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Integration of Satellite-Aerial-Terrestrial Networks
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Integration of Satellite-Aerial-Terrestrial Networks

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: closed (15 November 2023) | Viewed by 25890

Special Issue Editors

Dr. Kang An

E-Mail Website
Guest Editor
The Sixty-Third Research Institute, National University of Defense Technology, Nanjing 210007, China
Interests: satellite communication; multi-access systems; relay networks (telecommunication); cognitive radio; telecommunication network
Special Issues, Collections and Topics in MDPI journals
Dr. Kefeng Guo

E-Mail Website
Guest Editor
School of Space Information, Space Engineering University, Beijing 101416, China
Interests: satellite communication; multi-access systems; relay networks (telecommunication); cognitive radio; telecommunication network; cooperative communications; 6G
Special Issues, Collections and Topics in MDPI journals
Dr. Xingwang Li

E-Mail Website
Guest Editor
School of Physics and Electronic Information Engineering, Henan Polytechnic University, Jiaozuo 454000, China
Interests: non-orthogonal multiple access (NOMA) schemes; physical layer security; backscatter communication for internet of things; reconfigurable intelligent metasurfaces for 6G communications; ultra-reliable and low-latency communication (URLLC); unmanned aerial vehicle (UAV) communication; hardware-constrained communication systems; unmanned aerial vehicle communication; multiple-input multiple-output (MIMO); energy harvesting
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Bin Li

E-Mail Website
Guest Editor
School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China
Interests: physical layer security; mobile edge computing; UAV communications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Due to the seamless connectivity and high data rate, aerial and space communication has been viewed as a key element to bring real-time, higher-capacity communication and wider coverage in the connection and deployment of a plethora of applications such as smart grids, Internet of Things (IoT), wireless sensor networks, space-based cloud for big data, and vehicular ad-hoc networks. It is viewed as a key element in emergency rescue for earthquakes and fire disasters as well as transoceanic communication that current terrestrial communications cannot cover.

Space and aerial communication is the key point of the Beyond 5 Generation (B5G) networks, which have already attracted a great deal of attention. Nevertheless, owing to the inherent nature of satellite broadcasting and the coverage of huge areas, aerial and space communications can easily be exposed to various security issues. Secure information transmission has aroused extensive interest from the wireless communications community in order to prevent eavesdroppers from taking advantage of the broadcast nature of the radio propagation medium to intercept confidential messages.

The theme of this topic is to investigate transmission secrecy in aerial and space communication, and potential topics may include, but are not limited to, the following:

  • Security protocol for aerial and space communications;
  • B5G network safety measures;
  • Developments in cloud storage security;
  • Interception prevention in aerial and space communications;
  • Developments in radio propagation mediums;
  • Security concerns and studies on radio communication;
  • Satellite broadcasting and security research;
  • Advanced network architecture design for integrating satellite–aerial–terrestrial networks;
  • Network optimization and communication protocol for integrating satellite–aerial–terrestrial networks;
  • Efficient resource allocation strategies for satellite–aerial–terrestrial networks;
  • AI enabled intelligent service for satellite–aerial–terrestrial networks;
  • Cloud/edge computing for satellite–aerial–terrestrial networks;
  • Security and privacy solutions for satellite–aerial–terrestrial networks;
  • Implementation/testbed/deployment of satellite–aerial–terrestrial networks;
  • Integration of satellite–aerial–terrestrial networks with state-of-the-art wireless technologies (e.g., NOMA, backscatter communication, reconfigurable intelligent surfaces, massive MIMO, physical layer security, millimeter-wave communication, cognitive radio, cooperative communication, energy harvesting).

Dr. Kang An
Dr. Kefeng Guo
Dr. Xingwang Li
Prof. Dr. Bin Li
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (16 papers)

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Research

18 pages, 711 KiB  
Article
Spectrum Situation Awareness for Space–Air–Ground Integrated Networks Based on Tensor Computing
by Bin Qi, Wensheng Zhang and Lei Zhang
Sensors 2024, 24(2), 334; https://0-doi-org.brum.beds.ac.uk/10.3390/s24020334 - 05 Jan 2024
Viewed by 705
Abstract
The spectrum situation awareness problem in space–air–ground integrated networks (SAGINs) is studied from a tensor-computing perspective. Tensor and tensor computing, including tensor decomposition, tensor completion and tensor eigenvalues, can satisfy the application requirements of SAGINs. Tensors can effectively handle multidimensional heterogeneous big data [...] Read more.
