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    FEATURE TOPIC: LEO SATELLITE ACCESS NETWORK
  • FEATURE TOPIC: LEO SATELLITE ACCESS NETWORK
    Yuanzhi He, Yuan Li, Hao Yin
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    In recent years, as giant satellite constellations grow rapidly worldwide, the co-existence between constellations has been widely concerned. In this paper, we overview the co-frequency interference (CFI) among the giant non-geostationary orbit (NGSO) constellations. Specifically, we first summarize the CFI scenario and evaluation index among different NGSO constellations. Based on statistics about NGSO constellation plans, we analyse the challenges in mitigation and analysis of CFI. Next, the CFI calculation methods and research progress are systematically sorted out from the aspects of interference risk analysis framework, numerical calculation and link construction. Then, the feasibility of interference mitigation technologies based on space, frequency domain isolation, power control, and interference alignment mitigation in the NGSO mega-constellation CFI scenario are further sorted out. Finally, we present promising directions for future research in CFI analysis and CFI avoidance.

  • FEATURE TOPIC: LEO SATELLITE ACCESS NETWORK
    Yuanyuan Yao, Dengyang Dong, Sai Huang, Chunyu Pan, Shuo Chen, Xuehua Li
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    In order to achieve dependable and efficient data acquisition and transmission in the Internet of Remote Things (IoRT), we investigate the optimization scheme of IoRT data acquisition under the unmanned aerial vehicle (UAV)-low earth orbit (LEO) satellite integrated space-air-ground network, in which the UAV acquires data from massive Internet of Things (IoT) devices in special scenarios. To combine with the actual scenario, we consider two different data types, that is, delay-sensitive data and delay-tolerant data, the transmission mode is accordingly divided into two types. For delay-sensitive data, the data will be transmitted via the LEO satellite relay to the data center (DC) in real-time. For delay-tolerant data, the UAV will store and carry the data until the acquisition is completed, and then return to DC. Due to non-convexity and complexity of the formulated problem, a multi-dimensional optimization Rate Demand based Joint Optimization (RDJO) algorithm is proposed. The algorithm first uses successive convex approximation (SCA) technology to solve the non-convexity, and then based on the block coordinate descent (BCD) method, the data acquisition efficiency is maximized by jointly optimizing UAV deployment, the bandwidth allocation of IoRT devices, and the transmission power of the UAV. Finally, the proposed RDJO algorithm is compared with the conventional algorithms. Simulation consequences demonstrate that the efficiency of IoRT data acquisition can be greatly improved by multi-parameter optimization of the bandwidth allocation, UAV deployment and the transmission power.

  • FEATURE TOPIC: LEO SATELLITE ACCESS NETWORK
    Leyi Lyu, Chenhao Qi
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    The numbers of beam positions (BPs) and time slots for beam hopping (BH) dominate the latency of LEO satellite communications. Aiming at minimizing the number of BPs subject to a predefined requirement on the radius of BP, a low-complexity user density-based BP design scheme is proposed, where the original problem is decomposed into two subproblems, with the first one to find the sparsest user and the second one to determine the corresponding best BP. In particular, for the second subproblem, a user selection and smallest BP radius algorithm is proposed, where the nearby users are sequentially selected until the constraint of the given BP radius is no longer satisfied. These two subproblems are iteratively solved until all the users are selected. To further reduce the BP radius, a duplicated user removal algorithm is proposed to decrease the number of the users covered by two or more BPs. Aiming at minimizing the number of time slots subject to the no co-channel interference (CCI) constraint and the traffic demand constraint, a low-complexity CCI-free BH design scheme is proposed, where the BPs having difficulty in satisfying the constraints are considered to be illuminated in priory. Simulation results verify the effectiveness of the proposed schemes.

  • FEATURE TOPIC: LEO SATELLITE ACCESS NETWORK
    Yongpeng Shi, Jiajia Liu, Jiadai Wang, Yijie Xun
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    The ultra-dense low earth orbit (LEO) integrated satellite-terrestrial networks (UDLEO-ISTN) can bring lots of benefits in terms of wide coverage, high capacity, and strong robustness. Meanwhile, the broadcasting and open natures of satellite links also reveal many challenges for transmission security protection, especially for eavesdropping defence. How to efficiently take advantage of the LEO satellite's density and ensure the secure communication by leveraging physical layer security with the cooperation of jammers deserves further investigation. To our knowledge, using satellites as jammers in UDLEO-ISTN is still a new problem since existing works mainly focused on this issue only from the aspect of terrestrial networks. To this end, we study in this paper the cooperative secrecy communication problem in UDLEO-ISTN by utilizing several satellites to send jamming signal to the eavesdroppers. An iterative scheme is proposed as our solution to maximize the system secrecy energy efficiency (SEE) via jointly optimizing transmit power allocation and user association. Extensive experiment results verify that our designed optimization scheme can significantly enhance the system SEE and achieve the optimal power allocation and user association strategies.

