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In this paper, we introduce the concept of spatially coupled turbo-like codes (SC-TCs) as the spatial coupling of a number of turbo-like code ensembles. In particular, we consider the spatial coupling of Berrou et al. parallel concatenated…

Information Theory · Computer Science 2017-10-03 Saeedeh Moloudi , Michael Lentmaier , Alexandre Graell i Amat

In this paper, we study the density evolution analysis of spatially coupled low-density parity-check (SC-LDPC) codes over binary input additive white Gaussian noise (BIAWGN) channels under the belief propagation (BP) decoding algorithm.…

Information Theory · Computer Science 2015-10-19 Md. Noor-A-Rahim , Gottfried Lechner , Khoa D. Nguyen

An ensemble of LDPC convolutional codes with parity-check matrices composed of permutation matrices is considered. The convergence of the iterative belief propagation based decoder for terminated convolutional codes in the ensemble is…

Information Theory · Computer Science 2016-11-17 Michael Lentmaier , Arvind Sridharan , Kamil Sh. Zigangirov , Daniel J. Costello

Parallel, additive white Gaussian noise (AWGN) channels with an average sum power constraint are considered. It is shown how the waterfilling Shannon capacity can be approached by higher order modulation and probabilistic amplitude shaping…

Information Theory · Computer Science 2018-04-06 Fabian Steiner , Georg Böcherer , Patrick Schulte

We consider a peak-power-limited single-antenna block-stationary Gaussian fading channel where neither the transmitter nor the receiver knows the channel state information, but both know the channel statistics. This model subsumes most…

Information Theory · Computer Science 2016-11-17 Jun Chen , Venugopal V. Veeravalli

Motivated by a wide-spread use of convex optimization techniques, convexity properties of bit error rate of the maximum likelihood detector operating in the AWGN channel are studied for arbitrary constellations and bit mappings, which also…

Information Theory · Computer Science 2010-04-16 Sergey Loyka , Francois Gagnon , Victoria Kostina

The capacity of a complex and discrete-time memoryless additive white Gaussian noise (AWGN) channel under three constraints, namely, input average power, input amplitude and output delivered power is studied. The output delivered power…

Information Theory · Computer Science 2020-04-27 Morteza Varasteh , Borzoo Rassouli , Bruno Clerckx

This paper studies a large random matrix system (LRMS) model involving an arbitrary signal distribution and forward error control (FEC) coding. We establish an area property based on the approximate message passing (AMP) algorithm. Under…

Information Theory · Computer Science 2021-06-07 Lei Liu , Chulong Liang , Junjie Ma , Li Ping

We consider a broadcast scenario where one transmitter communicates with two receivers under quality-of-service constraints. The transmitter initially employs superposition coding strategies with arbitrarily distributed signals and sends…

Information Theory · Computer Science 2016-03-09 Marwan Hammouda , Sami Akin , Jürgen Peissig

In a recent paper, the authors proposed a new class of low-complexity iterative thresholding algorithms for reconstructing sparse signals from a small set of linear measurements \cite{DMM}. The new algorithms are broadly referred to as AMP,…

Information Theory · Computer Science 2009-11-24 David L. Donoho , Arian Maleki , Andrea Montanari

Random linear network coding (RLNC) in theory achieves the max-flow capacity of multicast networks, at the cost of high decoding complexity. To improve the performance-complexity tradeoff, we consider the design of sparse network codes. A…

Information Theory · Computer Science 2016-04-20 Ye Li , Wai-Yip Chan , Steven D. Blostein

The minimum energy, and, more generally, the minimum cost, to transmit one bit of information has been recently derived for bursty communication when information is available infrequently at random times at the transmitter. Furthermore, it…

Information Theory · Computer Science 2017-10-25 Venkat Chandar , Aslan Tchamkerten

We investigate robust linear consensus over networks under capacity-constrained communication. The capacity of each edge is encoded as an upper bound on the number of state variables that can be communicated instantaneously. When the edge…

Systems and Control · Electrical Eng. & Systems 2021-05-25 Yasin Yazicioglu , Alberto Speranzon

We derive a lower bound on the secrecy capacity of the compound wiretap channel with channel state information at the transmitter which matches the general upper bound on the secrecy capacity of general compound wiretap channels given by…

Information Theory · Computer Science 2016-11-17 Igor Bjelakovic , Holger Boche , Jochen Sommerfeld

For a continuous-time additive white Gaussian noise (AWGN) channel with possible feedback, it has been shown that as sampling gets infinitesimally fine, the mutual information of the associative discrete-time channels converges to that of…

Information Theory · Computer Science 2020-08-26 Guangyue Han , Shlomo Shamai

The performance of Gallager's error-correcting code is investigated via methods of statistical physics. In this approach, the transmitted codeword comprises products of the original message bits selected by two randomly-constructed sparse…

Disordered Systems and Neural Networks · Physics 2009-10-31 Yoshiyuki Kabashima , Tatsuto Murayama , David Saad

Basing on recently developed convex programming framework in the paper [arXiv:2204.10626], we provide a proof for a long-standing conjecture on optimality of Gaussian encondings for the ultimate communication rate of generalized heterodyne…

Quantum Physics · Physics 2023-07-25 A. S. Holevo , S. N. Filippov

We revisit the error correction scheme of real-valued signals when the codeword is corrupted by gross errors on a fraction of entries and a small noise on all the entries. Combining the recent developments of approximate message passing and…

Information Theory · Computer Science 2014-02-04 Jean Barbier , Florent Krzakala , Lenka Zdeborová , Pan Zhang

A simple model to study subspace clustering is the high-dimensional $k$-Gaussian mixture model where the cluster means are sparse vectors. Here we provide an exact asymptotic characterization of the statistically optimal reconstruction…

Machine Learning · Statistics 2023-04-04 Luca Pesce , Bruno Loureiro , Florent Krzakala , Lenka Zdeborová

Considering a short frame length, which is typical in Ultra-Reliable Low-Latency and massive Machine Type Communications, a trade-off exists between improving the performance of frame synchronization (FS) and improving the performance of…

Information Theory · Computer Science 2019-03-12 Alex The Phuong Nguyen , Raphaël Le Bidan , Frédéric Guilloud
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