User Activity Detection and Channel Estimation for Grant-Free Random Access in LEO Satellite-Enabled Internet of Things

Zhang, Zhaoji; Liu, Ying; Huang, Chongwen; Guo, Qinghua; Liu, Lei; Yuen, Chau; Guan, Yong Liang

doi:10.1109/jiot.2020.2997336

Cited by 109 publications

(41 citation statements)

References 36 publications

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“…, as M becomes large. In (5) and (6), the scalar τ 2 ∞ is the solution converged to the state evolution of the AMP algorithm. In the high signal-to-noise ratio (SNR) regions, i.e.,…”

Section: A Device Activity Detection and Channel Estimationmentioning

confidence: 99%

“…Due to the sparse nature of access in the IoT, DAD and CE can be transformed into a compressed sensing problem. In recent years, researchers have studied many algorithms for DAD and CE, such as those based on mean-field message passing [4] or Gaussian message passing [5], [6]. However, these algorithms do not have a rigorous performance analysis, which is usually required by researchers to study the system performance.…”

Section: Introductionmentioning

confidence: 99%

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Analysis and Optimization of Massive Access to the IoT Relying on Multi-Pair Two-Way Massive MIMO Relay Systems

Peng

Chen

et al. 2021

IEEE Trans. Commun.

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We investigate massive access in the Internet-of-Things (IoT) relying on multi-pair two-way amplify-and-forward (AF) relay systems using massive multiple-input multiple-output (MIMO). We utilize the approximate message passing (AMP) algorithm for joint device activity detection and channel estimation. Furthermore, we analyze the achievable rates for multiple pairs of active devices and derive the closed-form expressions for both maximum-ratio combining/maximum-ratio transmission (MRC/MRT) and zero-forcing reception/zero-forcing transmission (ZFR/ZFT)-based beamforming schemes adopted at the relay. Moreover, to improve the achievable sum rates, we propose a low-complexity algorithm for optimizing the pilot length L. Our simulation results verify the accuracy of the closed-form expressions of the MRC/MRT and ZFR/ZFT scenarios. Finally, the proposed pilot-length optimization algorithm performs well in both the MRC/MRT and ZFR/ZFT scenarios.

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“…, as M becomes large. In (5) and (6), the scalar τ 2 ∞ is the solution converged to the state evolution of the AMP algorithm. In the high signal-to-noise ratio (SNR) regions, i.e.,…”

Section: A Device Activity Detection and Channel Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Analysis and Optimization of Massive Access to the IoT Relying on Multi-Pair Two-Way Massive MIMO Relay Systems

Peng

Chen

et al. 2021

IEEE Trans. Commun.

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show abstract

“…In fact, confronted with the massive machine-type communication, the grant-free random-access (GF-RA) schemes are always favored in IoT for their low-complexity, low-latency, and high-reliability [3], where active IoT terminals share the non-orthogonal resource allocation and directly transmit their data packets and pilot sequences without applying for the grant. Then along comes one crucial task to detect IoT terminals' activity.…”

Section: Introductionmentioning

confidence: 99%

“…Then along comes one crucial task to detect IoT terminals' activity. By exploiting the intrinsic sporadic traffic property [3], several compressive sensing (CS)-based GF-RA schemes have been proposed, where active user detection (AUD) was formulated as a sparse signal recovery problem [4]. In [5], [6], two low-complexity multi-user detectors based on structured CS were proposed to jointly detect users' activity and transmit signal in several continuous time slots.…”

Section: Introductionmentioning

confidence: 99%

Joint Active User Detection and Channel Estimation for Grant-Free NOMA-OTFS in LEO Constellation Internet-of-Things

Zhou

Gao

2021

Preprint

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The flourishing low-Earth orbit (LEO) constellation communication network provides a promising solution for seamless coverage services to Internet-of-Things (IoT) terminals. However, confronted with massive connectivity and rapid variation of terrestrial-satellite link (TSL), the traditional grant-free randomaccess schemes always fail to match this scenario. In this paper, a new non-orthogonal multiple-access (NOMA) transmission protocol that incorporates orthogonal time frequency space (OTFS) modulation is proposed to solve these problems. Furthermore, we propose a two-stages joint active user detection and channel estimation scheme based on the training sequences aided OTFS data frame structure. Specifically, in the first stage, with the aid of training sequences, we perform active user detection and coarse channel estimation by recovering the sparse sampled channel vectors. And then, we develop a parametric approach to facilitate more accurate result of channel estimation with the previously recovered sampled channel vectors according to the inherent characteristics of TSL channel. Simulation results demonstrate the superiority of the proposed method in this kind of highmobility scenario in the end.Index Terms-Internet of Things (IoT), low-Earth orbit (LEO) satellite, orthogonal time frequency space (OTFS), nonorthogonal multiple access (NOMA).

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“…can make full use of advantages provided by mature terrestrial networks, such as high speed, ultra-reliability, and low latency [1]. However, as for Internet of remote things (IoRT) located in geographies such as oceans, forests, and polar regions, the costs of deployment and maintenance of the terrestrial networks are very high, which imposes great challenges on providing cost-effective network access [2]- [4]. In addition, low power consumption and long battery life on IoRT devices have become paramount requirements of the industry [5].…”

Section: Introductionmentioning

confidence: 99%

Sum-Rate Maximization for UAV Aided Wireless Power Transfer in Space-Air-Ground Networks

et al. 2020

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The Internet of things (IoT) has become a prominent platform which bridges diverse technologies in order to meet the ever-increasing application requirements of various industries. However, the IoT devices, especially in remote areas that lack infrastructures, are featured by the restricted energy and pose great challenges on network access and sustainable communication. In this paper, we investigate the unmanned aerial vehicle (UAV) aided wireless power transfer under a space-air-ground (SAG) network, where the UAV is exploited as an aerial relay to assist in uploading information generated by ground nodes (GNs), and mounted with energy transmitter to deliver wireless energy for GNs. The goal is to maximize the system sum rate while satisfying the proportional rate for GNs and the sustainability of the ground network. To this end, by adopting decode and forward (DF) and amplify and forward (AF) protocols, two sum rate maximization problems are formulated via jointly optimizing power control, time allocation as well as UAV trajectory. The resource allocation problems are both nonconvex, which are difficult to solve directly. To tackle them, two near-optimal iterative algorithms are proposed by leveraging the successive convex approximation technology and the alternating optimization method. Extensive simulations are provided to demonstrate the effectiveness of the proposed algorithms and evaluate the impacts of various parameters on DF and AF relays. INDEX TERMS unmanned aerial vehicle (UAV); wireless power transfer (WPT); space-air-ground (SAG); decode-and-forward (DF); amplify-and-forward (AF).

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User Activity Detection and Channel Estimation for Grant-Free Random Access in LEO Satellite-Enabled Internet of Things

Cited by 109 publications

References 36 publications

Analysis and Optimization of Massive Access to the IoT Relying on Multi-Pair Two-Way Massive MIMO Relay Systems

Analysis and Optimization of Massive Access to the IoT Relying on Multi-Pair Two-Way Massive MIMO Relay Systems

Joint Active User Detection and Channel Estimation for Grant-Free NOMA-OTFS in LEO Constellation Internet-of-Things

Sum-Rate Maximization for UAV Aided Wireless Power Transfer in Space-Air-Ground Networks

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