  • FEATURE TOPIC: LEO SATELLITE ACCESS NETWORK
    Tianyu Zhang, Hewu Li, Jun Liu, Lu Lu, Qian Wu, Shaowen Zheng, Zeqi Lai, Yuanjie Li
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    The gradual deployment of Low-Earth Orbit (LEO) mega constellations with inter-satellite links (ISLs) promises ubiquitous, low-latency, and high-throughput satellite network services. However, networked LEO satellites with ISLs are also at risk of routing attacks such as hijacking. Existing defenses against route hijacking in terrestrial networks can hardly work for the LEO satellite network due to its high spatiotemporal dynamics. To deal with it, we propose RPD, a high-risk routing path detection method for LEO mega-constellation networks. RPD detects abnormal high-risk LEO network paths by checking the consistency between the path delay and the geographical distance. This is efficiently achieved by combining in-band measurements and out-of-band statistical processing to detect the anomaly of the clustering feature in the reference delay matrix. RPD avoids the recalculation of the header cryptographic marks when the handover occurs, thus greatly reducing the cost and improving the performance of high-risk path detection. Experiments showed that the proposed RPD mechanism achieves an average detection accuracy of 91.64% under normal network conditions, and maintain about 89% even when congestion occurs in multiple areas of the network and measurement noise is considered. In addition, RPD does not require any cryptographic operation on the intermediate node, only minimal communication cost with excellent scalability and deployability.

  • FEATURE TOPIC: LEO SATELLITE ACCESS NETWORK
    Xin Xu, Jun Cai, Aijun Liu, Chaoying Dong, Chen Han
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    Routing algorithms in satellite constellation networks usually make use of the local state information to adapt to the topology and traffic dynamics, since it’s difficult to obtain the global states in time due to the spatial large-scale feature of constellation networks. Furthermore, they use different range of local states and give these states distinct weights. However, the behind design criterion is ambiguous and often based on experience. This paper discusses the problem from the perspective of complex network. A universal local-state routing model with tunable parameters is presented to generalize the common characteristics of local-state routing algorithms for satellite constellation networks. Based on this, the impacts of local-state routing algorithms on performance and the correlation between routing and traffic dynamics are analyzed in detail. Among them, the tunable parameters, the congestion propagation process, the critical packet sending rate, and the network robustness are discussed respectively. Experimental results show that routing algorithms can achieve a satisfactory performance by maintaining a limited state awareness capability and obtaining the states in a range below the average path length. This provides a valuable design basis for routing algorithms in satellite constellation networks.

  • FEATURE TOPIC: LEO SATELLITE ACCESS NETWORK
    Mai Yang, Qi Zhang, Haipeng Yao, Ran Gao, Xiangjun Xin, Feng Tian, Weiying Feng, Dong Chen, Fu Wang, Qinghua Tian, Jinxi Qian
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    With the development of satellite communication, in order to solve the problems of shortage of on-board resources and refinement of delay requirements to improve the communication performance of satellite optical networks, this paper proposes a bee colony optimization algorithm for routing and wavelength assignment based on directional guidance (D-BCO-RWA) in satellite optical networks. In D-BCO-RWA, directional guidance based on relative position and link load is defined, and then the link cost function in the path search stage is established based on the directional guidance factor. Finally, feasible solutions are expanded in the global optimization stage. The wavelength utilization, communication success probability, blocking rate, communication hops and convergence characteristic are simulated. The results show that the performance of the proposed algorithm is improved compared with existing algorithms.

  • FEATURE TOPIC: LEO SATELLITE ACCESS NETWORK
    Laiding Zhao, Xun Zhu, Gengxin Zhang, Zhaowen Wang
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    The main geolocation technology currently used in COSPAS-SARSAT system is TDOA/FDOA or three-star TDOA, the principle is to determine the location of the signal source by using the difference in arrival time and frequency of the wireless signal between different receivers. Therefore, ground monitoring stations need to be equipped with more than two antenna receiving stations, and multiple satellites should be able to simultaneously relay the distress signal from the target source in order to achieve the geolocation function. However, when the ground receiving system has only one antenna receiving station, or the target source is in a heavily obscured environment, the ground side is unable to receive the forwarded signals from multiple satellites at the same time, which will make it impossible to locate. To address these problems, in this paper, a time-sharing single satellite geolocations method based on different orbits is proposed for the first time. This method uses one or several low-earth orbit satellites (LEO) and medium-earth orbit satellites (MEO) in the visible area, and the receiving station only needs one pair of receiving antennas to complete the positioning. It can effectively compensate for the shortcomings of the traditional TDOA using the same moment and have better positioning accuracy compared with the single satellite in the same orbit. Due to the limited experimental conditions, this paper tests the navigation satellite using different orbit time-sharing single satellite geolocations, and proves that the positioning method has high positioning accuracy and has certain promotion and application value.

