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    COVER PAPER
  • COVER PAPER
    Error Probability Analysis for Ultra-Massive MIMO System and Near-Optimal Signal Detection
    Lixia Xiao, Shuo Li, Yangyang Liu, Guanghua Liu, Pei Xiao, Tao Jiang
    2023, 20(5): 1-19. https://doi.org/10.23919/JCC.fa.2022-0630.202305
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    In this paper, average bit error probability (ABEP) bound of optimal maximum likelihood (ML) detector is first derived for ultra massive (UM) multiple-input-multiple-output (MIMO) system with generalized amplitude phase modulation (APM), which is confirmed by simulation results. Furthermore, a minimum residual criterion (MRC) based low-complexity near-optimal ML detector is proposed for UM-MIMO system. Specifically, we first obtain an initial estimated signal by a conventional detector, i.e., matched filter (MF), or minimum mean square error (MMSE) and so on. Furthermore, MRC based error correction mechanism (ECM) is proposed to correct the erroneous symbol encountered in the initial result. Simulation results are shown that the performance of the proposed MRC-ECM based detector is capable of approaching theoretical ABEP of ML, despite only imposing a slightly higher complexity than that of the initial detector.

    • REVIEW PAPER
  • REVIEW PAPER
    In Band Full Duplex (IBFD) Technology for Next Generation Wireless Networks: A Survey in Cellular Networks
    Injila, G. R. Begh
    2023, 20(5): 20-39. https://doi.org/10.23919/JCC.2023.00.008
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    Next-Generation (NextG) wireless communication networks with their widespread applications require high data rates, seamless connectivity and high quality of service (QoS). To cope up with an unprecedented rise of data hungry applications, users demand more spectral resources imposing a limitation on available wireless spectrum. One of the potential solutions to address the spectrum scarce issue is to incorporate in band full duplex (IBFD) or full duplex (FD) paradigm in next generation networks including 5G new radio (NR). Recently, FD has gained the research interest in cellular networks for its potential to double the wireless link capacity and enhancing spectral efficiency (SE). In half duplex (HD) cellular networks, base stations (BSs) can either perform uplink (UL) or downlink (DL) transmission at a particular time instant leading to reduced throughput levels. Due to the advancement in the self interference reduction (SIR) techniques, full duplex base stations (FD-BSs) can be employed to allow simultaneous UL and DL transmissions at the same time-frequency resources as compared to its HD counterpart. It ideally achieves twice the throughput without any additional complexity at user-equipment(UE). This paper covers a detailed survey on FD cellular networks. A series of SIR approaches, UE-UE mitigation techniques are summarized. Various existing MAC protocols and antenna architectures for FD cellular networks are outlined. An overview of security aspects for FD in cellular networks is also presented. Lastly, various open issues and possible research directions are brought up for FD cellular networks.
