulus signals applying basic non-negative matrix factorization (BNMF) in blind adaptive beamforming environment. We compared the existing Unscented Kalman Filter based Constant Modulus Algorithm (UKF-CMA) with proposed NMF-UKF-CMA algorithm. We see there is a better improvement of sensor array gain, signal to interference plus noise ratio (SINR) and mean squared deviation (MSD) as the noise variance and the array size increase with reduced computational complexity with the UKF-CMA.

Blind Adaptive Beamforming, NMF-UKF-CMA, Performance Comparison, UKF-CMA, MSD, SINR

Vignesh, R. and Narayanankutty, K. (2016) Non-Negative Matrix Factorization Based UKF Algorithm for Constant Modulus Signals in Adaptive Beamforming. Open Journal of Antennas and Propagation, 4, 119-127. doi: 10.4236/ojapr.2016.43009.