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  • Shuiling Cao, Gongpu Wang, Jie Gao, Lei Kuang, Chintha Tellambura
    Received: 2022-12-23; Revised: 2023-11-10; Accepted: 2024-03-12; Online: 2024-04-15
    Existing orthogonal space-time block coding (OSTBC) schemes for backscatter communication systems cannot achieve a full transmission code rate when the tag is equipped with more than two antennas. In this paper, we propose a quasi-orthogonal space-time block code (QOSTBC) that can achieve a full transmission code rate for backscatter communication systems with a four-antenna tag and then extend the scheme to support tags with 2^i antennas. Specifically, we first present the system model for the backscatter system. Next, we propose the QOSTBC scheme to encode the tag signals. Then, we provide the corresponding maximum likelihood detection algorithms to recover the tag signals. Finally, simulation results are provided to demonstrate that our proposed QOSTBC scheme and the detection algorithm can achieve a better transmission code rate or symbol error rate performance for backscatter communication systems compared with benchmark schemes.
  • Kaijun Cheng, Xuming Fang
    Received: 2023-06-01; Revised: 2023-12-24; Accepted: 2024-03-12; Online: 2024-04-15
    With miscellaneous applications generated in vehicular networks, the computing performance cannot be satisfied owing to vehicles’ limited processing capabilities. Besides, the low-frequency (LF) band cannot further improve network performance due to its limited spectrum resources. High-frequency (HF) band has plentiful spectrum resources which is adopted as one of the operating bands in 5G. To achieve low latency and sustainable development, a task processing scheme is proposed in dual-band cooperation-based vehicular network where tasks are processed at local side, or at macro-cell base station or at road side unit through LF or HF band to achieve stable and high-speed task offloading. Moreover, a utility function including latency and energy consumption is minimized by optimizing computing and spectrum resources, transmission power and task scheduling. Owing to its non-convexity, an iterative optimization algorithm is proposed to solve it. Numerical results evaluate the performance and superiority of the scheme, proving that it can achieve efficient edge computing in vehicular networks.
  • Zehua Chen, Zhili Wang, Shaoyong Guo, XingyuChen
    Received: 2023-06-15; Revised: 2023-10-18; Accepted: 2024-03-15; Online: 2024-04-15
    Time-Sensitive Network (TSN) has been widely used in industrial Internet and automatic vehicle fields. However, nowadays performance of TSN in the network with large-scale and complex business is not satisfactory, and it will encounter the bottleneck when scheduling a large number of period-incompatible TSN traffic. In this paper, we propose an offline time-triggered (TT) flow routing and no-wait scheduling method using period-compatibility aware flow partitioning and iterated integer linear programming (ILP). The proposed method can split TT flows into several groups with high relative period-compatibility and then schedule each flow group iteratively and greedily in order to achieve better scheduling performance. We compare the scheduling performance of different type and scale of TT flows of our proposed method with two baseline methods DASP and RSP and the result shows that our method can achieve higher scheduling success rate (about 11% increase at most) and bandwidth utilization rate with acceptable computational time cost.
  • Zhengbin Zhu, Qinrang Liu, Dongpei Liu, Chenyang Ge
    Received: 2023-08-11; Revised: 2024-01-23; Accepted: 2024-03-12; Online: 2024-04-15
    As an emerging networking paradigm, Software-Defined Networking (SDN) separates the control plane and data plane to achieve flexible network management. However, one of the crucial challenges is multi-controller placement problem (MCPP) for hierarchical SDN.In this paper, we first analyze the existing reliable problems and formulate the Hierarchical Reliable Multi-Controller Placement Problem(HRM-CPP). To this end, we propose a new multi-controller placement architecture and scheme to solve the HRM-CPP. Specifically, we first propose a reliable domain partition algorithm R-Louvain to improve the reliable connections between domains. Next, we improve the Non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ) to make a satisfactory decision on local controller placement. Finally, we innovatively propose the Adaptive Granular Global Search (AGGS) algorithm to search the optimal location for global controller. We conduct simulations with real network topologies, and results show that RLNA(Reliable algorithm based on Louvain, NSGA-Ⅱand AGGS) outperforms related schemes in terms of reliability, average latency and the load of global controller, which is conducive to the solution of HRM-CPP.
  • Aleksandra S. Panajotović, Jelena A. Anastasov, Dejan N. Milić, Daniela M. Milović, Nenad D. Milošević
    Received: 2022-09-07; Revised: 2023-12-11; Accepted: 2024-01-15; Online: 2024-04-15
    In this paper, we present an analytical framework for a two-user nonorthogonal multiple access (NOMA) system performance over composite alpha-F fading channels. This analysis is of importance due to the fact that NOMA has been seen as a candidate of Beyond 5G wireless communication in which alpha-F is the best fitting distribution. Specifically, we derive the exact outage probability and ergodic capacity expressions accompanied with asymptotic/approximated expressions to obtain quicker insight into performance metrics. The influence of various channel/system parameters on the overall system performance improvement is analysed. The accuracy of the analytical results is confirmed by extensive simulations.
  • Jianxin Huang, Bo Yu, Jinshu Su, Lei Zhou, Runhao Liu
    Received: 2023-09-05; Revised: 2024-01-23; Accepted: 2024-03-20; Online: 2024-04-15
    Statefulness abnormality is a significant factor leading to network protocol vulnerabilities. Usually, the external protocol state can be reflected by the internal program state, so the statefulness abnormalities can be detected according to the inconsistency and disharmony of stateful variables in the program. However, current stateful fuzzers of network protocols inspecting the runtime stateful variables only focus on exploring the protocol state space and program paths, without detecting statefulness abnormalities and analyzing the logical errors beyond system crashes. To address this challenge, we propose a novel approach for assisting in the analysis of protocol vulnerabilities by reconstructing a model for statefulness abnormality in network protocols. Our approach develops a method for automated computing the runtime states of a program during replay analysis through the use of stateful variables. Subsequently, we establish detection rules and design a heuristic algorithm for diagnosing protocol, and implement a prototype system. Experimental results from testing 9 protocol software programs demonstrate that our approach can efficiently detect statefulness abnormalities, with an average precision of 80.45\%. Furthermore, the prototype system has been validated to effectively identify statefulness abnormalities in complex execution paths through detection of several typical known vulnerabilities in real-world software. Our work demonstrates that rule-based detection can effectively address this problem, providing valuable insights for future research.
