MAP decoding of quantized sources over soft-decision fading channels with memory

We study a joint source-channel decoding scheme that exploits the channel's statistical memory and soft-decision information in fading channels. The channel considered is a recently introduced binary input 2q-ary output channel with Markovian ergodic noise based on a finite queue (called NBNDC-QB). This model has been shown to effectively represent soft-decision demodulated correlated Rayleigh fading channels. The coding scheme consists of a scalar quantizer, a proper index assignment, and a sequence maximum a posteriori (MAP) decoder designed to harness the redundancy left in the quantizer's indices, the channel's soft-decision output, and correlation in the channel noise process. We first consider the simple case where the quantized indices form a binary symmetric Markov source and establish a necessary and sufficient condition under which the sequence MAP decoder is reduced to a simple instantaneous symbol-by-symbol decoder. We next assess the signal-to-distortion ratio (SDR) performance of our general system. Our numerical results confirm that this system can successfully take advantage of the channel memory and outperforms systems that use channel interleaving by as much as 2.6 dB in SDR. In addition, SDR gains of up to 2.8 dB are achieved using as few as 2 bits for soft-decision quantization over hard quantized output schemes. Finally, the NBNDC-QB channel model is validated in terms of SDR performance by fitting the NBNDC-QB model to a discrete correlated Rayleigh fading channel, designing a system for this matched NBNDC-QB model, and comparing this system's performance over both the NBNDC-QB and the Rayleigh fading channels.

[1]  Fady Alajaji,et al.  Detection of binary Markov sources over channels with additive Markov noise , 1996, IEEE Trans. Inf. Theory.

[2]  David J. Miller,et al.  A sequence-based approximate MMSE decoder for source coding over noisy channels using discrete hidden Markov models , 1998, IEEE Trans. Commun..

[3]  Fady Alajaji,et al.  Soft-decision demodulation design for COVQ over white, colored, and ISI Gaussian channels , 2000, IEEE Trans. Commun..

[4]  Fady Alajaji,et al.  A Discrete Channel Model for Capturing Memory and Soft-Decision Information: A Capacity Study , 2009, 2009 IEEE International Conference on Communications.

[5]  F. Behnamfar,et al.  Channel-Optimized Quantization With Soft-Decision Demodulation for Space–Time Orthogonal Block-Coded Channels , 2006, IEEE Transactions on Signal Processing.

[6]  Fady Alajaji,et al.  A Binary Communication Channel With Memory Based on a Finite Queue , 2007, IEEE Transactions on Information Theory.

[7]  Robert M. Gray,et al.  The design of joint source and channel trellis waveform coders , 1987, IEEE Trans. Inf. Theory.

[8]  Robert M. Gray,et al.  An Algorithm for Vector Quantizer Design , 1980, IEEE Trans. Commun..

[9]  Fady Alajaji,et al.  Quantization of memoryless and Gauss-Markov sources over binary Markov channels , 1997, IEEE Trans. Commun..

[10]  Masao Kasahara,et al.  A construction of vector quantizers for noisy channels , 1984 .

[11]  Upamanyu Madhow,et al.  On the limits of communication with low-precision analog-to-digital conversion at the receiver , 2009, IEEE Transactions on Communications.

[12]  R. Clarke.  A statistical theory of mobile-radio reception , 1968 .

[13]  Yahong Rosa Zheng,et al.  Improved models for the generation of multiple uncorrelated Rayleigh fading waveforms , 2002, IEEE Communications Letters.

[14]  Fady Alajaji,et al.  A Discrete Queue-Based Model for Soft-Decision Demodulated Correlated Fading Channels , 2011, 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring).

[15]  Mikael Skoglund,et al.  On source decoding based on finite-bandwidth soft information , 2005, Proceedings. International Symposium on Information Theory, 2005. ISIT 2005..

[16]  Aaron D. Wyner,et al.  Coding Theorems for a Discrete Source With a Fidelity CriterionInstitute of Radio Engineers, International Convention Record, vol. 7, 1959. , 1993 .

[17]  Mikael Skoglund,et al.  Soft Decoding for Vector Quantization Over Noisy Channels with Memory , 1999, IEEE Trans. Inf. Theory.

[18]  S. P. Lloyd,et al.  Least squares quantization in PCM , 1982, IEEE Trans. Inf. Theory.