The spectrum situation awareness problem in space–air–ground integrated networks (SAGINs) is studied from a tensor-computing perspective. Tensor and tensor computing, including tensor decomposition, tensor completion and tensor eigenvalues, can satisfy the application requirements of SAGINs. Tensors can effectively handle multidimensional heterogeneous big data generated by SAGINs. Tensor computing is used to process the big data, with tensor decomposition being used for dimensionality reduction to reduce storage space, and tensor completion utilized for numeric supplementation to overcome the missing data problem. Notably, tensor eigenvalues are used to indicate the intrinsic correlations within the big data. A tensor data model is designed for space–air–ground integrated networks from multiple dimensions. Based on the multidimensional tensor data model, a novel tensor-computing-based spectrum situation awareness scheme is proposed. Two tensor eigenvalue calculation algorithms are studied to generate tensor eigenvalues. The distribution characteristics of tensor eigenvalues are used to design spectrum sensing schemes with hypothesis tests. The main advantage of this algorithm based on tensor eigenvalue distributions is that the statistics of spectrum situation awareness can be completely characterized by tensor eigenvalues. The feasibility of spectrum situation awareness based on tensor eigenvalues is evaluated by simulation results. The new application paradigm of tensor eigenvalue provides a novel direction for practical applications of tensor theory. Full article
(This article belongs to the Special Issue Integration of Satellite-Aerial-Terrestrial Networks)
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19 pages, 599 KiB  
Article
Computation Offloading and Resource Allocation Based on P-DQN in LEO Satellite Edge Networks
by Xu Yang, Hai Fang, Yuan Gao, Xingjie Wang, Kan Wang and Zheng Liu
Sensors 2023, 23(24), 9885; https://0-doi-org.brum.beds.ac.uk/10.3390/s23249885 - 17 Dec 2023
Viewed by 920
Abstract
Traditional low earth orbit (LEO) satellite networks are typically independent of terrestrial networks, which develop relatively slowly due to the on-board capacity limitation. By integrating emerging mobile edge computing (MEC) with LEO satellite networks to form the business-oriented “end-edge-cloud” multi-level computing architecture, some [...] Read more.
Traditional low earth orbit (LEO) satellite networks are typically independent of terrestrial networks, which develop relatively slowly due to the on-board capacity limitation. By integrating emerging mobile edge computing (MEC) with LEO satellite networks to form the business-oriented “end-edge-cloud” multi-level computing architecture, some computing-sensitive tasks can be offloaded by ground terminals to satellites, thereby satisfying more tasks in the network. How to make computation offloading and resource allocation decisions in LEO satellite edge networks, nevertheless, indeed poses challenges in tracking network dynamics and handling sophisticated actions. For the discrete-continuous hybrid action space and time-varying networks, this work aims to use the parameterized deep Q-network (P-DQN) for the joint computation offloading and resource allocation. First, the characteristics of time-varying channels are modeled, and then both communication and computation models under three different offloading decisions are constructed. Second, the constraints on task offloading decisions, on remaining available computing resources, and on the power control of LEO satellites as well as the cloud server are formulated, followed by the maximization problem of satisfied task number over the long run. Third, using the parameterized action Markov decision process (PAMDP) and P-DQN, the joint computing offloading, resource allocation, and power control are made in real time, to accommodate dynamics in LEO satellite edge networks and dispose of the discrete-continuous hybrid action space. Simulation results show that the proposed P-DQN method could approach the optimal control, and outperforms other reinforcement learning (RL) methods for merely either discrete or continuous action space, in terms of the long-term rate of satisfied tasks. Full article
(This article belongs to the Special Issue Integration of Satellite-Aerial-Terrestrial Networks)
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22 pages, 912 KiB  
Article
Integrated Sensing and Communication via Orthogonal Time Frequency Space Signaling with Hybrid Message Passing Detection and Fractional Parameter Estimation
by Ji Zhang, Leqi Cai and Huanyou Liu
Sensors 2023, 23(24), 9874; https://0-doi-org.brum.beds.ac.uk/10.3390/s23249874 - 16 Dec 2023
Cited by 1 | Viewed by 839
Abstract
For the orthogonal time frequency space (OTFS) modulation, we generally multiplex symbols on a new type of carrier waveform in the delay-Doppler (DD) domain. These two parameters can be used to infer the range (R) and velocity (V) of the communication user and [...] Read more.