    • COMMUNICATIONS THEORIES & SYSTEMS
  • COMMUNICATIONS THEORIES & SYSTEMS
    Event-Driven Non-Intrusive Load Monitoring Algorithm Based on Targeted Mining Multidimensional Load Characteristics
    Gang Xie, Hongpeng Wang
    2023, 20(5): 40-56. https://doi.org/10.23919/JCC.2023.00.003
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    Nowadays, the advancement of non-intrusive load monitoring (NILM) has been hastened by the ever-increasing requirements for the reasonable use of electricity by users and demand side management. Although existing researches have tried their best to extract a wide variety of load features based on transient or steady state of electrical appliances, it is still very difficult for their algorithm to model the load decomposition problem of different electrical appliance types in a targeted manner to jointly mine their proposed features. This paper presents a very effective event-driven NILM solution, which aims to separately model different appliance types to mine the unique characteristics of appliances from multi-dimensional features, so that all electrical appliances can achieve the best classification performance. First, we convert the multi-classification problem into a serial multiple binary classification problem through a pre-sort model to simplify the original problem. Then, ConTrastive Loss K-Nearest Neighbour (CTLKNN) model with trainable weights is proposed to targeted mine appliance load characteristics. The simulation results show the effectiveness and stability of the proposed algorithm. Compared with existing algorithms, the proposed algorithm has improved the identification performance of all electrical appliance types.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Vector Approximate Message Passing with Sparse Bayesian Learning for Gaussian Mixture Prior
    Chengyao Ruan, Zaichen Zhang, Hao Jiang, Jian Dang, Liang Wu, Hongming Zhang
    2023, 20(5): 57-69. https://doi.org/10.23919/JCC.2023.00.005
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    Compressed sensing (CS) aims for seeking appropriate algorithms to recover a sparse vector from noisy linear observations. Currently, various Bayesian-based algorithms such as sparse Bayesian learning (SBL) and approximate message passing (AMP) based algorithms have been proposed. For SBL, it has accurate performance with robustness while its computational complexity is high due to matrix inversion. For AMP, its performance is guaranteed by the severe restriction of the measurement matrix, which limits its application in solving CS problem. To overcome the drawbacks of the above algorithms, in this paper, we present a low complexity algorithm for the single linear model that incorporates the vector AMP (VAMP) into the SBL structure with expectation maximization (EM). Specifically, we apply the variance auto-tuning into the VAMP to implement the E step in SBL, which decrease the iterations that require to converge compared with VAMP-EM algorithm when using a Gaussian mixture (GM) prior. Simulation results show that the proposed algorithm has better performance with high robustness under various cases of difficult measurement matrices.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Fast GNSS Acquisition Algorithm Based on SFFT with High Noise Immunity
    Haoran Zhang, Ying Xu, Ruidan Luo, Yi Mao
    2023, 20(5): 70-83. https://doi.org/10.23919/JCC.2023.00.006
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    The Global Navigation Satellite System(GNSS) has been widely used in various fields. To achieve positioning, the receiver must first lock the satellite signal. This is a complicated and expensive process that consumes a lot of resources of the receiver. For this reason, this paper proposes a new fast acquisition algorithm with High Signal-to-noise ratio(SNR) performance based on sparse fast Fourier transform(HSFFT). The algorithm first replaces the IFFT process of the traditional parallel code phase capture algorithm with inverse sparse fast Fourier transform (ISFFT) with better computing performance, and then uses linear search combined with code phase discrimination to replace the positioning loop and the estimation loop with poor noise immunity in ISFFT. Theoretical analysis and simulation results show that, compared with the existing SFFT parallel code phase capture algorithm, the calculation amount of this algorithm is reduced by 19%, and the SNR performance is improved by about 5dB. Compared with the classic FFT parallel code phase capture algorithm, the calculation amount of the algorithm in this paper is reduced by 43%, and when the capture probability is greater than 95%, the SNR performance of the two is approximately the same.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Construction of Protograph LDPC Codes Based on the Convolution Neural Network
    Zhiyuan Xiao, Liguang Li, Jin Xu, Jin Sha
    2023, 20(5): 84-92. https://doi.org/10.23919/JCC.2023.00.012
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    This paper presents an intelligent protograph construction algorithm. Protograph LDPC codes have shown excellent error correction performance and play an important role in wireless communications. Random search or manual construction are often used to obtain a good protograph, but the efficiency is not high enough and many experience and skills are needed. In this paper, a fast searching algorithm is proposed using the convolution neural network to predict the iterative decoding thresholds of protograph LDPC codes effectively. A special input data transformation rule is applied to provide stronger generalization ability. The proposed algorithm converges faster than other algorithms. The iterative decoding threshold of the constructed protograph surpasses greedy algorithm and random search by about 0.53 dB and 0.93 dB respectively under 100 times of density evolution. Simulation results show that quasi-cyclic LDPC (QC-LDPC) codes constructed from the proposed algorithm have competitive performance compared to other papers.