  • Fei Zheng, He Li,Shaoyong Guo, Yu Hu,ChaoWang, Yaolong Ning
    Received: 2023-03-17; Revised: 2023-11-13; Accepted: 2024-03-06; Online: 2024-04-15
    Cooperative edge computing can provide low-latency services in Low Earth Orbit (LEO) satellite networks. Due to load limitations, satellites equipped with lightweight Multi-access Edge Computing (MEC) servers cannot process massive amounts of computing tasks. Cooperative offloading between adjacent satellites is an effective means of solving the problem. This paper proposes a cooperative edge computing offloading strategy based on deep Q-network (DQN) algorithm to achieve spaceborne MEC server load balancing. To minimize the delay and energy consumption, we transform the computation offloading optimization into a mixed integer nonlinear programming (MINLP) problem with the constraints of battery capacity of terminals and the computation capability of LEO satellites. The DQN algorithm can adapt to rapid environment changes due to the high mobility of satellites. We use the DQN algorithm to solve the MINLP problem. In the simulation, the numerical results show that the proposed offloading strategy effectively reduces the delay and energy consumption.
  • Zilu Gao, Shaohui Sun
    Received: 2023-11-15; Revised: 2024-03-07; Accepted: 2024-03-29; Online: 2024-04-15
    Reconfigurable intelligent surface (RIS) is an innovative technology in increasing data rates for the next-generation wireless network. Unlike most existing works, which assumed that each reflecting element of RIS has the constant reflection amplitude, we consider a practical reflection model and propose a joint active and passive beamforming design to maximize the average sum-rate in a multi-user system. Specifically, the original problem is transformed to the minimization of weighted mean-square error (MSE), and an iterative algorithm is proposed to design transmit beamforming and RIS-based passive beamforming. Finally, simulation results are presented to show that the proposed joint beamforming design is effective and the proposed reflection coefficients design has better performance than the existing algorithm. Moreover, the assumption of the ideal reflection model will result in performance loss, and low reflection amplitude caused by energy loss in reflecting elements will reduce the system performance.
  • Yuhao Wang, Chuan Xu, Lisu Yu, Xinxin Lv, Junyuan Chen, Zhenghai Wang
    Received: 2023-08-16; Revised: 2024-01-04; Accepted: 2024-02-27; Online: 2024-03-15
    Sparse code multiple access (SCMA) is a non-orthogonal multiple access (NOMA) scheme based on joint modulation and spread spectrum coding. It is ideal for future communication networks with a massive number of nodes due to its ability to handle user overload. Introducing SCMA into visible light communication (VLC) systems can improve the data transmission capability of the system. However, designing a suitable codebook becomes a challenging problem when addressing the demands of massive connectivity scenarios. Therefore, this paper proposes a low-complexity design method for high-overload codebooks based on the minimum bit error rate (BER) criterion. Firstly, this paper constructs a new codebook with parameters based on the symmetric mother codebook structure by allocating the codeword power so that the power of each user codebook is unbalanced; then, the BER performance in the visible light communication system is optimized to obtain specific parameters; finally, the successive interference cancellation (SIC) detection algorithm is used at the receiver side. Simulation results show that the method proposed in this paper can converge quickly by utilizing a relatively small number of detection iterations. This can simultaneously reduce the complexity of design and detection, outperforming existing design methods for massive SCMA codebooks.
  • Huanyu Guo, Donghua Yang, Hong Gao
    Received: 2023-04-15; Revised: 2023-11-20; Accepted: 2024-02-27; Online: 2024-03-15
    This paper studies the routing problem in ambient backscatter wireless sensor networks (AB-WSNs) using heuristic stateless approaches. In AB-WSNs, sensor nodes employing ambient backscatter technology communicate by backscattering RF signals instead of actively generating them. These nodes operate without batteries and being powered only by these RF signals. This leads to a dynamic topology and intermittent connections among sensor nodes for AB-WSNs, resulting in increased delays in data routing and posing challenges to the widespread deployment of AB-WSNs. To address this issue, we first introduce a network model incorporating a channel competition mechanism and present Minimum Data Delay Routing Problem in AB-WSNs. We then propose three heuristic distributed stateless routing algorithms, allowing node to relay data using only information about its immediate neighbors without looking up a route table, for general and near scenarios. We analyze the time complexity and approximate ratios for the proposed algorithms. In different scenarios under various conditions, the proposed heuristic algorithm, when compared to the baseline strategies, improves the data success rate by at least 10% and up to 100%, while reducing the data delay by at most 30%.
  • Zixv Su, Changzhen Li, Wei Chen, Quan Yu
    Received: 2023-09-01; Revised: 2023-11-30; Accepted: 2024-02-27; Online: 2024-03-15
    Intelligent reflecting surface (IRS) is regarded as a key and emerging technology to substantially improve communication performance. In this paper, an IRS-aided unmanned aerial vehicle (UAV)-to-ship geometry-based channel model (GBSM) for multiple-input multiple-output (MIMO) communication systems is proposed. Two different cylinder models are combined to model an inland river scattering scenario. A two-state Markov process is introduced to simulate the dynamic properties of multipath components (MPCs). In addition, water fluctuation and duct propagation are both introduced to characterize the inland river communication characteristics. The corresponding statistical properties such as space-time-frequency correlation function (STF-CF), Doppler power spectrum density (PSD), quasi-stationary interval, level crossing rate (LCR), average fading duration (AFD), and channel capacity are derived and analyzed. It is found that time evolution has a prominent influence on properties in time domain. Additionally, different trajectories of the UAV lead to different changing trends of channel properties. Channel parameters such as the number of reflection units, the Ricean factor, and the height of the IRS also have significant impacts on statistical properties. These observations and analyses can provide references to design an optimized IRS-aided UAV-to-ship MIMO system for inland river scenarios.