For the orthogonal time frequency space (OTFS) modulation, we generally multiplex symbols on a new type of carrier waveform in the delay-Doppler (DD) domain. These two parameters can be used to infer the range (R) and velocity (V) of the communication user and sensing target; thus, it is natural for the OTFS to be implemented in integrated sensing and communication (ISAC). A framework for ISAC based on OTFS modulation is proposed in this paper, in which the matched filter scheme with fractional parameter estimation is implemented for radar sensing. In addition, the hybrid message passing (MP) detection algorithm is developed for OTFS symbol demodulation. According to the simulation results, fractional DD shifts associated with multiple targets can be accurately obtained through the proposed framework. Meanwhile, the bit error rate under the proposed detector is less than 10−4 when the signal-to-noise ratio is high enough. Full article
(This article belongs to the Special Issue Integration of Satellite-Aerial-Terrestrial Networks)
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22 pages, 6593 KiB  
Article
Load-Balancing Routing for LEO Satellite Network with Distributed Hops-Based Back-Pressure Strategy
by Chi Han, Wei Xiong and Ronghuan Yu
Sensors 2023, 23(24), 9789; https://0-doi-org.brum.beds.ac.uk/10.3390/s23249789 - 12 Dec 2023
Viewed by 939
Abstract
With the expansion of user scale in LEO satellite networks, unbalanced regional load and bursty network traffic lead to the problem of load disequilibrium. A distributed hops-based back-pressure (DHBP) routing is proposed. DHBP theoretically derives a fast solution for the minimum end-to-end propagation [...] Read more.
With the expansion of user scale in LEO satellite networks, unbalanced regional load and bursty network traffic lead to the problem of load disequilibrium. A distributed hops-based back-pressure (DHBP) routing is proposed. DHBP theoretically derives a fast solution for the minimum end-to-end propagation hops between satellite nodes in inclined-orbit LEO satellite networks; hence, link weights are determined based on remaining hops between the next hop and destination satellites. In order to control the number of available retransmission paths, the permitted propagation region is restricted to a rectangular region consisting of source-destination nodes to reduce the propagation cost. Finally, DHBP is designed distributedly, to realize a dynamic selection of the shortest link with low congestion and balanced traffic distribution without obtaining the whole network topology. Network simulation results demonstrate that DHBP has higher throughput and lower delay under high load conditions compared with state-of-the-art routing protocols. Full article
(This article belongs to the Special Issue Integration of Satellite-Aerial-Terrestrial Networks)
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19 pages, 3277 KiB  
Article
An Asynchronous Collision-Tolerant ACRDA Scheme Based on Satellite-Selection Collaboration-Beamforming for LEO Satellite IoT Networks
by Tao Hong, Rui Liu, Ziwei Liu, Xiaojin Ding and Gengxin Zhang
Sensors 2023, 23(7), 3549; https://0-doi-org.brum.beds.ac.uk/10.3390/s23073549 - 28 Mar 2023
Viewed by 1225
Abstract
In this paper, an asynchronous collision-tolerant ACRDA scheme based on satellite-selection collaboration-beamforming (SC-ACRDA) is proposed to solve the avalanche effect caused by packet collision under random access (RA) high load in the low earth orbit (LEO) satellite Internet of Things (IoT) networks. A [...] Read more.