  • COMMUNICATIONS THEORIES & SYSTEMS
    A TDMA Approach for OFDM-Based Multiuser RadCom Systems
    Yixuan Huang, Su Hu, Gang Wu
    2023, 20(5): 93-103. https://doi.org/10.23919/JCC.2023.00.014
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    This paper is focused on the multiuser implementation of fusion of radar and communication (RadCom) in internet-of-vehicles (IoV) scenarios. Traditional time-division multiple access (TDMA) technology degrades the velocity detection performance of orthogonal frequency-division multiplexing (OFDM)-based RadCom systems. We propose a new TDMA approach for OFDM-based RadCom systems, where multiuser communication and radar detection are completed synchronously. We consider a continuous-wave TDMA OFDM structure in which random user data or Zadoff-Chu (ZC) sequences are transmitted in one symbol duration to ensure detection performance. As an application of interference cancellation method, user data demodulation and environment sensing can be simultaneously accomplished by our proposed approach. We carry out numerical evaluation and show wireless communication and radar detection performance over the continuous-wave TDMA OFDM-based RadCom approach.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Low Complexity Joint Spectrum Resource and Power Allocation for Ultra Dense Networks
    Qiang Wang, Yanhu Huang, Qingxiu Ma
    2023, 20(5): 104-118. https://doi.org/10.23919/JCC.2023.00.016
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    In this paper, we propose a low complexity spectrum resource allocation scheme cross the access points (APs) for the ultra dense networks (UDNs), in which all the APs are divided into several AP groups (APGs) and the total bandwidth is divided into several narrow band spectrum resources and each spectrum resource is allocated to APGs independently to decrease the interference among the cells. Furthermore, we investigate the joint spectrum and power allocation problem in UDNs to maximize the overall throughput. The problem is formulated as a mixed-integer nonconvex optimization (MINCP) problem which is difficult to solve in general. The joint optimization problem is decomposed into two subproblems in terms of the spectrum allocation and power allocation respectively. For the spectrum allocation, we model it as a auction problem and a combinatorial auction approach is proposed to tackle it. In addition, the DC programming method is adopted to optimize the power allocation subproblem. To decrease the signaling and computational overhead, we propose a distributed algorithm based on the Lagrangian dual method. Simulation results illustrate that the proposed algorithm can effectively improve the system throughput.
  • COMMUNICATIONS THEORIES & SYSTEMS
    Uniquely Decomposable Constellation Group-Based Sparse Vector Coding for Short Packet Communications
    Xuewan Zhang, Hongyang Chen, Di Zhang, Ganyu Qin, Battulga Davaasambuu, Takuro Sato
    2023, 20(5): 119-134. https://doi.org/10.23919/JCC.fa.2022-0253.202305
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    Sparse vector coding (SVC) is emerging as a potential technology for short packet communications. To further improve the block error rate (BLER) performance, a uniquely decomposable constellation group-based SVC (UDCG-SVC) is proposed in this article. Additionally, in order to achieve an optimal BLER performance of UDCG-SVC, a problem to optimize the coding gain of UDCG-based superimposed constellation is formulated. Given the energy of rotation constellations in UDCG, this problem is solved by converting it into finding the maximized minimum Euclidean distance of the superimposed constellation. Simulation results demonstrate the validness of our derivation. We also find that the proposed UDCG-SVC has better BLER performance compared to other SVC schemes, especially under the high order modulation scenarios.
  • COMMUNICATIONS THEORIES & SYSTEMS
    A Convolutional and Transformer Based Deep Neural Network for Automatic Modulation Classification
    Shanchuan Ying, Sai Huang, Shuo Chang, Zheng Yang, Zhiyong Feng, Ningyan Guo
    2023, 20(5): 135-147. https://doi.org/10.23919/JCC.ja.2022-0580
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    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) backbone, transition module, transformer module, and final classifier. In the CNN backbone, a wide and deep convolution structure is designed, which consists of 1$\times$15 convolution kernels and intensive cross-layer connections instead of traditional 1$\times$3 kernels and sequential connections. In the transition module, a 1$\times$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.