  • Wanfa Chen, Qingan Zheng, Shuzhen Chen, Hongyi Fu, Liang Chen
    Received: 2023-11-20; Revised: 2024-01-03; Accepted: 2024-01-23; Online: 2024-03-15
    In recent years, blockchain technology integration and application has gradually become an important driving force for new technological innovation and industrial transformation. While blockchain technology and applications are developing rapidly, the emerging security risks and obstacles have gradually become prominent. Attackers can still find security issues in blockchain systems and conduct attacks, causing increasing losses from network attacks every year. In response to the current demand for blockchain application securitydetection and assessment in all industries, and the insufficient coverage of existing detection technologies such as smart contract detectiontechnology, this paper proposes a blockchain core technology security assessment system model, and studies the relevant detection and assessment key technologies and systems. A security assessment scheme based on a smart contract and consensus mechanism detection scheme is designed. And the underlying blockchain architecture supports the traceability of detection results using super blockchains. Finally, the functionality and performance of the system were tested, and the test results show that the model and solutions proposed in this paper have good feasibility.
  • Yongjie Yang, Yajing Hao, Qiang Sun, Xiaomin Chen, Jiayi Zhang
    Received: 2023-07-31; Revised: 2024-01-05; Accepted: 2024-02-27; Online: 2024-03-15
    This paper presents a novel cooperative network architecture that utilizes reconfigurable intelligent surfaces (RIS) to assist non-orthogonal multiple access (NOMA) communications between two users with similar channel gains. We derive a strict upper bound of the ergodic achievable rate by using Jensen's inequality and the central limit theorem. Subsequently, we investigate the impact of the total number of RIS elements on the sum-rate of RIS-aided NOMA (RIS-NOMA) and RIS-aided time division multiple access (RIS-TDMA) systems. We also determine the minimum number of RIS elements required for RIS-NOMA to achieve a higher sum-rate. Finally, we propose an iterative fairness optimization algorithm that addresses fairness issues in the considered system by adjusting the power allocation factors of the two users.
  • Zhiqing Wei, Wangjun Jiang, Meichen Lai, Zhiyong Feng
    Received: 2023-03-15; Revised: 2023-11-06; Accepted: 2024-02-27; Online: 2024-03-15
    Anti-collision is essential for unmanned aerial vehicle (UAV) swarm to survive in harsh environments. The traditional UAV swarm with separated sensing and communication has the disadvantages of low sensing accuracy and slow target identification, which cannot meet the requirements of anti-collision. To alleviate this problem, we propose the improved local and global anti-collision scheme using integrated sensing and communication (ISAC) technology. In terms of local anti-collision, we adopt the extended Kalman filter (EKF) algorithm to improve the accuracy of target sensing by fusing the communication localization information and sensing information. Moreover, we propose a fast target identification mechanism using ISAC signals. With higher sensing accuracy and faster sensing speed, smaller minimum safety distance can be obtained, which is a typical performance metric of anti-collision. Simulation results show that, assisted by the ISAC technology, the sensing accuracy is improved by 24.2\%, the sensing speed is increased by 50\% and the minimum safety distance is reduced by 38.73\%. In terms of global anti-collision, we propose an improved rapidly-exploring random tree* (RRT*) algorithm in the process of path planning. Simulation results show that ISAC technology can effectively improve the performance of global anti-collision.
  • Guolin Chen, Yiqin Deng, Xiaoxia Huang, Yuguang Fang
    Received: 2023-12-21; Revised: 2024-01-28; Accepted: 2024-02-27; Online: 2024-03-15
    The deployment of multiple intelligent reflecting surfaces (IRSs) in blockage-prone millimeter wave (mmWave) communication networks have garnered considerable attention lately. Despite the remarkably low circuit power consumption per IRS element, the aggregate energy consumption becomes substantial if all elements of an IRS are turned on given a considerable number of IRSs, resulting in lower overall energy efficiency (EE). To tackle this challenge, we propose a flexible and efficient approach that individually controls the status of each IRS element. Specifically, the network EE is maximized by jointly optimizing the associations of base stations (BSs) and user equipments (UEs), transmit beamforming, phase shifts of IRS elements, and the associations of individual IRS elements and UEs. The problem is efficiently addressed in two phases. First, the Gale-Shapley algorithm is applied for BS-UE association, followed by a block coordinate descent-based algorithm that iteratively solves the subproblems related to active beamforming, phase shifts, and element-UE associations. To reduce the tremendous dimensionality of optimization variables introduced by element-UE associations in large-scale IRS networks, we introduce an efficient algorithm to solve the associations between IRS elements and UEs. Numerical results show that the proposed elementwise control scheme improves EE by 34.24% compared to the network with IRS-all-on scheme.
  • Bin Lyu, Yining Zhang, Pengcheng Chen, Ziwei Liu, Feng Tian
    Received: 2023-09-27; Revised: 2024-01-15; Accepted: 2024-02-27; Online: 2024-03-15
    Wireless powered and backscattering mobile edge computing (WPB-MEC) network is a novel network paradigm to supply energy supplies and computing resource to wireless sensors (WSs). However, its performance is seriously affected by severe attenuations and inappropriate assumptions of infinite computing capability at the hybrid access point (HAP). To address the above issues, in this paper, we propose a simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) aided scheme for boosting the performance of WPB-MEC network under the constraint of finite computing capability. Specifically, energy-constrained WSs are able to offload tasks actively or passively from them to the HAP. In this process, the STAR-RIS is utilized to improve the quantity of harvested energy and strengthen the offloading efficiency by adapting its operating protocols. We then maximize the sum computational bits (SCBs) under the finite computing capability constraint. To handle the solving challenges, we first present interesting results in closed-form and then design a block coordinate descent (BCD) based algorithm, ensuring a near-optimal solution. Finally, simulation results are provided to confirm that our proposed scheme can improve the SCBs by 9.9 times compared to the local computing only scheme.