  • COVER PAPER
  • COVER PAPER
    Zan Li, Jia Shi, Chao Wang, Danyang Wang, Xiaomeng Li, Xiaomin Liao
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    Extensive research attentions have been devoted to studying cooperative cognitive radio networks (CCRNs), where secondary users (SU) providing cooperative transmissions can be permitted by primary users (PU) to use spectrum. In order to maximize SU’s utility, SU may transmit its own information during the period of cooperative transmission, which stimulates the use of covert transmission against PU’s monitoring. For this sake, this article reviews the motivations of studying covert communications in CCRN. In particular, three intelligent covert transmission approaches are developed for maximizing SU’s utility in CCRNs, namely, intelligent parasitic covert transmission (IPCT), intelligent jammer aided covert transmission (IJCT) and intelligent reflecting surface assisted covert transmission (IRSC). Further, some raw performance evaluations are discussed, and a range of potential research directions are also provided.

  • COMMUNICATIONS THEORIES & SYSTEMS
  • COMMUNICATIONS THEORIES & SYSTEMS
    Musbahu Mohammed Adam, Liqiang Zhao, Kezhi Wang, Zhu Han
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    In recent years, the exponential proliferation of smart devices with their intelligent applications poses severe challenges on conventional cellular networks. Such challenges can be potentially overcome by integrating communication, computing, caching, and control (i4C) technologies. In this survey, we first give a snapshot of different aspects of the i4C, comprising background, motivation, leading technological enablers, potential applications, and use cases. Next, we describe different models of communication, computing, caching, and control (4C) to lay the foundation of the integration approach. We review current state-of-the-art research efforts related to the i4C, focusing on recent trends of both conventional and artificial intelligence (AI)-based integration approaches. We also highlight the need for intelligence in resources integration. Then, we discuss the integration of sensing and communication (ISAC) and classify the integration approaches into various classes. Finally, we propose open challenges and present future research directions for beyond 5G networks, such as 6G.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Xiaorong Zhu, Lingyu Zhao, Jiaming Cao, Jianhong Cai
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    Fault diagnosis of 5G networks faces the challenges of heavy reliance on human experience and insufficient fault samples and relevant monitoring data. The digital twin technology can realize the interaction between virtual space and physical space through the fusion of model and data, providing a new paradigm for fault diagnosis. In this paper, we first propose a network digital twin model and apply it to 5G network diagnosis. We then use an improved Average Wasserstein GAN with Gradient Penalty (AWGAN-GP) method to discover and predict failures in the twin network. Finally, we use XGBoost algorithm to locate the faults in physical network in real time. Extensive simulation results show that the proposed approach can significantly increase fault prediction and diagnosis accuracy in the case of a small number of labeled failure samples in 5G networks.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Ge Song, Xiaojie Fang, Xuejun Sha
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    In this paper, we propose an extended hybrid carrier system based on the weighted fractional Fourier transform to ensure the reliability of wireless communication. The proposed scheme improves the dispersion and compensation capabilities of the hybrid carrier system for channel fading through the design of the signal power distribution, which has greatly reduced the probability of high-power distortion of the signal and improved the bit error rate performance as a result. Theoretical analysis has shown the superiority of the extended hybrid carrier system. With a lower cost of computational complexity increment, the proposed scheme obtains a performance improvement without occupying additional time-frequency physical resources. Compared with the existing hybrid carrier scheme, numerical simulation results have shown that the proposed extended hybrid carrier scheme has better anti-fading performance under the doubly-selective channel and improves the reliability of the wireless communication system effectively.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Jinhao Du, Tao Yang, Sheping Shi, Xue Chen
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    Large-scale dense wavelength division multiplexing (DWDM) multi-channel performance monitoring is one of the indispensable technologies for the flexible optical networks. The existing Label-based monitoring scheme requires expensive optical demultiplexing components/equipment to avoid the influence of stimulated Raman scattering (SRS), which is not only costly and bulky, but also could not monitor the wavelength channels simultaneously. In this paper, a low-cost, high-accuracy monitoring scheme based on Optical Label Method is proposed for DWDM networks, where the optical channel power and node identification (ID), as the main monitoring targets that both can indicate or evaluate the channel connection status, could be efficiently monitored. In the scheme, a novel digital signal processing (DSP) method of SRS mitigation is proposed and demonstrated, and an asynchronous code-division multiple access (A-CDMA) based digital label encoding and decoding method is adopted to distinguish the node ID so that channel initial added node can be accurately verified, thereby wavelength connection status can be reliably monitored by combining the channel power and node ID information. The simulation results show that each wavelength channel power and node ID can be accurately monitored only by low bandwidth photoelectric detector (PD) under the condition of 80 wavelengths and 10 spans at C-band.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Wenwei Yue, Peiang Zuo, Wengang Li, Yao Zhang, Yunfeng Zhang, Changle Li, Jun Huang