    • NETWORKS & SECURITY
  • NETWORKS & SECURITY
    A Cooperative Security Monitoring Mechanism Aided by Optimal Multiple Slave Cluster Heads for UASNs
    Yougan Chen, Wei Wang, Xiang Sun, Yi Tao, Zhenwen Liu, Xiaomei Xu
    2023, 20(5): 148-169. https://doi.org/10.23919/JCC.fa.2021-0168.202305
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    As each cluster head (CH) sensor node is used to aggregate, fuse, and forward data from different sensor nodes in an underwater acoustic sensor network (UASN), guaranteeing the data security in a CH is very critical. In this paper, a cooperative security monitoring mechanism aided by multiple slave cluster heads (SCHs) is proposed to keep track of the data security of a CH. By designing a low complexity “equilateral triangle algorithm (ETA)”, the optimal SCHs (named as ETA-based multiple SCHs) are selected from the candidate SCHs so as to improve the dispersion and coverage of SCHs and achieve large-scale data security monitoring. In addition, by analyzing the entire monitoring process, the close form expression of the probability of the failure attack identification for the SCHs with respect to the probability of attack launched by ordinary nodes is deduced. The simulation results show that the proposed optimal ETA-based multiple SCH cooperation scheme has lower probability of the failure attack identification than that of the existing schemes. In addition, the numerical simulation results are consistent with the theoretical analysis results, thus verifying the effectiveness of the proposed scheme.
  • NETWORKS & SECURITY
    Blockchain Based Secure Relay Scheme for Space-Terrestrial Integrated Networks
    Zhen Gao, Jiuzhi Zhang, Dongbin Zhang, Ailing Wang, Chengkang Pan, Xin Li
    2023, 20(5): 170-181. https://doi.org/10.23919/JCC.2023.00.015
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    The future 6G networks will integrates space and terrestrial networks to realize a fully connected world with extensive collaboration. However, how to build trust between multiple parties is a difficult problem for secure cooperation without a reliable third-party. Blockchain is a promising technology to solve this problem by converting the trust between multi-parties to the trust to the common shared data. Several works have proposed to apply the incentive mechanism in blockchain to encourage effective cooperation, but how to evaluate the cooperation performance and avoid breach of contract is not discussed. In this paper, a secure relay scheme is proposed based on the consortium blockchain system composed by different operators. In particular, smart contract checks the integrity of the message based on RSA accumulator, and executes transactions automatically when the message is delivered successfully. Detailed procedures are introduced for both uplink and downlink relay. Implementation based on Hyperledger Fabric proves the effectiveness of the proposed scheme and shows that the complexity of the scheme is low enough for practical deployment.
  • NETWORKS & SECURITY
    Directed Acyclic Graph Blockchain for Secure Spectrum Sharing and Energy Trading in Power IoT
    Zixi Zhang, Mingxia Zhang, Yu Li, Bo Fan, Li Jiang
    2023, 20(5): 182-197. https://doi.org/10.23919/JCC.2023.00.013
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    Peer-to-peer (P2P) spectrum sharing and energy trading are promising solutions to locally satisfy spectrum and energy demands in power Internet of Things(IoT). However, implementation of large-scale P2P spectrum sharing and energy trading confronts security and privacy challenges. In this paper, we exploit consortium blockchain and Directed Acyclic Graph (DAG) to propose a new secure and distributed spectrum sharing and energy trading framework in power IoT, named spectrum-energy chain, where a set of local aggregators (LAGs) cooperatively confirm the identity of the power devices by utilizing consortium blockchain, so as to form a main chain. Then, the local power devices verify spectrum and energy micro-transactions simultaneously but asynchronously to form local spectrum tangle and local energy tangle, respectively. Moreover, an iterative double auction based micro transactions scheme is designed to solve the spectrum and energy pricing and the amount of shared spectrum and energy among power devices. Security analysis and numerical results illustrate that the developed spectrum-energy chain and the designed iterative double auction based micro-transactions scheme are secure and efficient for spectrum sharing and energy trading in power IoT.