  • Chen Cui, Wei Xiang, Siwei Ma,Qing Guo
    Received: 2023-10-11; Revised: 2024-01-18; Accepted: 2024-02-27; Online: 2024-03-15
    Mobile communications are reaching out to every aspect of our daily life, necessitating high-efficiency data transmission and support for diverse data types and communication scenarios. Polar codes have emerged as a promising solution due to their outstanding error-correction performance and low complexity. Unequal error protection (UEP) entails non-uniform error safeguarding for distinct data segments, achieving a fine balance between error resilience and resource allocation, ultimately enhancing system performance and efficiency. In this paper, we propose a new class of UEP rateless polar codes which can support real-time communication scenarios. The codes are designed based on matrix extension of polar codes, and elegant mapping and copying operations are designed to achieve UEP property while preserving the overall performance of conventional polar codes. An excellent UEP performance is attained without significant modifications to conventional polar codes, making it straightforward for compatibility with existing polar codes. A theoretical analysis is conducted on the performance of the block error rate and throughput efficiency. To the best of our knowledge, this work represents the first theoretical performance of UEP rateless polar codes. Simulation results show that the proposed codes outperforms the existing polar coding schemes significantly both in the block error rate and throughput efficiency.
  • Xiaodong Zhang, Guochu Shou, Hongxing Li, Yaqiong Liu, Yihong Hu
    Received: 2023-08-25; Revised: 2023-12-26; Accepted: 2024-02-27; Online: 2024-03-15
    The rise of time-sensitive applications with broad geographical scope drives the development of time-sensitive networking (TSN) from intra-domain to inter-domain to ensure overall end-to-end connectivity requirements in heterogeneous deployments. When multiple TSN networks interconnect over non-TSN networks, all devices in the network need to be synchronized by sharing a uniform time reference. However, most non-TSN networks are best-effort. Path delay asymmetry and random noise accumulation can introduce unpredictable time errors during end-to-end time synchronization. These factors can degrade synchronization performance. Therefore, cross-domain time synchronization becomes a challenging issue for multiple TSN networks interconnected by non-TSN networks. This paper presents a cross-domain time synchronization scheme that follows the software-defined TSN (SD-TSN) paradigm. It utilizes a combined control plane constructed by a coordinate controller and a domain controller for centralized control and management of cross-domain time synchronization. The general operation flow of the cross-domain time synchronization process is designed. The mechanism of cross-domain time synchronization is revealed by introducing a synchronization model and an error compensation method. A TSN cross-domain prototype testbed is constructed for verification. Results show that the scheme can achieve end-to-end high-precision time synchronization with accuracy and stability.
  • Francisco R. Castillo-Soria, Sharon Macias-Velasquez, Vinoth Babu Kumaravelu, Victor Ramos, Cesar A. Azurdia-Meza
    Received: 2023-11-10; Revised: 2024-01-12; Accepted: 2024-02-27; Online: 2024-03-15
    New communication systems require high spectral and energy efficiencies to meet the growing demand for services in future networks. In this paper, an efficient multiple parallel reconfigurable intelligent surfaces (RIS)-assisted multiuser (MU) multiple input-multiple output (MIMO) double quadrature spatial modulation (DQSM) downlink transmission system is presented. In the transmitter, the proposed N-RIS-MU-MIMO-DQSM system uses a modified block diagonalization technique and a genetic algorithm (GA) to jointly design the precoding signals required at the base station (BS) and the optimal phase changes required at multiple RISs. A reduced detection complexity and an improved bit error rate (BER) performance are obtained by adding spatial modulation. The proposed system is compared under the same conditions and parameters with two reference systems considering blind and optimized RISs approaches over correlated Rayleigh fading channels. Results show that compared with a similar system that does not use RISs, the proposed system has up to 30 dB gain in BER performance. Compared with a similar system based on conventional quadrature amplitude modulation (QAM), the proposed system has gains of up to 2-3 dB in BER performance and up to 55.8% lower detection complexity for the analyzed cases.
  • Yan Lin, Zhijuan Wu, Nuoheng Peng, Tianyu Zhao, Yijin Zhang, Feng Shu, Jun Li
    Received: 2023-08-21; Revised: 2023-12-27; Accepted: 2024-02-27; Online: 2024-03-15
    The Internet of Unmanned Aerial Vehicles (I-UAVs) is expected to execute latency-sensitive tasks, but limited by co-channel interference and malicious jamming. In the face of unknown prior environmental knowledge, defending against jamming and interference through spectrum allocation becomes challenging, especially when each UAV pair makes decisions independently. In this paper, we propose a cooperative multi-agent reinforcement learning (MARL)-based anti-jamming framework for I-UAVs, enabling UAV pairs to learn their own policies cooperatively. Specifically, we first model the problem as a model-free multi-agent Markov decision process (MAMDP) to maximize the long-term expected system throughput. Then, for improving the exploration of the optimal policy, we resort to optimizing a MARL objective function with a mutual-information (MI) regularizer between states and actions, which can dynamically assign the probability for actions frequently used by the optimal policy. Next, through sharing their current channel selections and local learning experience (their soft Q-values), the UAV pairs can learn their own policies cooperatively relying on only preceding observed information and predicting others' actions. Our simulation results show that for both sweep jamming and Markov jamming patterns, the proposed scheme outperforms the benchmarkers in terms of throughput, convergence and stability for different numbers of jammers, channels and UAV pairs.