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    The foundation of ad hoc networks lies in the guarantee of continuous connectivity. However, critical nodes, whose failure can easily destroy network connectivity, will influence the ad hoc network connectivity significantly. To protect the network efficiently, critical nodes should be identified accurately and rapidly. Unlike existing critical node identification methods for unknown topology that identify critical nodes according to historical information, this paper develops a critical node identification method to relax the prior topology information condition about critical nodes. Specifically, we first deduce a theorem about the minimum communication range for a node through the number of nodes and deployment ranges, and prove the universality of the theorem in a realistic two-dimensional scenario. After that, we analyze the relationship between communication range and degree value for each node and prove that the greater number of nodes within the communication range of a node, the greater degree value of nodes with high probability. Moreover, we develop a novel strategy to improve the accuracy of critical node identification without topology information. Finally, simulation results indicate the proposed strategy can achieve high accuracy and low redundancy while ensuring low time consumption in the scenarios with unknown topology information in ad hoc networks.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Xiaohan Qi, Jianxiao Xie
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    In this paper, a Millimeter wave (mmWave) beam tracking problem is studied in orthogonal time frequency space (OTFS) systems. Considering the nonlinearity of beamforming and the constraints of existing Kalman-filtering based beam tracking schemes, we propose a novel Cubature Kalman Filter (CKF) framework tracking the channel state information (CSI) to manage the challenge of high-speed channel variation in single-user moving scene for OTFS systems. Aiming for low complexity for mobile settings, this paper trains only one beam pair to track a path to maintain the reliable communication link in the analog beamforming architecture. Simulation results show that our proposed method has better tracking performance to improve the accuracy of the estimated beam angle compared with prior work.
  • EMERGING TECHNOLOGIES & APPLICATIONS
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Tao Peng, Chao Yang, Peiliang Zuo, Xinyue Wang, Rongrong Qian, Wenbo Wang
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    Spectrum prediction plays an important role for the secondary user (SU) to utilize the shared spectrum resources. However, currently utilized prediction methods are not well applied to spectrum with high burstiness, as parameters of prediction models cannot be adjusted properly. This paper studies the prediction problem of bursty bands. Specifically, we first collect real WiFi transmission data in 2.4GHz Industrial, Scientific, Medical (ISM) band which is considered to have bursty characteristics. Feature analysis of the data indicates that the spectrum occupancy law of the data is time-variant, which suggests that the performance of commonly used single prediction model could be restricted. Considering that the match between diverse spectrum states and multiple prediction models may essentially improve the prediction performance, we then propose a deep-reinforcement learning based multilayer perceptron (DRL-MLP) method to address this matching problem. The state space of the method is composed of feature vectors, and each of the vectors contains multi-dimensional feature values. Meanwhile, the action space consists of several multilayer perceptrons (MLPs) that are trained on the basis of multiple classified data sets. We finally conduct experiments with the collected real data and simulations with generated data to verify the performance of the proposed method. The results demonstrate that the proposed method significantly outperforms the state-of-the-art methods in terms of the prediction accuracy.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Yan Zhao, Shichuan Chen, Tao Chen, Weiguo Shen, Shilian Zheng, Zhijin Zhao, Xiaoniu Yang
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    Radio modulation classification has always been an important technology in the field of communications. The difficulty of incremental learning in radio modulation classification is that learning new tasks will lead to catastrophic forgetting of old tasks. In this paper, we propose a sample memory and recall framework for incremental learning of radio modulation classification. For data with different signal-to-noise ratios, we use a partial memory strategy by selecting appropriate samples for memorizing. We compare the performance of our proposed method with three baselines through a large number of simulation experiments. Results show that our method achieves far higher classification accuracy than fine-tuning method and feature extraction method. Furthermore, it performs closely to joint training method which uses all old data in terms of classification accuracy which validates the effectiveness of our method against catastrophic forgetting.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Nong Qu, Chao Wang, Zuxing Li, Fuqiang Liu
