A Belief Propagation Based Framework for Soft Multiple-Symbol Differential Detection

Soft noncoherent detection, which relies on calculating the \textit{a posteriori} probabilities (APPs) of the bits transmitted with no channel estimation, is imperative for achieving excellent detection performance in high-dimensional wireless communications. In this paper, a high-performance belief propagation (BP)-based soft multiple-symbol differential detection (MSDD) framework, dubbed BP-MSDD, is proposed with its illustrative application in differential space-time block-code (DSTBC)-aided ultra-wideband impulse radio (UWB-IR) systems. Firstly, we revisit the signal sampling with the aid of a trellis structure and decompose the trellis into multiple subtrellises. Furthermore, we derive an APP calculation algorithm, in which the forward-and-backward message passing mechanism of BP operates on the subtrellises. The proposed BP-MSDD is capable of significantly outperforming the conventional hard-decision MSDDs. However, the computational complexity of the BP-MSDD increases exponentially with the number of MSDD trellis states. To circumvent this excessive complexity for practical implementations, we reformulate the BP-MSDD, and additionally propose a Viterbi algorithm (VA)-based hard-decision MSDD (VA-HMSDD) and a VA-based soft-decision MSDD (VA-SMSDD). Moreover, both the proposed BP-MSDD and VA-SMSDD can be exploited in conjunction with soft channel decoding to obtain powerful iterative detection and decoding based receivers. Simulation results demonstrate the effectiveness of the proposed algorithms in DSTBC-aided UWB-IR systems.Comment: 14 pages, 12 figures, 3 tables, accepted to appear on IEEE Transactions on Wireless Communications, Aug. 201

The use of interleaving for reducing radio loss in convolutionally coded systems

The use of interleaving after convolutional coding and deinterleaving before Viterbi decoding is proposed. This effectively reduces radio loss at low-loop Signal to Noise Ratios (SNRs) by several decibels and at high-loop SNRs by a few tenths of a decibel. Performance of the coded system can further be enhanced if the modulation index is optimized for this system. This will correspond to a reduction of bit SNR at a certain bit error rate for the overall system. The introduction of interleaving/deinterleaving into communication systems designed for future deep space missions does not substantially complicate their hardware design or increase their system cost

A learning receiver for communication in three-component multipath channels

An adaptive receiver is designed for transmissions through a time-varying multipath channel which may include both specular and diffuse components. The design is based on the theory of unsupervised learning machines and the receiver is a recursive structure which does not grow in complexity with each new observation, but is Bayes\u27 optimal at each instant of time. The multipath medium is modelled as an aggregate of L conditionally independent transmission paths, each consisting of random and/or fixed reflections, and is identified in terms of three components: (1) indirect diffuse scatter, (2) indirect specular reflection, and (3) direct transmission. The channel parameters are time-varying and either independent from one signaling interval to the next or at most M-th order Markov dependent. A review of machines that learn without a teacher is presented and the learning receiver for three-component multipath is designed and modelled on the digital computer. A Monte Carlo simulation is used to estimate the performance when the channel is either Rician or nonfading. This performance, in terms of probability of error, is shown to be consistent with the existing coherent receivers and improves on their performance when the correlation between observations is increased --Abstract, page ii

A space communications study Final report, 15 Sep. 1966 - 15 Sep. 1967

Investigation of signal to noise ratios and signal transmission efficiency for space communication system