Title :
Innovative parallel equalizer design for continuous phase modulation systems
Author :
Shih Yu Chang ; Hsiao-Chun Wu
Author_Institution :
Dept. of Comput. Sci., Nat. Tsing Hua Univ., Hsinchu, Taiwan
Abstract :
In this paper, we propose a new parallel structure of the linear frequency-domain equalization approach for continuous phase modulated (CPM) signals. Since CPM is a nonlinear modulation technique, the corresponding equalizer design is mathematically intractable. However, it is possible to decompose any CPM signal into a sum of linearly modulated signals through Laurent decomposition. By utilizing Laurent decomposition, the nonlinear nature of CPM is manifested by the mapping of the input symbols onto the “pseudo-coefficients”. This enables us to establish a time-domain polyphase matrix signal model, which can characterize various block-based CPM systems. Such a polyphase matrix model can yield a linear equalizer as its matrix inverse. Moreover, we propose a matrix inverse approximation algorithm to design the equalizers for CPM systems in a parallel paradigm. The algorithmic complexity for the optimal equalizer design is thus significantly reduced. Monte Carlo simulations are taken in compliance with the wireless personal-area network (WPAN) standard. Two primary equalizers, namely minimum-mean-square-error (MMSE) and zero-forcing (ZF) equalizers, are adopted therein. Simulation results demonstrate that our proposed new parallel MMSE/ZF equalizer would lead to a slightly worse bit-error-rate performance than the conventional MMSE/ZF equalizer. Nevertheless, the former scheme would reduce a lot of computational complexity compared to the latter method.
Keywords :
Monte Carlo methods; channel estimation; computational complexity; equalisers; error statistics; least mean squares methods; matrix inversion; phase modulation; Laurent decomposition; MMSE; Monte Carlo simulations; bit error rate performance; computational complexity; continuous phase modulation systems; innovative parallel equalizer design; linear frequency domain equalization approach; linearly modulated signals; matrix inverse approximation algorithm; minimum mean square error; nonlinear modulation technique; time domain polyphase matrix signal model; wireless personal area network standard; zero forcing equalizers; Approximation methods; Computational complexity; Equalizers; Frequency-domain analysis; Matrices; Program processors; Sparse matrices; Continuous phase modulation (CPM); complexity reduction; minimum mean-square-error (MMSE) equalization; polyphase representation; zero-forcing (ZF) equalization;
Conference_Titel :
Communications (ICC), 2014 IEEE International Conference on
Conference_Location :
Sydney, NSW
DOI :
10.1109/ICC.2014.6884008