  • Xin Dong , Stefanos Bakirtzis, Jiliang Zhang, Jie Zhang
    Received: 2023-05-09; Revised: 2023-10-30; Accepted: 2023-12-18; Online: 2024-03-15
    The utilization of millimeter-wave frequencies and cognitive radio (CR) are promising ways to increase the spectral efficiency of wireless communication sys tems. However, conventional CR spectrum sensing techniques entail sampling the received signal at a Nyquist rate, and they are not viable for wideband sig nals due to their high cost. This paper expounds on how sub-Nyquist sampling in conjunction with deep learning can be leveraged to remove this limitation. To this end, we propose a multi-task learning (MTL) framework using convolutional neural networks for the joint inference of the underlying narrowband sig nal number, their modulation scheme, and their loca tion in a wideband spectrum. We demonstrate the ef fectiveness of the proposed framework for real-world millimeter-wave wideband signals collected by physi cal devices, exhibiting a 91.7% accuracy in the joint inference task when considering up to two narrow band signals over a wideband spectrum. Ultimately, the proposed data-driven approach enables on-the-fly wideband spectrum sensing, combining accuracy, and computational efficiency, which are indispensable for CR and opportunistic networking.
  • Lihua Pang, Yue Wang, Yang Zhang, Yiteng Zhang, Yijian Chen, Anyi Wang
    Received: 2023-10-26; Revised: 2024-01-18; Accepted: 2024-02-27; Online: 2024-03-15
    As emerging services continue to be explored, indoor communications geared towards different user requirements will face severe challenges such as larger penetration losses and more critical multipath issues, leading to difficulties in achieving flexible coverage. In this paper, we introduce transmissive reconfigurable intelligent surfaces (RISs) as intelligent passive auxiliary devices into indoor scenes, replacing conventional ultra-dense small cell and relay forwarding approaches to address these issues at low deployment and operation costs. Specifically, we study the optimization design of active and passive beamforming for the transmissive RISs-aided indoor multi-user downlink communication systems. This involves considering more realistic indoor congestion modeling and near-field propagation characteristics. The goal of our optimization is to minimize the total transmit power at the access point (AP) for different user service requirements, including quality-of-service (QoS) and wireless power transfer (WPT). Due to the non-convex nature of the optimization problem, adaptive penalty coefficients are imported to solve it alternatively with closed-form solutions for both active and passive beamforming. Simulation results demonstrate that the use of transmissive RISs is indeed an efficient way to achieve flexible coverage in indoor scenarios. Furthermore, the proposed optimization algorithm has been proven to be effective and robust in achieving energy-saving transmission.
  • Yaoping Zeng, Zhiyuan Ge, Zixu Wang, Weiwei Jiang, Shisen Chen
    Received: 2023-04-28; Revised: 2023-07-24; Accepted: 2024-02-27; Online: 2024-03-15
    Mobile edge computing (MEC) is a promising technology to improve the quality of ser_x0002_vice of user equipment (UE) by offloading their computation-intensive and delay-sensitive tasks to the wireless network edge. In this paper, we consider a hybrid NOMA-based system with one MEC server and multiple users, causing a marked increase in spectral efficiency of UEs by leveraging non-orthogonal multiple access (NOMA) technology. First, using cognitive radio (CR) technology, we divide the UEs into primary users (PUs) and secondary users (SUs), then we formulate a Stackelberg game in which the PUs are the leader and the SUs are the follower, with the aim to minimize the PUs’ energy consumption and SUs’ overall delay. To tackle the follower delay-minimization problem, we propose a deep reinforcement-learning approach to address transmit-power control problem, then a convex method is applied to overcome offloading decision and computational-resource-allocation problems of the SUs. In order to overcome the leader energyconsumption-optimization problem, we use an iterative algorithm based on the Karush-Kuhn-Tucker conditions to figure out the problems of task offloading decisions, transmit-power control, computational resources, and sub-channel allocation. Eventually, both the leader-tier and follower-tier subgames are proved to be exact potential games with at least one Nash equilibrium (NE), then demonstrating the existence of Stackelberg equilibrium (SE). The simulation results are provided to demonstrate that the proposed scheme achieves considerable performance gains over benchmark schemes.
  • Pengcheng Guo, Miao Yu, Miaomiao Gu, Bingyin Ren
    Received: 2023-09-21; Revised: 2023-12-28; Accepted: 2024-02-27; Online: 2024-03-15
    Automatic modulation classification (AMC) aims at identifying the modulation of the received signals, which is a significant approach to identifying the target in military and civil applications. In this paper, a novel data-driven framework named convolutional and transformer-based deep neural network (CTDNN) is proposed to improve the classification performance. CTDNN can be divided into four modules, i.e., convolutional neural network (CNN) back_x0002_bone, transition module, transformer module, and final classifier. In the CNN backbone, a wide and deep convolution structure is designed, which consists of 1×15 convolution kernels and intensive cross-layer connections instead of traditional 1×3 kernels and sequential connections. In the transition module, a 1×1 convolution layer is utilized to compress the channels of the previous multi-scale CNN features. In the transformer module, three self-attention layers are designed for extracting global features and generating the classification vector. In the classifier, the final decision is made based on the maximum a posterior probability. Extensive simulations are conducted, and the result shows that our proposed CTDNN can achieve superior classification performance than traditional deep models.
  • Feng Zheng,Yongshuai Li,Chongyu Zhang,Bin Ni
    Received: 2023-06-22; Revised: 2023-10-10; Accepted: 2024-02-27; Online: 2024-03-15
    This paper adopts discrete passive beam forming to an intelligent reflecting surface (IRS) assisted multi-input multi-output (MIMO) system, aiming to maximize the sum capacity cost-effectively. To tackle this intractable non-convex optimization problem, we use the sum-path-gain maximization (SPGM)criterion to obtain an effective suboptimal so lution to this problem and propose a low-complexity closest point projection (CPP) algorithm to project the continuous solution to the closest point in the discrete set. Furthermore, we proposed an approximation al gorithm based on time order to reduce the complex ity caused by algorithm iteration. Specifically, the approximation algorithm selects the optimal phase of each reflecting element from a discrete phase set in turn, and the local optimal solutions can be achieved in linear time. The numerical results show that the pro posed algorithms significantly reduce the complexity of discrete passive beamforming and achieve perfor mance close to continuous at a low quantized level.
