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相关论文: An Investigation of the Compressed Sensing Phase i…

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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…

This paper addresses the unsourced/uncoordinated random access problem in an integrated sensing and communications (ISAC) system, with a focus on uplink multiple access code design. Recent theoretical advancements highlight that an ISAC…

信息论 · 计算机科学 2025-04-25 Zhentian Zhang , Jian Dang , Kai-Kit Wong , Zaichen Zhang , Christos Masouros

Massive communication is one of key scenarios of 6G where two magnitude higher connection density would be required to serve diverse services. As a promising direction, unsourced multiple access has been proved to outperform significantly…

信息论 · 计算机科学 2024-11-18 Yifei Yuan , Yuhong Huang , Chunlin Yan , Sen Wang , Shuai Ma , Xiaodong Shen

A key challenge of massive MTC (mMTC), is the joint detection of device activity and decoding of data. The sparse characteristics of mMTC makes compressed sensing (CS) approaches a promising solution to the device detection problem.…

信息论 · 计算机科学 2018-06-27 Kamil Senel , Erik G. Larsson

The central challenge in massive machine-type communications (mMTC) is to connect a large number of uncoordinated devices through a limited spectrum. The typical mMTC communication pattern is sporadic, with short packets. This could be…

信息论 · 计算机科学 2022-09-29 Yanna Bai , Wei Chen , Feifei Sun , Bo Ai , Petar Popovski

Massive machine-type communications (mMTC) is a crucial scenario to support booming Internet of Things (IoTs) applications. In mMTC, although a large number of devices are registered to an access point (AP), very few of them are active with…

信息论 · 计算机科学 2022-09-07 Jiaqi Liu , Gang Wu , Xiaoxu Zhang , Shu Fang , Shaoqian Li

Unsourced random access (URA) is a recently proposed multiple access paradigm tailored to the uplink channel of machine-type communication networks. By exploiting a strong connection between URA and compressed sensing, the massive multiple…

This paper investigates the unsourced random access (URA) scheme to accommodate numerous machine-type users communicating to a base station equipped with multiple antennas. Existing works adopt a slotted transmission strategy to reduce…

信息论 · 计算机科学 2022-02-17 Xinyu Xie , Yongpeng Wu , Jianping An , Junyuan Gao , Wenjun Zhang , Chengwen Xing , Kai-Kit Wong , Chengshan Xiao

This paper considers a simple on-off random multiple access channel, where n users communicate simultaneously to a single receiver over m degrees of freedom. Each user transmits with probability lambda, where typically lambda n < m << n,…

信息论 · 计算机科学 2009-03-09 Alyson K. Fletcher , Sundeep Rangan , Vivek K Goyal

Massive machine-type communications (mMTC) are poised to provide ubiquitous connectivity for billions of Internet-of-Things (IoT) devices. However, the required low-latency massive access necessitates a paradigm shift in the design of…

信息论 · 计算机科学 2021-08-24 Yikun Mei , Zhen Gao , Yongpeng Wu , Wei Chen , Jun Zhang , Derrick Wing Kwan Ng , Marco Di Renzo

Cost-efficient compressive sensing is challenging when facing large-scale data, {\em i.e.}, data with large sizes. Conventional compressive sensing methods for large-scale data will suffer from low computational efficiency and massive…

数据结构与算法 · 计算机科学 2016-03-18 Sung-Hsien Hsieh , Chun-Shien Lu , Soo-Chang Pei

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…

信号处理 · 电气工程与系统科学 2019-06-26 Vamsi K. Amalladinne , Jean-Francois Chamberland , Krishna R. Narayanan

Mobile crowdsourced sensing (MCS) is a new paradigm which takes advantage of the pervasive smartphones to efficiently collect data, enabling numerous novel applications. To achieve good service quality for a MCS application, incentive…

计算机科学与博弈论 · 计算机科学 2013-06-25 Dong Zhao , Xiang-Yang Li , Huadong Ma

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…

We present an unsourced multiple access (UMAC) scheme tailored to high-mobility wireless channels. The proposed construction is based on orthogonal time frequency space (OTFS) modulation and sparse interleaver division multiple access…

信号处理 · 电气工程与系统科学 2026-01-21 Davide Bergamasco , Federico Clazzer , Paolo Casari

This article introduces a novel communication paradigm for the unsourced, uncoordinated Gaussian multiple access problem. The major components of the envisioned framework are as follows. The encoded bits of every message are partitioned…

This paper analyzes the impact of non-Gaussian multipath component (MPC) amplitude distributions on the performance of Compressed Sensing (CS) channel estimators for OFDM systems. The number of dominant MPCs that any CS algorithm needs to…

信息论 · 计算机科学 2020-02-24 Felipe Gomez-Cuba , Andrea J. Goldsmith

In future wireless networks, one fundamental challenge for massive machine-type communications (mMTC) lies in the reliable support of massive connectivity with low latency. Against this background, this paper proposes a compressive sensing…

信息论 · 计算机科学 2018-09-13 Malong Ke , Zhen Gao , Yongpeng Wu , Xiangming Meng

Support massive connectivity is an important requirement in 5G wireless communication system. For massive Machine Type Communication (MTC) scenario, since the network is expected to accommodate a massive number of MTC devices with sparse…

信息论 · 计算机科学 2017-01-11 Yanlun Wu , Jun Fang

The advent of the sixth-generation (6G) of wireless communications has given rise to the necessity to connect vast quantities of heterogeneous wireless devices, which requires advanced system capabilities far beyond existing network…

信息论 · 计算机科学 2023-11-14 Zhen Gao , Malong Ke , Yikun Mei , Li Qiao , Sheng Chen , Derrick Wing Kwan Ng , H. Vincent Poor
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