New Combined Adaptive (NCA) Algorithm for Smart Antenna System Applications

ABSTRACT

This paper proposes a new combined algorithm for performance enhancement of smart antenna systems in mobile communications. The new combined algorithm (NCA) uses sample matrix inversion (SMI) initialization with a modified version of normalized least mean square (NLMS) algorithm (MNLMS). The MNLMS algorithm is regarded as time-varying regularization parameter ϵ(k) that is fixed in the conventional NLMS algorithm. The MNLMS algorithm uses a reciprocal of the estimation error square term in the denominator of the learning rate of NLMS instead of fixed regularization parameter (ϵ). Through simulation results of smart antennas for an additive white Gaussian noise channel model, the NCA algorithm achieves about 15 and 19 dB improvement in interference suppression compared with NLMS and another proposed previously matrix inversion NLMS (MI-NLMS) algorithms, respectively. While the NLMS algorithm starts to converge from 50 iterations, the MI-NLMS and NCA algorithms start to converge from the initial iteration. Moreover, when this algorithm applied for the Rayleigh fading channel with a Jakes power spectral density, it provides about 7 dB improvements over NLMS and MI-NLMS algorithms and starts converge from the initial iteration. The NCA provides improved performance in weight stability for both channels.

Keywords:

• Sample matrix inversion (SMI)
• Least mean square (LMS)
• Normalized LMS (NLMS)
• Smart antenna
• Time-varying regularization parameter

ACKNOWLEDGEMENT

I would like to thank Professor Domanic Ho of Missouri University, USA, for his scientific advice and supporting during preparing this work.

Additional information

Notes on contributors

Thamer M. Jamel

Thamer M. Jamel was born in Baghdad, Iraq in 1961. He graduated from the University of Technology with a bachelor's degree in electronics engineering in 1983. He received a master's degree in digital communications engineering from the University of Technology in 1990 and a doctoral degree in communication engineering from the University of Technology in 1997. He is an associate professor in the Communication Engineering branch, Electrical Engineering Department at University of Technology, Baghdad, Iraq. Currently, he is a visitor scholar in the Electrical and Computer Engineering Department at University of Missouri, Columbia, MO. His research interests include adaptive signal processing, neural networks, DSP microprocessors, FPGA, and modern digital communications systems.

E-mail: [email protected]