Improved Modeling of the Correlation Between Continuous-Valued Sources in LDPC-Based DSC

Accurate modeling of the correlation between the sources plays a crucial role in the efficiency of distributed source coding (DSC) systems. This correlation is commonly modeled in the binary domain by using a single binary symmetric channel (BSC), both for binary and continuous-valued sources. We show that "one" BSC cannot accurately capture the correlation between continuous-valued sources; a more accurate model requires "multiple" BSCs, as many as the number of bits used to represent each sample. We incorporate this new model into the DSC system that uses low-density parity-check (LDPC) codes for compression. The standard Slepian-Wolf LDPC decoder requires a slight modification so that the parameters of all BSCs are integrated in the log-likelihood ratios (LLRs). Further, using an interleaver the data belonging to different bit-planes are shuffled to introduce randomness in the binary domain. The new system has the same complexity and delay as the standard one. Simulation results prove the effectiveness of the proposed model and system.Comment: 5 Pages, 4 figures; presented at the Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, November 201

Analysis of the Convergence Process by EXIT Charts for Parallel Implementations of Turbo Decoders

International audienceIterative process is a general principle in decoding powerful FEC codes such as turbo codes. However, the mutual information exchange during the iterative process is not easy to analyze and to describe. A useful technique to help the designer is the EXtrinsic Information Transfer (EXIT) chart. Unfortunately, this method cannot be directly applied to the decoding convergence analysis if parallel processing has to be exploited for the design of turbo decoders. In this letter, an extension of the EXIT charts method is proposed in order to take into account the constraints introduced by parallel implementations. The corresponding analysis associated with Monte-Carlo simulations gives additional understanding of the convergence process for the design of parallel architectures dedicated to turbo decoding

A shuffled iterative bit-interleaved coded modulation receiver for the DVB-T2 standard: Design, implementation and FPGA prototyping

International audienceRotated QAM constellations improve Bit-Interleaved Coded Modulation (BICM) performance over fading channels. Indeed, an increased diversity is obtained by coupling a constellation rotation with interleaving between the real and imaginary components of transmitted symbols either in time or frequency domain. Iterative processing at the receiver side can provide additional improvement in performance. In this paper, an efficient shuffled iterative receiver is investigated for the second generation of the terrestrial digital video broadcasting standard DVB-T2. Scheduling an efficient message passing algorithm with low latency between the demapper and the LDPC decoder represents the main contribution. The design and the FPGA prototyping of the resultant shuffled iterative BICM receiver are then described. Architecture complexity and measured performance validate the potential of iterative receiver as a practical and competitive solution for the DVB-T2 standard

Uncovering temporal structure in hippocampal output patterns.

Place cell activity of hippocampal pyramidal cells has been described as the cognitive substrate of spatial memory. Replay is observed during hippocampal sharp-wave-ripple-associated population burst events (PBEs) and is critical for consolidation and recall-guided behaviors. PBE activity has historically been analyzed as a phenomenon subordinate to the place code. Here, we use hidden Markov models to study PBEs observed in rats during exploration of both linear mazes and open fields. We demonstrate that estimated models are consistent with a spatial map of the environment, and can even decode animals' positions during behavior. Moreover, we demonstrate the model can be used to identify hippocampal replay without recourse to the place code, using only PBE model congruence. These results suggest that downstream regions may rely on PBEs to provide a substrate for memory. Additionally, by forming models independent of animal behavior, we lay the groundwork for studies of non-spatial memory

Belief Propagation Decoding of Polar Codes on Permuted Factor Graphs

We show that the performance of iterative belief propagation (BP) decoding of polar codes can be enhanced by decoding over different carefully chosen factor graph realizations. With a genie-aided stopping condition, it can achieve the successive cancellation list (SCL) decoding performance which has already been shown to achieve the maximum likelihood (ML) bound provided that the list size is sufficiently large. The proposed decoder is based on different realizations of the polar code factor graph with randomly permuted stages during decoding. Additionally, a different way of visualizing the polar code factor graph is presented, facilitating the analysis of the underlying factor graph and the comparison of different graph permutations. In our proposed decoder, a high rate Cyclic Redundancy Check (CRC) code is concatenated with a polar code and used as an iteration stopping criterion (i.e., genie) to even outperform the SCL decoder of the plain polar code (without the CRC-aid). Although our permuted factor graph-based decoder does not outperform the SCL-CRC decoder, it achieves, to the best of our knowledge, the best performance of all iterative polar decoders presented thus far.Comment: in IEEE Wireless Commun. and Networking Conf. (WCNC), April 201