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    In highly dynamic and heterogeneous vehicular communication networks, it is challenging to efficiently utilize network resources and ensure demanding performance requirements of safety-related applications. This paper investigates machine-learning-assisted transmission design in a typical multi-user vehicle-to-vehicle (V2V) communication scenario. The transmission process proceeds sequentially along the discrete time steps, where several source nodes intend to deliver multiple different types of messages to their respective destinations within the same spectrum. Due to rapid movement of vehicles, real-time acquirement of channel knowledge and central coordination of all transmission actions are in general hard to realize. We consider applying multi-agent deep reinforcement learning (MADRL) to handle this issue. By transforming the transmission design problem into a stochastic game, a multi-agent proximal policy optimization (MAPPO) algorithm under a centralized training and decentralized execution framework is proposed such that each source decides its own transmission message type, power level, and data rate, based on local observations of the environment and feedback, to maximize its energy efficiency. Via simulations we show that our method achieves better performance over conventional methods.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Xinyu Fan, Jie Hu, Kun Yang
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    Terminal devices deployed in outdoor environments are facing a thorny problem of power supply. Data and energy integrated network (DEIN) is a promising technology to solve the problem, which simultaneously transfers data and energy through radio frequency signals. State-of-the-art researches mostly focus on theoretical aspects. By contrast, we provide a complete design and implementation of a fully functioning DEIN system with the support of an unmanned aerial vehicle (UAV). The UAV can be dispatched to areas of interest to remotely recharge batteryless terminals, while collecting essential information from them. Then, the UAV uploads the information to remote base stations. Our system verifies the feasibility of the DEIN in practical applications.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Selvakumari P, Chinnasamy A, Sree Rathna Lakshmi NVS, Sheela D
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    Road Side Units (RSUs) are the essential component of vehicular communication for the objective of improving safety and mobility in the road transportation. RSUs are generally deployed at the roadside and more specifically at the intersections in order to collect traffic information from the vehicles and disseminate alarms and messages in emergency situations to the neighborhood vehicles cooperating with the network. However, the development of a predominant RSUs placement algorithm for ensuring competent communication in VANETs is a challenging issue due to the hindrance of obstacles like water bodies, trees and buildings. In this paper, Ruppert's Delaunay Triangulation Refinement Scheme (RDTRS) for optimal RSUs placement is proposed for accurately estimating the optimal number of RSUs that has the possibility of enhancing the area of coverage during data communication. This RDTRS is proposed by considering the maximum number of factors such as global coverage, intersection popularity, vehicle density and obstacles present in the map for optimal RSUs placement, which is considered as the core improvement over the existing RSUs optimal placement strategies. It is contributed for deploying requisite RSUs with essential transmission range for maximal coverage in the convex map such that each position of the map could be effectively covered by at least one RSU in the presence of obstacles. The simulation experiments of the proposed RDTRS are conducted with complex road traffic environments. The results of this proposed RDTRS confirmed its predominance in reducing the end-to-end delay by 21.32%, packet loss by 9.38% with improved packet delivery rate of 10.68%, compared to the benchmarked schemes.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    En Yuan, Peng Liu, Weiwei Chen, Rui Wang, Bing Xu, Wenyu Zhang, Yanqin Tang
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    Global navigation satellite system has been widely used, but it is vulnerable to jamming. In military satellite communications, frequency hopping (FH) signal is usually used for anti-jamming communications. If the FH signal can be used in satellite navigation, the anti-jamming ability of satellite navigation can be improved. Although a recently proposed time-frequency matrix ranging method (TFMR) can use FH signals to realize pseudorange measurement, it cannot transmit navigation messages using the ranging signal which is crucial for satellite navigation. In this article, we propose dual-tone binary frequency shift keying-based TFMR (DBFSK-TFMR). DBFSK-TFMR designs an extended time-frequency matrix (ETFM) and its generation algorithm, which can use the frequency differences in different dual-tone signals in ETFM to modulate data and eliminate the negative impact of data modulation on pseudorange measurement. Using ETFM, DBFSK-TFMR not only realizes the navigation message transmission but also ensures the precision and unambiguous measurement range of pseudorange measurement. DBFSK-TFMR can be used as an integrated solution for anti-jamming communication and navigation based on FH signals. Simulation results show that DBFSK-TFMR has almost the same ranging performance as TFMR.