  • Hongchao Hu, Yuanbo Li , Shuai Zhang, Wenyan Liu, Guozhen Cheng, Shumin Huo, Hao Liang
    Received: 2023-10-30; Revised: 2024-01-17; Accepted: 2024-02-27; Online: 2024-03-15
    Vulnerability-based attacks are the main threats to various information communication technology systems. With the widespread deployment of cloud computing environments, security threats based on various known and unknown vulnerabilities in cloud computing may cause serious impacts. The goal of this paper is to study the possibility of defending against attackers by building an endogenous security cloud that can mask the known and unknown vulnerabilities exploited by attackers at the attack path, utilizing n diversified executors and negative feedback control mechanism. The proposed framework can also provide alerts for cloud management systems to resolve the intrusion at the same time through adaptive monitoring and scheduling. This paper describes the necessary steps to transform a naive cloud into an endogenous security cloud that includes intrusion tolerance and detection, and evaluated the security, feasibility and effectiveness of the approach using real cases. Experimental results demonstrate that endogenous security cloud can defend known and unknown vulnerability-based attacks, meanwhile, hold acceptable usability and scalability.
  • Haoyue Zhang, Yiqing Zhou, Yanli Qi, Qing Cai, Ling Liu
    Received: 2023-06-27; Revised: 2024-01-29; Accepted: 2024-02-27; Online: 2024-03-15
    Vehicular edge computing (VEC) is a promising technology for computing-intensive and latency-sensitive applications in vehicular networks. However, vehicles with high mobility will travel across multiple cells with changing wireless channel states and heterogeneous MEC servers, which makes the target MEC server selection critical to achieving the minimum task latency. Moreover, the intermediate data among dependent sub-tasks results in asymmetrical uplink and downlink transmission latencies, which requires a two-way offloading in VEC. Therefore, considering dependent task in VEC, a Mobility-aware Dependent Task Two-way Offloading (MADTO) scheme is proposed, where the target MEC server selection and task partition are jointly optimized to minimize the task completion latency. Firstly, the dual-weighted task latency graph (DWTLG) is proposed to characterize the two-way offloading latency. Then, a two-stage sub-optimal algorithm, iterative local resource allocation and task DWTLG partition (ILRA-DP), is proposed to solve the joint optimization problem. Simulation results show the proposed MADTO scheme reduces task completion latency by up to 30% compared with existing schemes.
  • Yunping Mu, GongpuWang, Saman Atapattu, Xingwang Li, Bo Ai
    Received: 2023-10-07; Revised: 2024-01-22; Accepted: 2024-02-27; Online: 2024-03-15
    Wireless network coverage in tunnel scenarios is a challenge for wireless communication systems on high-speed railways. This letter considers utilizing backscatter technology to enhance the coverage in the straight tunnels, and evaluates the corresponding performance in terms of the signal strength. Specifically, we derive the probability of the case that the signal strength of the direct link is stronger than or close to that of the backscatter link. During the probability derivation process, we use the Gamma approximation method to simplify the calculation. Besides, we evaluate the effects of different tag positions on the signal strength. All analyses are based on the channel state information (CSI) perfectly known. It is found that the signal strength will be improved when the tag is close to the transmitter. Finally, simulation results are provided to corroborate our proposed studies.
  • Xuan Shen, Bo Wu, Jun He, Yi Zhang
    Received: 2023-07-19; Revised: 2023-10-08; Accepted: 2023-12-18; Online: 2024-02-08
    To improve the resistance against known statistical attacks, the design of block ciphers integrated the dynamic idea and proposed the dynamic block cipher structure. The components of specific block ciphers in dynamic structures are variable under a set of independent control parameters. Therefore, the data flow and properties of each instance in the dynamic structure can be different. Meanwhile, the complexity of cryptanalysis will also increase.In this paper, we focus on the impossible differential properties of a CLEFIA-based dynamic block cipher structure. Utilizing a matrix method, a unified description of the differential propagation is presented and the efforts for evaluating each specific instance can be saved.Our results show that there exist 8-round impossible differentials for every parameter in the dynamic structure. When the dynamic parameters satisfy $a_0=0$, which account for 50\% of the whole space, 9-round impossible differentials can be built. These are the first results concerning the impossible differential properties of the dynamic structure. Moreover, our results can also guide the choice of parameters in block cipher design.
  • Du Tang, Zhen Wu, Xizi Tang, Jiating Luo, Ji Luo, Bofang Zheng, Yaojun Qiao
    Received: 2023-05-02; Revised: 2023-11-14; Accepted: 2024-01-23; Online: 2024-02-08
    To achieve a low-complexity nonlinearity compensation (NLC) in high-symbol-rate (HSR) systems, we propose a modified weighted digital backpropagation (M-W-DBP) by jointly shifting the calculated position of nonlinear phase noise and considering the correlation of neighboring symbols in the NLC section of DBP. Based on this model, with the aid of neural network optimization, a learned version of M-W-DBP (M-W-LDBP) is also proposed and explored. Furthermore, enough technical details are revealed for the first time, including the principle of our proposed M-W-DBP and M-W-LDBP, the training process, and the complexity analysis of different DBP-class NLC algorithms. Evaluated numerically with QPSK, 16QAM, and PS-64QAM modulation formats, 1-step-per-span (1-StPS) M-W-DBP/LDBP achieves up to 1.29/1.49 dB and 0.63/0.74 dB signal-to-noise ratio improvement compared to chromatic dispersion compensation (CDC) in 90-GBaud and 128-GBaud 1000-km single-channel transmission systems, respectively. Moreover, 1-StPS M-W-DBP/LDBP provides a more powerful NLC ability than 2-StPS LDBP but only needs about 60% of the complexity. The effectiveness of the proposed M-W-DBP and M-W-LDBP in the presence of laser phase noise is also verified and the necessity of using the learned version of M-W-DBP is also discussed. This work is a comprehensive study of M-W-DBP/LDBP and other DBP-class NLC algorithms in HSR systems.
