Title :
Multiuser Detection of Sparsely Spread CDMA
Author :
Guo, Dongning ; Wang, Chih-Chun
Author_Institution :
Northwestern Univ., Evanston
fDate :
4/1/2008 12:00:00 AM
Abstract :
Code-division multiple access (CDMA) is the basis of a family of advanced air interfaces in current and future generation networks. The benefits promised by CDMA have not been fully realized partly due to the prohibitive complexity of optimal detection and decoding of many users communicating simultaneously using the same frequency band. From both theoretical and practical perspectives, this paper advocates a new paradigm of CDMA with sparse spreading sequences, which enables near-optimal multiuser detection using belief propagation (BP) with low-complexity. The scheme is in part inspired by capacity-approaching low-density parity-check (LDPC) codes and the success of iterative decoding techniques. Specifically, it is shown that BP-based detection is optimal in the large-system limit under many practical circumstances, which is a unique advantage of sparsely spread CDMA systems. Moreover, it is shown that, from the viewpoint of an individual user, the CDMA channel is asymptotically equivalent to a scalar Gaussian channel with some degradation in the signal-to-noise ratio (SNR). The degradation factor, known as the multiuser efficiency, can be determined from a fixed-point equation. The results in this paper apply to a broad class of sparse, semi-regular CDMA systems with arbitrary input and power distribution. Numerical results support the theoretical findings for systems of moderate size, which further demonstrate the appeal of sparse spreading in practical applications.
Keywords :
Gaussian channels; code division multiple access; communication complexity; iterative decoding; multiuser detection; parity check codes; sparse matrices; CDMA channel; belief propagation; capacity-approaching low-density parity-check code; code-division multiple access; communication complexity; iterative decoding technique; near-optimal multiuser detection; scalar Gaussian channel; signal-to-noise ratio; sparse spreading matrix;
Journal_Title :
Selected Areas in Communications, IEEE Journal on
DOI :
10.1109/JSAC.2008.080402