MAP Decoding of Correlated Sources over Soft-Decision Orthogonal Multiple Access Fading Channels with Memory

Abstract

Abstract-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 subchannels 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 quantizer's indices, the channel's softdecision 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. For the simple case of quantizing the sources with two levels, we establish a necessary and sufficient condition under which the joint sequence MAP decoder can be reduced to a simple instantaneous symbol-by-symbol decoder. Then, using numerical results obtained by system simulation, it is observed that when the sources are highly correlated and soft-decision quantization is used, JSCC can profit from a high correlation in the channel noise process and provide significant signal-to-distortion ratio improvements of up to 6.3 dB over a fully interleaved channel.

Scalar Quantizer Design for Two-Way Channels

“…In the multi-user setup, the authors in [19] used multi-resolution quantization and layered JSCC to serve simultaneously several users over the binary erasure broadcast channel. Also, in [20], the proposed single-user JSCC scheme of [21] was adopted for the transmission of two correlated sources over an orthogonal multiple-access channel. In this paper, we propose a COSQ design for the effective transmission of generally correlated sources over discrete memoryless two-way channels.…”