Title :
Simple iterative methods to exploit the signal-space diversity
Author :
Li, Yabo ; Xia, Xiang-Gen ; Wang, Genyuan
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Delaware, Newark, DE, USA
Abstract :
Signal-space diversity is a power- and bandwidth-efficient diversity technique. To exploit the signal-space diversity, joint maximum-likelihood (ML) detection at the receiver is usually needed, where the complexity grows exponentially with the dimension of the lattice. In this letter, we propose a serial concatenated scheme and two simple iterative methods to exploit the signal-space diversity. The simple iterative methods are based on the idea of soft interference cancellation. The first iterative method is based on a vector Gaussian approximation, while the second one is based on a scalar Gaussian approximation. The complexity of the first iterative method grows cubically with the dimension of the lattice, and the simulations show that its performance approaches that of the optimal maximum a posteriori detection method. The complexity of the second iterative method grows linearly with the dimension of the lattice, and the simulations show that when the dimension of the lattice N=32, at bit-error rate =10-5, the performance gap between the Rayleigh fading channel and the Gaussian channel is only 0.3 dB.
Keywords :
Gaussian channels; Rayleigh channels; computational complexity; diversity reception; error statistics; interference suppression; iterative methods; maximum likelihood detection; Gaussian channel; Rayleigh fading channel; bandwidth-efficient diversity technique; bit-error rate; iterative method; joint maximum-likelihood detection; optimal maximum a posteriori detection method; power-efficient diversity technique; scalar Gaussian approximation; serial concatenated scheme; signal-space diversity; soft interference cancellation; vector Gaussian approximation; AWGN; Fading; Frequency diversity; Gaussian approximation; Interference cancellation; Iterative decoding; Iterative methods; Lattices; Maximum likelihood decoding; Maximum likelihood detection;
Journal_Title :
Communications, IEEE Transactions on
DOI :
10.1109/TCOMM.2004.840665