Browsing International Telemetering Conference Proceedings, Volume 49 (2013) by Authors
combined Modulation and Error Correction Decoder for TDMR Using Generalized Belief PropagationVasić, Bane; Khatami, Mehrdad; University of Arizona (International Foundation for Telemetering, 2013-10)Constrained codes also known as modulation codes are a key component in the digital magnetic recording systems. The constrained codes forbid particular input data patterns which lead to some of the dominant error events or higher media noise. In data recording systems, a concatenated approach toward the constrained code and error-correcting code (ECC) is typically used and the decoding is done independently. In this paper, we show the improvement in combining the decoding of the constrained code and the ECC using generalized belief propagation (GBP) algorithm. We consider the performance of a combined modulation constraints and the ECC on a binary symmetric channel (BSC). We show that combining demodulation and decoding results in a superior performance compared to concatenated schemes. Furthermore, we compute the capacity of the joint ECC and modulation codes for 1-D and 2-D constraints.
Low-Complexity Iterative Reconstruction Algorithms in Compressed SensingVasić, Bane; Marcellin, Michael W.; Declercq, David; Danjean, Ludovic; University of Arizona (International Foundation for Telemetering, 2013-10)In this paper we focus on two low-complexity iterative reconstruction algorithms in compressed sensing. These algorithms, called the approximate message-passing algorithm and the interval-passing algorithm, are suitable to recover sparse signals from a small set of measurements. Depending on the type of measurement matrix (sparse or random) used to acquire the samples of the signal, one or the other reconstruction algorithm can be used. We present the reconstruction results of these two reconstruction algorithms in terms of proportion of correct reconstructions in the noise free case. We also report in this paper possible practical applications of compressed sensing where the choice of the measurement matrix and the reconstruction algorithm are often governed by the constraint of the considered application.