Sample-by-sample and block-adaptive robust constant modulus-based algorithms

• Published in: IET signal processing Vol. 6; no. 8; pp. 805 - 813
• Main Authors: Elnashar, A., Elnoubi, S., Elmikati, H.
• Format: Journal Article
• Language: English
• Published: Stevenage Institution of Engineering and Technology 01.10.2012; John Wiley & Sons, Inc
• Subjects: Adaptive algorithms; Applied sciences; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; Information, signal and communications theory; Signal and communications theory; Signal, noise; Telecommunications and information theory; Multiple access; Steepest descent method; Measurement sensor; Output signal; Computational complexity; Implementation; Convergence speed; Constant modulus algorithm; Signal interference; Inverse matrix; Simulation; Code division multiple access; Convergence rate; Signal processing; Robustness; Signal to interference plus noise ratio; Hessian matrices; Newton method; Direct sequence
• ISSN: 1751-9675; 1751-9683
• DOI: 10.1049/iet-spr.2011.0430

In this study, a robust sample-by-sample linearly constrained constant modulus algorithm (LCCMA) and a robust adaptive block-Shanno constant modulus algorithm (BSCMA) are developed. The well-established quadratic inequality constraint approach is exploited to add robustness to the developed algorithms. The LCCMA algorithm is implemented, using a fast steepest descent adaptive algorithm, whereas the BSCMA algorithm is realised, using a modified Newton's algorithm without the inverse of Hessian matrix estimation. The developed algorithms are exercised to cancel the multiple access interference in a loaded direct sequence code division multiple access (DS/CDMA) system. Simulations are presented in a rich multipath environment with a severe near-far effect to evaluate the robustness of the proposed DS/CDMA detectors. Finally, a comprehensive comparative analysis between the sample-by-sample and block-adaptive constant modulus-based detectors is presented. It has been demonstrated that, the developed robust BSCMA detector offers rapid convergence speed and very low computational complexity, whereas the developed robust LCCMA detector engenders about 5 dB improvement in the output signal-to-interference-plus-noise ratio over the BSCMA detector.