  • Zhe Tu, Huachun Zhou, Kun Li, Haoxiang Song, Yuzheng Yang, Luxi Liu, Xiaoge Wang
    Received: 2023-04-24; Revised: 2023-06-24; Accepted: 2024-01-04; Online: 2024-02-08
    Due to the continuous expansion of network scale, the network security boundary has become increasingly ambiguous. Traditional access control methods rely on network boundaries to establish a trust foundation, leading to challenges such as trust abuse and internal attacks that are challenging to mitigate. This paper proposes a blockchain-enabled attribute-based access control method for zero-trust networks to address the issues of insufficient continuous verification capability and weak dynamic control ability in traditional access control methods. Firstly, a blockchain-based access control model that combines blockchain technology, the attribute-based access control model, and zero-trust network architecture is proposed. Furthermore, the access control process is optimized based on the proposed model, considering the access status of different users to enhance the efficiency of user access control. Finally, the evaluation results demonstrate that the proposed method of access control can offer continuous and efficient access control responses to user-initiated access requests, enabling dynamic control of user access behaviors.
  • Lili Tong, Jia Zeng, Ying Di, Nan Wang
    Received: 2023-11-16; Revised: 2023-12-20; Accepted: 2023-01-29; Online: 2024-02-08
    The social transformation brought about by digital technology is deeply impacting various industries. Digital education products, with core technologies such as 5G, AI, IOT, etc., are continuously penetrating areas such as teaching, management, and evaluation. Apps, mini-programs, and emerging large-scale models are providing excellent knowledge performance and flexible cross-media output. However, they also expose risks such as content discrimination and algorithm commercialization. This paper conducts an evidence-based analysis of digital education product risks from four dimensions: ``digital resources-information dissemination-algorithm design-cognitive assessment''. It breaks through corresponding identification technologies and, relying on the diverse characteristics of governance systems, explores governance strategies for digital education products from the three domains of ``regulators-developers-users''.
  • Zhengcao Hu, Zhizhong Zhang, Lilan Liu, Chao Jiang
    Received: 2023-06-14; Revised: 2023-09-28; Accepted: 2023-11-29; Online: 2024-02-08
    This paper considers a resource-constrained (e.g., transmit power, spectrum, and on-board battery capacity) unmanned aerial vehicle (UAV) wireless network, where one UAV is dispatched as a mobile base station to satisfy the real-time quality-of-service requirements of ground users (GUs). To fully utilize the limited communication capacity of the UAV, we investigate a joint optimization problem of resource allocation and UAV trajectory design to maximize energy efficiency while considering the GUs' predictable movement routes. The investigated problem is challenging to solve due to the mixed-integer, non-linear, and non-convex properties, and thus an alternating iteration algorithm is proposed. Specifically, we transform the complex fractional objective function of the investigated problem into a subtractive form and then alternately optimize the subchannel allocation, power control, and trajectory design, where the particle swarm optimization algorithm with penalty functions and the successive convex approximation method are applied. Simulation results demonstrate that the proposed algorithm can obtain higher throughput and energy efficiency than benchmark schemes.
  • Chongzhi Han, Guji Gong, Bin He, Zhen Lin, Tongyu Ding, Liang Zhang
    Received: 2023-07-04; Revised: 2023-10-28; Accepted: 2023-01-23; Online: 2024-02-08
    In this paper, a novel wideband 8-element multiple-input and multiple-output (MIMO) antenna based on Booker’s relation is proposed for the fifth generation (5G) handset applications. The 8 antenna elements are arranged symmetrically along the two longer vertical side-edge frames of the handset. Each antenna element is composed of a monopole and a slot radiation structure, in which wideband characteristic covering 3140-5620MHz can be obtained. Note that the L-shaped monopole and the slot can be deemed as complementary counterparts approximatively. Furthermore, the Z-parameter of the proposed wideband antenna element is equivalent to the shunt impedance of monopole as well as slot radiator. Based on Booker’s relation, the wideband input impedance characteristic is therein achieved compared with conventional wideband technique such as multi-resonance. Four L-shaped stubs as well as two slots etched on the ground plane are utilized to achieve acceptable isolation performance better than 13 dB, with total efficiency higher than 60% and envelope correlation coefficients (ECCs) lower than 0.1. The proposed antenna scheme can be a good candidate for 5G handset applications with the advantages of wideband, simple structure, high efficiency, and acceptable isolation performance. Also, the scheme might be a rewarding attempt to promote the Booker’s relation in the application of 5G terminal MIMO antenna designs.
  • Hailong Su, Yaoqi Liu, Yiqing Zhou, Jinglin Shi, Hongguang Li, Manli Qian
    Received: 2022-12-15; Revised: 2023-04-13; Accepted: 2023-05-29; Online: 2024-02-08
    Low-Earth-Orbit satellite constellation networks (LEO-SCN) can provide low-cost, large-scale, flexible coverage wireless communication services. High dynamics and large topological sizes characterize LEO-SCN. Protocol development and application testing of LEO-SCN are challenging to carry out in a natural environment. Simulation platforms are a more effective means of technology demonstration. Currently available simulators have a single function and limited simulation scale. There needs to be a simulator for full-featured simulation. In this paper, we apply the parallel discrete-event simulation technique to the simulation of LEO-SCN to support large-scale complex system simulation at the packet level. To solve the problem that single-process programs cannot cope with complex simulations containing numerous entities, we propose a parallel mechanism and algorithms LP-NM and LP-YAWNS for synchronization. In the experiment, we use ns-3 to verify the acceleration ratio and efficiency of the above algorithms. The results show that our proposed mechanism can provide parallel simulation engine support for the LEO-SCN.