In this paper, an asynchronous collision-tolerant ACRDA scheme based on satellite-selection collaboration-beamforming (SC-ACRDA) is proposed to solve the avalanche effect caused by packet collision under random access (RA) high load in the low earth orbit (LEO) satellite Internet of Things (IoT) networks. A non-convex optimization problem is formulated to realize the satellite selection problem in multi-satellite collaboration-beamforming. To solve this problem, we employ the Charnes-Cooper transformation to transform a convex optimization problem. In addition, an iterative binary search algorithm is also designed to obtain the optimization parameter. Furthermore, we present a signal processing flow combined with ACRDA protocol and serial interference cancellation (SIC) to solve the packet collision problem effectively in the gateway station. Simulation results show that the proposed SC-ACRDA scheme can effectively solve the avalanche effect and improve the performance of the RA protocol in LEO satellite IoT networks compared with benchmark problems. Full article
(This article belongs to the Special Issue Integration of Satellite-Aerial-Terrestrial Networks)
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17 pages, 593 KiB  
Article
Joint Beamforming Design for RIS-Assisted Integrated Satellite-HAP-Terrestrial Networks Using Deep Reinforcement Learning
by Min Wu, Shibing Zhu, Changqing Li, Yudi Chen and Feng Zhou
Sensors 2023, 23(6), 3034; https://0-doi-org.brum.beds.ac.uk/10.3390/s23063034 - 11 Mar 2023
Cited by 2 | Viewed by 1952
Abstract
In this paper, we consider reconfigurable intelligent surface (RIS)-assisted integrated satellite high-altitude platform terrestrial networks (IS-HAP-TNs) that can improve network performance by exploiting the HAP stability and RIS reflection. Specifically, the reflector RIS is installed on the side of HAP to reflect signals [...] Read more.
In this paper, we consider reconfigurable intelligent surface (RIS)-assisted integrated satellite high-altitude platform terrestrial networks (IS-HAP-TNs) that can improve network performance by exploiting the HAP stability and RIS reflection. Specifically, the reflector RIS is installed on the side of HAP to reflect signals from the multiple ground user equipment (UE) to the satellite. To aim at maximizing the system sum rate, we jointly optimize the transmit beamforming matrix at the ground UEs and RIS phase shift matrix. Due to the limitation of the unit modulus of the RIS reflective elements constraint, the combinatorial optimization problem is difficult to tackle effectively by traditional solving methods. Based on this, this paper studies the deep reinforcement learning (DRL) algorithm to achieve online decision making for this joint optimization problem. In addition, it is verified through simulation experiments that the proposed DRL algorithm outperforms the standard scheme in terms of system performance, execution time, and computing speed, making real-time decision making truly feasible. Full article
(This article belongs to the Special Issue Integration of Satellite-Aerial-Terrestrial Networks)
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24 pages, 1157 KiB  
Article
Link-State Aware Hybrid Routing in the Terrestrial–Satellite Integrated Network
by Huihui Xu, Zhangsong Shi, Mingliu Liu, Ning Zhang, Yanjun Yan and Guangjie Han
Sensors 2022, 22(23), 9124; https://0-doi-org.brum.beds.ac.uk/10.3390/s22239124 - 24 Nov 2022
Cited by 3 | Viewed by 1508
Abstract
In this paper, we study data transmission in the Terrestrial–Satellite Integrated Network (TSIN), where terrestrial networks and satellites are combined together to provide seamless global network services for ground users. However, efficiency of the data transmission is limited by the time-varying inter-satellite link [...] Read more.
