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Adaptive modulation and coding (AMC) is widely employed in modern wireless communication systems to improve the transmission efficiency by adjusting the transmission rate according to the channel conditions. Thus, AMC can provide very…

Signal Processing · Electrical Eng. & Systems 2017-12-21 Zhe Yang , Lin Cai , Aaron Gulliver , Liang He , Jianping Pan

We propose a novel scheme for rate-compatible arbitrary-length polar code construction for the additive white Gaussian noise (AWGN) channel. The proposed scheme is based on the concept of non-uniform channel polarization. The original polar…

Information Theory · Computer Science 2021-03-23 R. M. Oliveira , R. C. de Lamare

We optimize modulation formats for the additive white Gaussian noise channel with nonnegative input, also known as the intensity-modulated direct-detection channel, with and without confining them to a lattice structure. Our optimization…

Information Theory · Computer Science 2015-01-07 Johnny Karout , Erik Agrell , Krzysztof Szczerba , Magnus Karlsson

There is increasing realization in neuroscience that information is represented in the brain, e.g., neocortex, hippocampus, in the form sparse distributed codes (SDCs), a kind of cell assembly. Two essential questions are: a) how are such…

Machine Learning · Computer Science 2020-10-22 Rod Rinkus

Linear coding schemes have been the main choice of coding for the additive white Gaussian noise broadcast channel (AWGN-BC) with noiseless feedback in the literature. The achievable rate regions of these schemes go well beyond the capacity…

Information Theory · Computer Science 2016-11-15 Ziad Ahmad , Zachary Chance , David J. Love

This paper addresses the prediction of error floors of low-density parity-check (LDPC) codes with variable nodes of constant degree in the additive white Gaussian noise (AWGN) channel. Specifically, we focus on the performance of the…

Information Theory · Computer Science 2013-06-11 Brian K. Butler , Paul H. Siegel

Block encoding of sparse matrices underpins powerful quantum algorithms such as quantum singular value transformation, Hamiltonian simulation, and quantum linear solvers, yet its efficient gate-level realization for general sparse matrices…

Quantum Physics · Physics 2026-04-07 Abhishek Setty

Approximate Message Passing (AMP) is a general framework for iterative algorithms, originally developed for compressed sensing and later extended to a wide range of high-dimensional inference problems. Although recent work has advanced…

Signal Processing · Electrical Eng. & Systems 2026-04-24 Vishnu Teja Kunde , Alessandro Mirri , Jean-Francois Chamberland , Enrico Paolini

An energy-efficient approach is presented for shaping a bit-interleaved low-density parity-check (LDPC) coded amplitude phase-shift keying (APSK) system. A subset of the interleaved bits output by a binary LDPC encoder are passed through a…

Information Theory · Computer Science 2013-04-22 Matthew C. Valenti , Xingyu Xiang

The mutual information between a complex-valued channel input and its complex-valued output is decomposed into four parts based on polar coordinates: an amplitude term, a phase term, and two mixed terms. Numerical results for the additive…

Information Theory · Computer Science 2015-03-13 Bernhard Goebel , René-Jean Essiambre , Gerhard Kramer , Peter J. Winzer , Norbert Hanik

The generalized approximate message passing (GAMP) algorithm under the Bayesian setting shows advantage in recovering under-sampled sparse signals from corrupted observations. Compared to conventional convex optimization methods, it has a…

Information Theory · Computer Science 2017-01-12 Shuai Huang , Trac D. Tran

This paper proposes a coding framework for capacity-region-achieving sparse regression (SR) codes over MIMO multiple-access channels (MIMO-MAC), where a single SR code is used for each user at the transmitter. With random semi-unitary…

Information Theory · Computer Science 2026-04-14 Hao Yan , Lei Liu , Yuhao Liu , Burak Çakmak , Giuseppe Caire

In this paper we present an online wide-area oscillation damping control (WAC) design for uncertain models of power systems using ideas from reinforcement learning. We assume that the exact small-signal model of the power system at the…

Systems and Control · Computer Science 2018-10-02 Amirhassan Fallah Dizche , Aranya Chakrabortty , Alexandra Duel-Hallen

Approximate message passing (AMP) algorithms have shown great promise in sparse signal reconstruction due to their low computational requirements and fast convergence to an exact solution. Moreover, they provide a probabilistic framework…

Sound · Computer Science 2018-02-02 Turab Iqbal , Wenwu Wang

Pansharpening is a fundamental issue in remote sensing field. This paper proposes a side information partially guided convolutional sparse coding (SCSC) model for pansharpening. The key idea is to split the low resolution multispectral…

Computer Vision and Pattern Recognition · Computer Science 2021-03-11 Shuang Xu , Jiangshe Zhang , Kai Sun , Zixiang Zhao , Lu Huang , Junmin Liu , Chunxia Zhang

This paper addresses spatial programming of sparse matrix computations for productive performance. The challenge is how to express an irregular computation and its optimizations in a regular way. A sparse matrix has (non-zero) values and a…

Mathematical Software · Computer Science 2018-10-18 Hongbo Rong

In the evolving landscape of sixth-generation (6G) wireless networks, which demand ultra high data rates, this study introduces the concept of super constellation communications. Also, we present super amplitude phase shift keying (SAPSK),…

We study the theoretical performance of a combined approach to demodulation and decoding of binary continuous-phase modulated signals under repetition-like codes. This technique is motivated by a need to transmit packetized or framed data…

Information Theory · Computer Science 2014-04-28 Gaurav Thakur

State-of-the-art approaches toward image restoration can be classified into model-based and learning-based. The former - best represented by sparse coding techniques - strive to exploit intrinsic prior knowledge about the unknown…

Image and Video Processing · Electrical Eng. & Systems 2018-11-29 Fangfang Wu , Weisheng Dong , Guangming Shi , Xin Li

Sparse coding approximates the data sample as a sparse linear combination of some basic codewords and uses the sparse codes as new presentations. In this paper, we investigate learning discriminative sparse codes by sparse coding in a…

Machine Learning · Statistics 2015-01-19 Jim Jing-Yan Wang , Xin Gao