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We investigate power allocation for the base matrix of a spatially coupled sparse regression code (SC-SPARC) for reliable communications over an additive white Gaussian noise channel. A conventional SC-SPARC allocates power uniformly to the…

Information Theory · Computer Science 2023-05-16 Nian Guo , Shansuo Liang , Wei Han

In the decades following Shannon's work, the quest to design codes for the additive white Gaussian noise (AWGN) channel led to the development of a rich theory, revealing a number of beautiful connections between information theory and…

Information Theory · Computer Science 2017-12-21 Laura Luzzi , Roope Vehkalahti

Low-rate and short-packet transmissions are important for ultra-reliable low-latency communications (URLLC). In this paper, we put forth a new family of sparse superposition codes for URLLC, called block orthogonal sparse superposition…

Information Theory · Computer Science 2022-08-16 Donghwa Han , Jeonghun Park , Youngjoo Lee , H. Vincent Poor , Namyoon Lee

Recent advances in deep learning for wireless communications have renewed interest in channel output feedback codes. In the additive white Gaussian broadcast channel with feedback (AWGN-BC-F), feedback can expand the channel capacity region…

Signal Processing · Electrical Eng. & Systems 2025-12-02 Jacqueline Malayter , Yingyao Zhou , Natasha Devroye , Chih-Chun Wang , Christopher Brinton , David J. Love

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

In this paper, we leverage polar codes and the well-established channel polarization to design capacity-achieving codes with a certain constraint on the weights of all the columns in the generator matrix (GM) while having a low-complexity…

Information Theory · Computer Science 2023-03-17 James Chin-Jen Pang , Hessam Mahdavifar , S. Sandeep Pradhan

3D Language Gaussian Splatting (3DLGS) augments 3D Gaussian Splatting with language-aligned visual features for open-vocabulary 3D scene understanding. A core challenge is efficiently associating high-dimensional vision-language embeddings…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Lovre Antonio Budimir , Yushi Guan , Steve Ryhner , Sven Lončarić , Nandita Vijaykumar

Spinal codes, a family of rateless codes introduced in 2011, have been proved to achieve Shannon capacity over both the additive white Gaussian noise (AWGN) channel and the binary symmetric channel (BSC). In this paper, we derive explicit…

Information Theory · Computer Science 2023-04-28 Xiaomeng Chen , Aimin Li , Shaohua Wu

In this paper, we construct protograph-based spatially coupled low-density parity-check (SC-LDPC) codes by coupling together a series of L disjoint, or uncoupled, LDPC code Tanner graphs into a single coupled chain. By varying L, we obtain…

Information Theory · Computer Science 2016-11-17 David G. M. Mitchell , Michael Lentmaier , Daniel J. Costello

Novel sparse regression LDPC (SR-LDPC) codes exhibit excellent performance over additive white Gaussian noise (AWGN) channels in part due to their natural provision of shaping gains. Though SR-LDPC-like codes have been considered within the…

Information Theory · Computer Science 2024-02-13 Jamison R. Ebert , Jean-Francois Chamberland , Krishna R. Narayanan

We consider spatially coupled low-density parity-check codes with finite smoothing parameters. A finite smoothing parameter is important for designing practical codes that are decoded using low-complexity windowed decoders. By optimizing…

Information Theory · Computer Science 2019-07-09 Laurent Schmalen , Vahid Aref

Next-generation wireless communication systems impose much stricter requirements for transmission rate, latency, and reliability. The peak data rate of 6G networks should be no less than 1 Tb/s, which is comparable to existing long-haul…

Information Theory · Computer Science 2024-10-28 Kirill Andreev , Pavel Rybin , Alexey Frolov

Recently, it was found that clipping can significantly improve the section error rate (SER) performance of sparse regression (SR) codes if an optimal clipping threshold is chosen. In this paper, we propose irregularly clipped SR codes,…

Information Theory · Computer Science 2021-06-04 Wencong Li , Lei Liu , Brian M. Kurkoski

Sparse fusion is a compile-time loop transformation and runtime scheduling implemented as a domain-specific code generator. Sparse fusion generates efficient parallel code for the combination of two sparse matrix kernels where at least one…

Programming Languages · Computer Science 2021-11-25 Kazem Cheshmi , Michelle Mills Strout , Maryam Mehri Dehnavi

In this paper, we propose a new approach to proving results regarding channel coding schemes based on construction-A lattices for the Additive White Gaussian Noise (AWGN) channel that yields new characterizations of the code construction…

Information Theory · Computer Science 2016-11-18 Wael Alghamdi , Walid Abediseid , Mohamed-Slim Alouini

Spatially coupled, parallel concatenated codes (SC-PCCs) have been shown to approach channel capacity when decoded using optimal iterative methods. However, under complexity constraints such decoding strategies can result in unacceptable…

Information Theory · Computer Science 2021-09-07 Andrew D. Cummins , David G. M. Mitchell , Daniel J. Costello,

Convolutional sparse coding (CSC) can learn representative shift-invariant patterns from multiple kinds of data. However, existing CSC methods can only model noises from Gaussian distribution, which is restrictive and unrealistic. In this…

Machine Learning · Computer Science 2020-04-22 Yaqing Wang , James T. Kwok , Lionel M. Ni

Spatially coupled codes have been of interest recently owing to their superior performance over memoryless binary-input channels. The performance is good both asymptotically, since the belief propagation thresholds approach capacity, as…

Information Theory · Computer Science 2012-12-03 Aravind R. Iyengar , Paul H. Siegel , Rudiger L. Urbanke , Jack K. Wolf

Sparse coding is a basic task in many fields including signal processing, neuroscience and machine learning where the goal is to learn a basis that enables a sparse representation of a given set of data, if one exists. Its standard…

Machine Learning · Computer Science 2015-03-04 Sanjeev Arora , Rong Ge , Tengyu Ma , Ankur Moitra

In this paper, we propose the explicit construction of a new class of lattices based on polar codes, which are provably good for the additive white Gaussian noise (AWGN) channel. We follow the multilevel construction of Forney \textit{et…

Information Theory · Computer Science 2013-07-05 Yanfei Yan , Cong Ling , Xiaofu Wu
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