In this paper, we study data transmission in the Terrestrial–Satellite Integrated Network (TSIN), where terrestrial networks and satellites are combined together to provide seamless global network services for ground users. However, efficiency of the data transmission is limited by the time-varying inter-satellite link connection and intermittent terrestrial–satellite link connection. Therefore, we propose a link-state aware hybrid routing algorithm, which selects the integrated data transmission path adaptively in this paper. First of all, a space–time topology model is constructed to represent the dynamic link connections in TSIN. Thus, the transmission delay can be analyzed accordingly, and the data transmission problem can then be formulated. To balance the effectiveness and accuracy of searching a hybrid path, we carefully discuss the optimization of space–time topology updating, and propose an inter-satellite link selection algorithm. For the terrestrial–satellite link in hybrid routing, the data transmission problem is transformed into a weighted bipartite graph matching problem and solved with a Kuhn–Munkres-based link selection algorithm. To verify the effectiveness of our proposed routing algorithm, extensive simulations are conducted based on a realistic Hongyun constellation project. Results show that the network performance is improved with respect to data transmission delay, packet loss rate, and throughput. Full article
(This article belongs to the Special Issue Integration of Satellite-Aerial-Terrestrial Networks)
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14 pages, 865 KiB  
Article
A Radio Environment Map Updating Mechanism Based on an Attention Mechanism and Siamese Neural Networks
by Pan Zhen, Bangning Zhang, Chen Xie and Daoxing Guo
Sensors 2022, 22(18), 6797; https://0-doi-org.brum.beds.ac.uk/10.3390/s22186797 - 08 Sep 2022
Cited by 2 | Viewed by 1598
Abstract
A radio environment map (REM) is an effective spectrum management tool. With the increase in the number of mobile devices, the wireless environment changes more and more frequently, bringing new challenges to REM updates. Traditional update methods usually rely on the amount of [...] Read more.
A radio environment map (REM) is an effective spectrum management tool. With the increase in the number of mobile devices, the wireless environment changes more and more frequently, bringing new challenges to REM updates. Traditional update methods usually rely on the amount of data collected for updating without paying attention to whether the wireless environment has changed enough. In particular, a waste of computational resources results from the frequently updated REM when the wireless environment does not change much. When the wireless environment changes a lot, the REM is not updated promptly, resulting in a decrease in REM accuracy. To overcome the above problems, this work combines the Siamese neural network and an attention mechanism in computer vision and proposes an update mechanism based on the amount of wireless environmental change starting from image data. The method compares the newly collected crowdsourced data with the constructed REM in terms of similarity. It uses similarity to measure the necessity of the REM to be updated. The algorithm in this paper can achieve a controlled update by setting a similarity threshold with good controllability. In addition, the effectiveness of the algorithm in detecting changes of the wireless environment has been demonstrated by combing simulation data. Full article
(This article belongs to the Special Issue Integration of Satellite-Aerial-Terrestrial Networks)
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11 pages, 3664 KiB  
Article
A Joint Automatic Modulation Classification Scheme in Spatial Cognitive Communication
by Mengtao Wang, Youchen Fan, Shengliang Fang, Tianshu Cui and Donghang Cheng
Sensors 2022, 22(17), 6500; https://0-doi-org.brum.beds.ac.uk/10.3390/s22176500 - 29 Aug 2022
Cited by 4 | Viewed by 1370
Abstract
Automatic modulation discrimination (AMC) is one of the critical technologies in spatial cognitive communication systems. Building a high-performance AMC model in intelligent receivers can help to realize adaptive signal synchronization and demodulation. However, tackling the intra-class diversity problem is challenging to AMC based [...] Read more.
Automatic modulation discrimination (AMC) is one of the critical technologies in spatial cognitive communication systems. Building a high-performance AMC model in intelligent receivers can help to realize adaptive signal synchronization and demodulation. However, tackling the intra-class diversity problem is challenging to AMC based on deep learning (DL), as 16QAM and 64QAM are not easily distinguished by DL networks. In order to overcome the problem, this paper proposes a joint AMC model that combines DL and expert features. In this model, the former builds a neural network that can extract the time series and phase features of in-phase and quadrature component (IQ) samples, which improves the feature extraction capability of the network in similar models; the latter achieves accurate classification of QAM signals by constructing effective feature parameters. Experimental results demonstrate that our proposed joint AMC model performs better than the benchmark networks. The classification accuracy is increased by 11.5% at a 10 dB signal-to-noise ratio (SNR). At the same time, it also improves the discrimination of QAM signals. Full article
(This article belongs to the Special Issue Integration of Satellite-Aerial-Terrestrial Networks)
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16 pages, 563 KiB  
Article
Covert Performance for Integrated Satellite Multiple Terrestrial Relay Networks with Partial Relay Selection
by Zeke Wu, Rui Liu, Haifeng Shuai, Shibing Zhu and Changqing Li
Sensors 2022, 22(15), 5524; https://0-doi-org.brum.beds.ac.uk/10.3390/s22155524 - 25 Jul 2022
Cited by 6 | Viewed by 1419
Abstract
Integrated satellite multiple terrestrial relay network (ISMTRN) is a new network architecture that combines satellite communication with terrestrial communication. It both utilizes the advantages of the two systems and overcomes their shortcomings. However, security issues inevitably arise in the ISMTRN resulting from the [...] Read more.
