Monte Carlo Bayesian Signal Processing for Wireless Communications
Journal of VLSI Signal Processing Systems
On sequential Monte Carlo sampling methods for Bayesian filtering
Statistics and Computing
Wireless Image Transmission Using Multiple-Description Based Concatenated Codes
DCC '00 Proceedings of the Conference on Data Compression
A sequential Monte Carlo blind receiver for OFDM systems infrequency-selective fading channels
IEEE Transactions on Signal Processing
Mismatched decoding of intersymbol interference using a parallel concatenated scheme
IEEE Journal on Selected Areas in Communications
Information fusion for wireless sensor networks: Methods, models, and classifications
ACM Computing Surveys (CSUR)
IKNOS: inference and knowledge in networks of sensors
International Journal of Sensor Networks
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We consider the problem of transmitting a continuous source through an OFDM system. Multiple description scalar quantization (MDSQ) is applied to the source signal, resulting in two correlated source descriptions. The two descriptions are then OFDM modulated and transmitted through two parallel frequency-selective fading channels. At the receiver, a blind turbo receiver is developed for joint OFDM demodulation and MDSQ decoding. Transformation of the extrinsic information of the two descriptions are exchanged between each other to improve system performance. A blind soft-input soft-output OFDM detector is developed, which is based on the techniques of importance sampling and resampling. Such a detector is capable of exchanging the so-called extrinsic information with the other component in the above turbo receiver, and successively improving the overall receiver performance. Finally, we also treat channel-coded systems, and a novel blind turbo receiver is developed for joint demodulation, channel decoding, and MDSQ source decoding.