MAP Decoding of Correlated Sources

Download or read book MAP Decoding of Correlated Sources written by Seyed Parsa Beheshti and published by LAP Lambert Academic Publishing. This book was released on 2014-11-24 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: We consider the joint source-channel coding (JSCC) problem where the real valued outputs of two correlated memoryless Gaussian sources are scalar quantized, bit assigned, and transmitted, without applying any error correcting code, over a multiple access channel (MAC) which consists of two orthogonal point-to-point time-correlated Rayleigh fading sub-channels with soft-decision demodulation. At the receiver side, a joint sequence maximum a posteriori (MAP) detector is used to exploit the correlation between the two sources as well as the redundancy left in the quantizers' indices, the channel's soft-decision outputs, and noise memory. The MAC's sub-channels are modeled via non-binary Markov noise discrete channels recently shown to effectively represent point-to-point fading channels. Two scenarios are studied in this book. In the first scenario, the sources are memoryless and generated according to a bivariate Gaussian distribution with a given correlation parameter. In the second scenario, the sources have memory, captured by a changing correlation parameter which is governed by a two state first order Markov process.