Integrated satellite multiple terrestrial relay network (ISMTRN) is a new network architecture that combines satellite communication with terrestrial communication. It both utilizes the advantages of the two systems and overcomes their shortcomings. However, security issues inevitably arise in the ISMTRN resulting from the broad coverage of the satellite beams and the openness of wireless communication. One of the promising methods to achieve secure transmission is covert communication technology, which has been a hot discussion topic in recent years. In this paper, we investigate the performance of covert communication in the ISMTRN with partial relay selection. Particularly, when the satellite transmits its signal to the user, we consider the scenario that the selected relay opportunistically sends covert information to the destination. Furthermore, the closed-form error detection probability and average covert communication rate are derived. Finally, numerical simulation results are provided to reveal the impact of critical parameters on system covert performance. Full article
(This article belongs to the Special Issue Integration of Satellite-Aerial-Terrestrial Networks)
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15 pages, 938 KiB  
Article
Secrecy Capacity Maximization of UAV-Enabled Relaying Systems with 3D Trajectory Design and Resource Allocation
by Qi An, Yu Pan, Huizhu Han and Hang Hu
Sensors 2022, 22(12), 4519; https://0-doi-org.brum.beds.ac.uk/10.3390/s22124519 - 15 Jun 2022
Cited by 4 | Viewed by 1629
Abstract
Unmanned aerial vehicles (UAVs) have attracted considerable attention, thanks to their high flexibility, on-demand deployment and the freedom in trajectory design. The communication channel quality can be effectively improved by using UAV to build a line-of-sight communication link between the transmitter and the [...] Read more.
Unmanned aerial vehicles (UAVs) have attracted considerable attention, thanks to their high flexibility, on-demand deployment and the freedom in trajectory design. The communication channel quality can be effectively improved by using UAV to build a line-of-sight communication link between the transmitter and the receiver. Furthermore, there is increasing demand for communication security improvement, as the openness of a wireless channel brings serious threat. This paper formulates a secrecy capacity optimization problem of a UAV-enabled relay communication system in the presence of malicious eavesdroppers, in which the secrecy capacity is maximized by jointly optimizing the UAV relay’s location, power allocation, and bandwidth allocation under the communication quality and information causality constraints. A successive convex approximation–alternative iterative optimization (SCA-AIO) algorithm is proposed to solve this highly coupled nonconvex problem. Simulation results demonstrate the superiority of the proposed secrecy transmission strategy with optimal trajectory design and resource allocation compared with the benchmark schemes and reveal the impacts of communication resources on system performance. Full article
(This article belongs to the Special Issue Integration of Satellite-Aerial-Terrestrial Networks)
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13 pages, 1600 KiB  
Article
NC-OFDM Satellite Communication Based on Compressed Spectrum Sensing
by Yong Wang, Hehao Niu, Qingsong Zhao, Lei Wang, Yue Gao and Zhi Lin
Sensors 2022, 22(10), 3800; https://0-doi-org.brum.beds.ac.uk/10.3390/s22103800 - 17 May 2022
Viewed by 1568
Abstract
With the fast development of giant LEO constellations, the effective spectrum utilization has been regarded as one of the key orientations for satellite communications. This paper focuses on improving the spectrum utilization efficiency of satellite communications by proposing a non-continuous orthogonal frequency division [...] Read more.
