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In this paper, we propose a new polar coding scheme for the unsourced, uncoordinated Gaussian random access channel. Our scheme is based on sparse spreading, treat interference as noise and successive interference cancellation (SIC). On the…

Information Theory · Computer Science 2020-07-14 Mengfan Zheng , Yongpeng Wu , Wenjun Zhang

In this paper, we study a concatenate coding scheme based on sparse regression code (SPARC) and tree code for unsourced random access in massive multiple-input and multiple-output systems. Our focus is concentrated on efficient decoding for…

Information Theory · Computer Science 2022-08-15 Juntao You , Wenjie Wang , Shansuo Liang , Wei Han , Bo Bai

We study sparse regression codes (SPARC) for multiple access channels with multiple receive antennas, in non-coherent flat fading channels. We propose a novel practical decoder, referred to as maximum likelihood matching pursuit (MLMP),…

Signal Processing · Electrical Eng. & Systems 2025-07-16 V S V Sandeep , Sai Dinesh Kancharana , Arun Pachai Kannu

Unsourced random-access (U-RA) is a type of grant-free random access with a virtually unlimited number of users, of which only a certain number $K_a$ are active on the same time slot. Users employ exactly the same codebook, and the task of…

Information Theory · Computer Science 2021-01-11 Alexander Fengler , Peter Jung , Giuseppe Caire

Unsourced random access is a novel communication paradigm designed for handling a large number of uncoordinated users that sporadically transmit very short messages. Under this model, coded compressed sensing (CCS) has emerged as a…

Information Theory · Computer Science 2021-07-22 Jamison R. Ebert , Vamsi K. Amalladinne , Stefano Rini , Jean-Francois Chamberland , Krishna R. Narayanan

Unsourced random-access (U-RA) is a type of grant-free random access with a virtually unlimited number of users, of which only a certain number $K_a$ are active on the same time slot. Users employ exactly the same codebook, and the task of…

Information Theory · Computer Science 2021-12-10 Alexander Fengler , Peter Jung , Giuseppe Caire

A joint sparse-regression-code (SPARC) and low-density-parity-check (LDPC) coding scheme for multiple-input multiple-output (MIMO) massive unsourced random access (URA) is proposed in this paper. Different from the state-of-the-art…

Information Theory · Computer Science 2022-01-12 Tianya Li , Yongpeng Wu , Mengfan Zheng , Dongming Wang , Wenjun Zhang

In this letter, we extend the sparse Kronecker-product (SKP) coding scheme, originally designed for the additive white Gaussian noise (AWGN) channel, to multiple input multiple output (MIMO) unsourced random access (URA). With the SKP…

Signal Processing · Electrical Eng. & Systems 2022-08-16 Zeyu Han , Xiaojun Yuan , Chongbin Xu , Xin Wang

This article presents a novel transmission scheme for the unsourced, uncoordinated Gaussian multiple access problem. The proposed scheme leverages notions from single-user coding, random spreading, minimum-mean squared error (MMSE)…

Information Theory · Computer Science 2019-11-05 Asit Kumar Pradhan , Vamsi K. Amalladinne , Krishna R. Narayanan , Jean-Francois Chamberland

Sparse superimposed coding (SSC) has emerged as a promising technique for short-packet transmission in ultra-reliable low-latency communication scenarios. However, conventional SSC schemes often suffer from high encoding and decoding…

Signal Processing · Electrical Eng. & Systems 2026-01-23 Yanfeng Zhang , Xi'an Fan , Xu Zhu , Jinkai Zheng , Hui Liang , Weiwei Yang , Tom H. Luan

We consider sparse superposition codes (SPARCs) over complex AWGN channels. Such codes can be efficiently decoded by an approximate message passing (AMP) decoder, whose performance can be predicted via so-called state evolution in the…

Information Theory · Computer Science 2021-03-09 Haiwen Cao , Pascal O. Vontobel

Sparse Code Multiple Access (SCMA) is an enabling code-domain non-orthogonal multiple access (NOMA)scheme for massive connectivity and ultra low-latency in future machine-type communication networks. As an evolved variant of code division…

Information Theory · Computer Science 2021-05-17 Saumya Chaturvedi , Zilong Liu , Vivek Ashok Bohara , Anand Srivastava , Pei Xiao

This article presents a novel enhancement to the random spreading based coding scheme developed by Pradhan et al.\ for the unsourced multiple access channel. The original coding scheme features a polar outer code in conjunction with a…

Information Theory · Computer Science 2021-05-31 Asit Kumar Pradhan , Vamsi K. Amalladinne , Krishna R. Narayanan , Jean-Francois Chamberland

Product codes (PCs) protect a two-dimensional array of bits using short component codes. Assuming transmission over the binary symmetric channel, the decoding is commonly performed by iteratively applying bounded-distance decoding to the…

Information Theory · Computer Science 2017-11-22 Christian Häger , Henry D. Pfister

Sparse regression codes (SPARCs) are a class of codes that encode information through the superposition of columns of a randomised coding matrix. The combination with an outer non-binary low density parity check (NB-LDPC) code was recently…

Information Theory · Computer Science 2025-09-23 Alexander Fengler , Burak Çakmak , Giuseppe Caire

This article introduces a novel communication scheme, termed coded compressed sensing, for unsourced multiple-access communication. The proposed divide-and-conquer approach leverages recent advances in compressed sensing and forward error…

Signal Processing · Electrical Eng. & Systems 2019-06-26 Vamsi K. Amalladinne , Jean-Francois Chamberland , Krishna R. Narayanan

Sparse Code Multiple Access (SCMA) is a disruptive code-domain non-orthogonal multiple access (NOMA) scheme to enable \color{black}future massive machine-type communication networks. As an evolved variant of code division multiple access…

Signal Processing · Electrical Eng. & Systems 2022-05-17 Saumya Chaturvedi , Zilong Liu , Vivek Ashok Bohara , Anand Srivastava , Pei Xiao

This article introduces a novel paradigm for the unsourced multiple-access communication problem. This divide-and-conquer approach leverages recent advances in compressive sensing and forward error correction to produce a computationally…

Information Theory · Computer Science 2018-06-04 Vamsi K. Amalladinne , Avinash Vem , Dileep Kumar Soma , Krishna R. Narayanan , Jean-Francois Chamberland

Sparse regression codes with approximate message passing (AMP) decoding have gained much attention in recent times. The concepts underlying this coding scheme extend to unsourced access with coded compressed sensing (CCS), as first pointed…

Information Theory · Computer Science 2020-01-14 Vamsi K. Amalladinne , Asit Kumar Pradhan , Cynthia Rush , Jean-Francois Chamberland , Krishna R. Narayanan

Sparse coding (SC) is attracting more and more attention due to its comprehensive theoretical studies and its excellent performance in many signal processing applications. However, most existing sparse coding algorithms are nonconvex and…

Machine Learning · Computer Science 2017-09-12 Xiaodong Feng , Zhiwei Tang , Sen Wu
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