  • Hao Zhang, Yuzhen Huang, Zhi Zhang, Xingbo Lu
    Received: 2023-07-20; Revised: 2023-11-09; Accepted: 2024-01-23; Online: 2024-02-08
    Applying non-orthogonal multiple access (NOMA) to the mobile edge computing (MEC) network supported by unmanned aerial vehicles (UAVs) can improve spectral efficiency and achieve massive user access on the basis of solving computing resource constraints and coverage problems. However, the UAV-enabled network has a serious risk of information leakage on account of the openness of wireless channel. This paper considers a UAV-MEC secure network based on NOMA technology, which aims to minimize the UAV energy consumption. To achieve the purpose while meeting the security and users' latency requirements, we formulate an optimization problem that jointly optimizes the UAV trajectory and the allocation of network resources. Given that the original problem is non-convex and multivariate coupled, we proposed an effective algorithm to decouple the non-convex problem into independent user relation coefficients and sub-problems based on successive convex approximation (SCA) and block coordinate descent (BCD). The simulation results showcase the performance of our optimization scheme across various parameter settings and confirm its superiority over other benchmarks with respect to energy consumption.
  • Khadiga Eltira, Abdelhamid Younis, Raed Mesleh
    Received: 2023-08-24; Revised: 2023-10-07; Accepted: 2024-01-07; Online: 2024-02-08
    In the realm of communication technol ogy, new techniques, collectively referred to as signed quadrature space modulation techniques (SQSMTs), have emerged. These techniques are designed to boost the spectral efficiency of traditional space mod ulation techniques (SMTs) by enabling additional bit modulation without the need for extra symbol trans mission. This research conducted a comprehensive analysis of outage probability and capacity in di verse SQSMTs scenarios, accounting for perfect and imperfect channel state information (CSI). Monte Carlo simulations were utilized to validate the de rived capacity formulas. The focus was primar ily on assessing mutual information within various systems, particularly signed quadrature spatial mod ulation (SQSM) and signed quadrature space shift keying (SQSSK) setups, across different multiple–input multiple–output (MIMO) channel distributions (Rayleigh, Rician, Nakagami-m fading). The study also examined the impact of channel estimation errors on system performance. Comparative analyses were carried out, contrasting the performance of SQSMTs systems against conventional quadrature spatial mod ulation (QSM), quadrature space shift keying (QSSK), improved QSM (IQSM), and parallel QSM (PQSM) systems. The findings highlighted SQSSK as con sistently outperforming other systems across various channel distributions and scenarios. Conversely,PQSM consistently exhibited the poorest performance when compared to the other systems. Notably, the per formance of SQSM and IQSM exhibited intersections at various signal-to-noise-ratio (SNR) levels. Addi tionally, it was evident that SQSSK could attain the capacity limit with a relatively small number of an tennas, distinguishing it from the other systems under consideration.
  • Kang Yan, Jinhui Li, Xinyu Fan, Jie Hu, Qin Yu, Kun Yang
    Received: 2023-08-08; Revised: 2023-11-24; Accepted: 2024-01-23; Online: 2024-02-08
    In indoor environments, various battery-powered Internet of Things (IoT) devices, such as remote controllers and electronic tags on high-level shelves, require efficient energy management. However, manually monitoring remaining energy levels and battery replacement is both inadequate and costly. This paper introduces an energy management system for indoor IoT, which includes a mobile energy station (ES) for enabling on-demand wireless energy transfer (WET) in radio frequency (RF), some energy receivers (ERs), and a cloud server. By implementing a two-stage positioning system and embedding energy receivers into traditional IoT devices, we robustly manage their energy storage. The experimental results demonstrate that the energy receiver can harvest a minimum power of 58 mW.
  • Yuanpeng Zhou, Li Li, Yanyan Wang, Xianfu Lei, Xiaohu Tang
    Received: 2023-08-08; Revised: 2023-12-06; Accepted: 2024-01-15; Online: 2024-02-08
    As a novel signaling technology, the power splitting receiver (PSR) simultaneously employs both the coherent and non-coherent signal processing. In order to improve its communication performance, an intelligent reflecting surface (IRS) is introduced into its signal propagation path. Consequently, an IRS aided PSR is concerned for a point-to-point (P2P) data link, where both the single-antenna and multi antenna deployments on the receiver are discussed. We aim at maximizing the capacity of the concerned P2P data-link by jointly optimizing the passive beam forming of IRS and the splitting ratio of PSR, either in single-antenna or multi-antenna case. However, ow ing to the coupling of multiple variables, the optimiza tion problems are non-convex and challenging, espe cially in the later multi-antenna case. The proposed alternating-approximating algorithm (A-A), aided by semi-definite relaxation (SDR) and successive con vex approximation (SCA) methods, et al., successfully overcomes these challenges. We compare the IRS aided PSR system that optimized by our proposed al gorithm to the systems without IRS or PSR, and the systems without joint optimization. The simulation re sults show that our proposal has a better performance.
  • Chunlin He, Lixia Xiao, Shuo Li, Weidan Liu, Pei Xiao, Tao Jiang
    Received: 2023-05-06; Revised: 2023-11-02; Accepted: 2024-01-23; Online: 2024-02-08
    In this paper, an index modulation (IM) aided uplink orthogonal time frequency space modulation (OTFS) structure for sparse code multiple access (SCMA) is proposed. To be more specific, the information bits are firstly partitioned for transmit antenna (TA) selection and sparse codeword mapping, respectively. Subsequently, the codewords deployed on the 2-dimensional (2D) delay-Doppler (DD) plane are transmitted by the selected TA, and the superimposed signals are jointly detected at the receiver. Furthermore, a low-complexity zero-embedded expectation propagation (ZE-EP) detector is conceived, where the codebooks are extended with zero vectors to reflect the silent indices. The simulation results demonstrate that the proposed IM-OTFS-SCMA system is capable of providing significant performance gain over the OTFS-SCMA counterpart.