With the fast development of giant LEO constellations, the effective spectrum utilization has been regarded as one of the key orientations for satellite communications. This paper focuses on improving the spectrum utilization efficiency of satellite communications by proposing a non-continuous orthogonal frequency division multiplexing (NC-OFDM) method. Based on the models of NC-OFDM system, we first propose a sub-carrier allocation method by using spectrum sensing to efficiently perceive and utilize the spectrum holes in the satellite communication system. Then, a hybrid genetic particle swarm optimization method is adopted to allocate the channel resources effectively. Finally, simulation results verify that the proposed algorithm can significantly improve the spectrum efficiency of satellite communications. Full article
(This article belongs to the Special Issue Integration of Satellite-Aerial-Terrestrial Networks)
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17 pages, 1524 KiB  
Article
Shooting Utility Maximization in UAV-Assisted Wireless Camera Sensor Networks
by Yulei Wu, Simeng Feng, Chao Dong and Weijun Wang
Sensors 2022, 22(10), 3685; https://0-doi-org.brum.beds.ac.uk/10.3390/s22103685 - 12 May 2022
Cited by 3 | Viewed by 1485
Abstract
Recently, wireless camera sensor networks (WCSNs) have entered an era of rapid development, and WCSNs assisted by unmanned aerial vehicles (UAVs) are capable of providing enhanced flexibility, robustness and efficiency when executing missions such as shooting targets. Existing research has mainly focused on [...] Read more.
Recently, wireless camera sensor networks (WCSNs) have entered an era of rapid development, and WCSNs assisted by unmanned aerial vehicles (UAVs) are capable of providing enhanced flexibility, robustness and efficiency when executing missions such as shooting targets. Existing research has mainly focused on back-end image processing to improve the quality of captured images, but it has neglected the question of attaining quality images on the front-end, which is significantly influenced by the location and hovering time of the UAV. Therefore, in this paper, we conceive a novel shooting utility model to quantify shooting quality, which is maximized by simultaneously considering the UAV’s trajectory planning, hovering time and shooting point selection. To expound further, we prove the submodularity of the utility function, whereby the original problem can be expressed as a submodular maximization problem with path constraints, and we propose a utility-cost ratio (UCR) algorithm to maximize shooting utility through two-level optimization. Then, by using the relaxation of the cost function, we analyze the gap between the proposed algorithm and the optimal algorithm (OPT) and prove that the UCR algorithm has a bi-criterion approximation ratio of 1−1/e/2. Simulation results show that the algorithm outperforms both the random algorithm (RAN) and the maximum shooting utility point selection algorithm (MSU) in terms of shooting utility and time utilization efficiency, improving shooting utility by 51% and 21% compared to the RAN and MSU algorithms, respectively, and achieving at least 88.2% of the OPT algorithm in terms of time utilization efficiency. Full article
(This article belongs to the Special Issue Integration of Satellite-Aerial-Terrestrial Networks)
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20 pages, 4812 KiB  
Article
Reliable and Energy-Efficient LEO Satellite Communication with IR-HARQ via Power Allocation
by Hongxiu Bian and Rongke Liu
Sensors 2022, 22(8), 3035; https://0-doi-org.brum.beds.ac.uk/10.3390/s22083035 - 15 Apr 2022
Cited by 2 | Viewed by 1878
Abstract
This paper examines reliable and energy-efficient transmission in low earth orbit (LEO) satellite communication systems. In particular, we analyze the link transmission characteristics of the LEO satellite to the ground user and model the channel as a combination of large-scale fading and small-scale [...] Read more.
