Collaborative LEO Satellites for Secure and Green Internet of Remote Things

Yue, Pingyue; Du, Jiaheng; Zhang, Rui; Ding, Haichuan; Shuai, Wang; An, Jianping

doi:10.1109/jiot.2022.3223913

Cited by 9 publications

(3 citation statements)

References 64 publications

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“…The authors in [ 76 ] propose utilizing collaborative LEO satellites to enhance IoRT systems. This approach involves combining uplink signals from multiple LEO satellites, substantially improving SNR, and reducing power requirements for energy-constrained terminals.…”

Section: Iort Systems Based On Space-borne Ntn Networkmentioning

confidence: 99%

Non-Terrestrial Networks for Energy-Efficient Connectivity of Remote IoT Devices in the 6G Era: A Survey

Plastras,

Tsoumatidis,

Skoutas

et al. 2024

Sensors

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The Internet of Things (IoT) is gaining popularity and market share, driven by its ability to connect devices and systems that were previously siloed, enabling new applications and services in a cost-efficient manner. Thus, the IoT fuels societal transformation and enables groundbreaking innovations like autonomous transport, robotic assistance, and remote healthcare solutions. However, when considering the Internet of Remote Things (IoRT), which refers to the expansion of IoT in remote and geographically isolated areas where neither terrestrial nor cellular networks are available, internet connectivity becomes a challenging issue. Non-Terrestrial Networks (NTNs) are increasingly gaining popularity as a solution to provide connectivity in remote areas due to the growing integration of satellites and Unmanned Aerial Vehicles (UAVs) with cellular networks. In this survey, we provide the technological framework for NTNs and Remote IoT, followed by a classification of the most recent scientific research on NTN-based IoRT systems. Therefore, we provide a comprehensive overview of the current state of research in IoRT and identify emerging research areas with high potential. In conclusion, we present and discuss 3GPP’s roadmap for NTN standardization, which aims to establish an energy-efficient IoRT environment in the 6G era.

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Section: Iort Systems Based On Space-borne Ntn Networkmentioning

confidence: 99%

Non-Terrestrial Networks for Energy-Efficient Connectivity of Remote IoT Devices in the 6G Era: A Survey

Plastras,

Tsoumatidis,

Skoutas

et al. 2024

Sensors

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show abstract

“…The four cases of our proposed integrated satellite-terrestrial networks offer various scenarios, especially in remote and rural areas. Here are some potential use cases for supporting the operation of "Case 1-3" with end-user devices equipped with both sub-6GHz patch antennas and satellite modules, i.e., integrated networks offer resilient communications in disaster-prone areas with damaged or nonexistent terrestrial infrastructure, ensuring reliable connectivity for emergency responders and affected communities [46]; in remote agricultural regions, they support precision agriculture techniques by enabling real-time monitoring and control of farming operations [47]; integrated networks also enhance connectivity along transportation routes, providing continuous communication links for vehicles and cargo containers.…”

Section: A Related Workmentioning

confidence: 99%

Multi-Connectivity Between Terrestrial and Non-Terrestrial MIMO Systems

Shang,

Li,

et al. 2024

IEEE Open J. Commun. Soc.

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Communicating in a non-terrestrial network (NTN) has recently emerged as a promising technology to provide global seamless connectivity. Although low earth orbit (LEO) satellites in an NTN have been employed for providing ubiquitous coverage and high data rates for ground users, especially in emergent outdoor scenarios, NTN has not been integrated into the design of multi-connectivity for users in a terrestrial network (TN). Inspired by the 3rd Generation Partnership Program (3GPP) suggestion, this paper investigates TN-NTN-combined multi-connectivity downlink multiple-input multiple-output (MIMO) communication system, where each user may simultaneously connect to a base station (BS) in a TN and an LEO satellite in an NTN. Specifically, each user may have four different downlink access modes: served by both an LEO satellite and a BS, served by a BS, served by an LEO satellite, and not scheduled. Zero-forcing beamforming is employed at each LEO satellite to reduce the mutual interference among the satellite's served users, and maximum ratio transmission beamforming is used at each terrestrial BS to enhance the downlink signal strength. By deriving the probability of each access mode and modeling the interference in such a TN-NTN-combined multi-connectivity MIMO system, we obtain a typical user's downlink coverage probability and average achievable data rate. Extensive Monte Carlo simulations are conducted to validate our analytical derivations. Simulation results demonstrate that the user's coverage probability and average achievable data rate can be significantly improved by realizing multi-connectivity with both TN and NTN compared to pure TN or NTN.

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“…Since many IoT devices are distributed in long-distance or inaccessible areas and have limited energy supply, traditional data collection methods can no longer meet the demand. Therefore, we need to develop novel data collection methods to solve this challenging task [9,10]. Some novel data collection schemes have already emerged.…”

Section: Introductionmentioning

confidence: 99%

A PSO-based energy-efficient data collection optimization algorithm for UAV mission planning

Lin,

Wang,

Tian

et al. 2024

PLoS ONE

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With the development of the Internet of Things (IoT), the use of UAV-based data collection systems has become a very popular research topic. This paper focuses on the energy consumption problem of this system. Genetic algorithms and swarm algorithms are effective approaches for solving this problem. However, optimizing UAV energy consumption remains a challenging task due to the inherent characteristics of these algorithms, which make it difficult to achieve the optimum solution. In this paper, a novel particle swarm optimization (PSO) algorithm called Double Self-Limiting PSO (DSLPSO) is proposed to minimize the energy consumption of the unmanned aerial vehicle (UAV). DSLPSO refers to the operational principle of PSO and incorporates two new mechanisms. The first mechanism is to restrict the particle movement, improving the local search capability of the algorithm. The second mechanism dynamically adjusts the search range, which improves the algorithm’s global search capability. DSLPSO employs a variable population strategy that treats the entire population as a single mission plan for the UAV and dynamically adjusts the number of stopping points. In addition, the proposed algorithm was also simulated using public and random datasets. The effectiveness of the proposed DSLPSO and the two new mechanisms has been verified through experiments. The DSLPSO algorithm can effectively improve the lifetime of the UAV, and the two newly proposed mechanisms have potential for optimization work.

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Collaborative LEO Satellites for Secure and Green Internet of Remote Things

Cited by 9 publications

References 64 publications

Non-Terrestrial Networks for Energy-Efficient Connectivity of Remote IoT Devices in the 6G Era: A Survey

Non-Terrestrial Networks for Energy-Efficient Connectivity of Remote IoT Devices in the 6G Era: A Survey

Multi-Connectivity Between Terrestrial and Non-Terrestrial MIMO Systems

A PSO-based energy-efficient data collection optimization algorithm for UAV mission planning

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