On joint source-channel decoding and interference cancellation in CDMA-based large-scale wireless sensor networks
Motivated by potential applications in wireless sensor networks, this thesis considers the problem of communicating a large number of correlated analog sources over a Gaussian multiple-access channel using non-orthogonal code-division multiple-access (CDMA). A joint source-channel decoder is presented which can exploit the inter-source correlation for interference reduction in the CDMA channel. This decoder uses a linear minimum mean square error (MMSE) multi-user detector (MUD) in tandem with a MMSE joint source decoder (JSD) for multiple sources to achieve a computational complexity that scales with the number of sources. The MUD and the JSD, then iteratively exchange extrinsic information to improve the interference cancellation. Experimental results show that, compared to a non-iterative decoder, the proposed iterative decoder is more robust against potential performance degradation due to correlated channel interference and offers better near far resistance.
Multi-user source coding, joint source-channel decoding, iterative decoding, CDMA, multi-user detection
C. Illangakoon and P. Yahampath, “On joint source-channel decoding and interference cancellation in CDMA-based large-scale wireless sensor networks,” IEEE International Conference on Acoustics, Speech and Signal Processing, 2013. ICASSP 2013.