This paper examines reliable and energy-efficient transmission in low earth orbit (LEO) satellite communication systems. In particular, we analyze the link transmission characteristics of the LEO satellite to the ground user and model the channel as a combination of large-scale fading and small-scale fading. Based on this, we consider an incremental redundancy hybrid automatic repeat request (IR-HARQ) technique with a variable-power allocation method, and we call it the IR-HARQ-VPA scheme. In this method, the outage probability after each IR-HARQ round can be obtained through numerical integration based on the fast Fourier transform (NI-FFT). This method is suitable for any number of HARQ transmission rounds and can improve the accuracy compared with previous approximation methods. In addition, variable-power allocation based on the genetic algorithm (VPA-GA) is introduced to reduce the energy consumption. The simulation results show that the proposed IR-HARQ-VPA scheme cannot only meet the requirements of transmission reliability but also achieves higher energy efficiency than IR-HARQ with equal power (IR-HARQ-EP) transmission and a previously proposed variable-power allocation method. Moreover, the simulation results in a LEO satellite communication window also confirm the effectiveness of the proposed IR-HARQ-VPA scheme. Full article
(This article belongs to the Special Issue Integration of Satellite-Aerial-Terrestrial Networks)
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15 pages, 709 KiB  
Article
Ergodic Capacity of NOMA-Based Multi-Antenna LMS Systems with Imperfect Limitations
by Haifeng Shuai, Rui Liu, Shibing Zhu, Changqing Li and Yi Fang
Sensors 2022, 22(1), 330; https://0-doi-org.brum.beds.ac.uk/10.3390/s22010330 - 02 Jan 2022
Cited by 3 | Viewed by 1373
Abstract
With the rapid development of land mobile satellite (LMS) systems, large scale sensors and devices are willing to request wireless services, which is a challenge to the quality of service requirement and spectrum resources utilization on onboard LMS systems. Under this situation, the [...] Read more.
With the rapid development of land mobile satellite (LMS) systems, large scale sensors and devices are willing to request wireless services, which is a challenge to the quality of service requirement and spectrum resources utilization on onboard LMS systems. Under this situation, the non-orthogonal multiple access (NOMA) is regarded as a promising technology for improving spectrum efficiency of LMS systems. In this paper, we analyze the ergodic capacity (EC) of NOMA-based multi-antenna LMS systems in the presence of imperfect limitations, i.e., channel estimation errors, imperfect successive interference cancellation, and co-channel interference. By considering multiple antennas at the satellite and terrestrial sensor users, the closed-form expression for EC of the NOMA-based LMS systems with imperfect limitations is obtained. Monte Carlo simulations are provided to verify theoretical results and reveal the influence of key parameters on system performance. Full article
(This article belongs to the Special Issue Integration of Satellite-Aerial-Terrestrial Networks)
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Article
Energy Efficient UAV Flight Path Model for Cluster Head Selection in Next-Generation Wireless Sensor Networks
by Syed Kamran Haider, Aimin Jiang, Ahmad Almogren, Ateeq Ur Rehman, Abbas Ahmed, Wali Ullah Khan and Habib Hamam
Sensors 2021, 21(24), 8445; https://0-doi-org.brum.beds.ac.uk/10.3390/s21248445 - 17 Dec 2021
Cited by 23 | Viewed by 2968
Abstract
Wireless sensor networks (WSNs) are one of the fundamental infrastructures for Internet of Things (IoTs) technology. Efficient energy consumption is one of the greatest challenges in WSNs because of its resource-constrained sensor nodes (SNs). Clustering techniques can significantly help resolve this issue and [...] Read more.
Wireless sensor networks (WSNs) are one of the fundamental infrastructures for Internet of Things (IoTs) technology. Efficient energy consumption is one of the greatest challenges in WSNs because of its resource-constrained sensor nodes (SNs). Clustering techniques can significantly help resolve this issue and extend the network’s lifespan. In clustering, WSN is divided into various clusters, and a cluster head (CH) is selected in each cluster. The selection of appropriate CHs highly influences the clustering technique, and poor cluster structures lead toward the early death of WSNs. In this paper, we propose an energy-efficient clustering and cluster head selection technique for next-generation wireless sensor networks (NG-WSNs). The proposed clustering approach is based on the midpoint technique, considering residual energy and distance among nodes. It distributes the sensors uniformly creating balanced clusters, and uses multihop communication for distant CHs to the base station (BS). We consider a four-layer hierarchical network composed of SNs, CHs, unmanned aerial vehicle (UAV), and BS. The UAV brings the advantage of flexibility and mobility; it shortens the communication range of sensors, which leads to an extended lifetime. Finally, a simulated annealing algorithm is applied for the optimal trajectory of the UAV according to the ground sensor network. The experimental results show that the proposed approach outperforms with respect to energy efficiency and network lifetime when compared with state-of-the-art techniques from recent literature. Full article
(This article belongs to the Special Issue Integration of Satellite-Aerial-Terrestrial Networks)
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