  • NETWORKS & SECURITY
    A Provably Secure and PUF-Based Authentication Key Agreement Scheme for Cloud-Edge IoT
    Liquan Chen, Jinlong Wang, Bangwei Yin, Kunliang Yu, Jinguang Han
    2023, 20(5): 198-216. https://doi.org/10.23919/JCC.2023.00.010
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    With the exponential growth of intelligent Internet of Things (IoT) applications, Cloud-Edge (CE) paradigm is emerging as a solution that facilitates resource-efficient and timely services. However, it remains an underlying issue that frequent end-edge-cloud communication is over a public or adversary-controlled channel. Additionally, with the presence of resource-constrained devices, it's imperative to conduct the secure communication mechanism, while still guaranteeing efficiency. Physical unclonable functions (PUF) emerge as promising lightweight security primitives. Thus, we first construct a PUF-based security mechanism for vulnerable IoT devices. Further, a provably secure and PUF-based authentication key agreement scheme is proposed for establishing the secure channel in end-edge-cloud empowered IoT, without requiring pre-loaded master keys. The security of our scheme is rigorously proven through formal security analysis under the random oracle model, and security verification using AVISPA tool. The comprehensive security features are also elaborated. Moreover, the numerical results demonstrate that the proposed scheme outperforms existing related schemes in terms of computational and communication efficiency.
  • NETWORKS & SECURITY
    Multi-Antenna Jammer Assisted Covert Communications in Data Collected IoT with NOMA
    Liwei Tao, Weiwei Yang, Xingbo Lu, Ruiqian Ma, Ling Yang, Yi Song
    2023, 20(5): 217-231. https://doi.org/10.23919/JCC.fa.2021-0300.202305
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    In this paper, we investigate covert communications in data collected IoT with NOMA, where the paired sensor nodes $S_m$ and $S_n$ transmit covert messages to a legitimate receiver (Bob) in the presence of a Warden (Willie). To confuse the detection at Willie, an extra multi-antenna friendly jammer (Jammer) has been employed to transmit artificial noise (AN) with random power. Based on the CSI of Willie is available or not at Jammer, three AN transmission schemes, including null-space artificial noise (NAN), transmit antenna selection (TAS), and zero-forcing beamforming (ZFB), are proposed. Furthermore, the closed-form expressions of expected minimum detection error probability (EMDEP) and joint connection outage probability (JCOP) are derived to measure covertness and reliability, respectively. Finally, the maximum effective covert rate (ECR) is obtained with a given covertness constraint. The numerical results show that ZFB scheme has the best maximum ECR in the case of the number of antennas satisfies $N >; 2$, and the same maximum ECR can be achieved in ZFB and NAN schemes with $N=2$. Moreover, TAS scheme also can improve the maximum ECR compared with the benchmark scheme (i.e., signal-antenna jammer). In addition, a proper NOMA node pairing can further improve the maximum ECR.
  • NETWORKS & SECURITY
    Multi-Panel Extra-Large Scale MIMO Based Joint Activity Detection and Channel Estimation for Near-Field Massive IoT Access
    Zhen Gao, Hanlin Xiu, Yikun Mei, Anwen Liao, Malong Ke, Chun Hu, Mohamed-Slim Alouini
    2023, 20(5): 232-243. https://doi.org/10.23919/JCC.fa.2022-0138.202305
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    The extra-large scale multiple-input multiple-output (XL-MIMO) for the beyond fifth/sixth generation mobile communications is a promising technology to provide Tbps data transmission and stable access service. However, the extremely large antenna array aperture arouses the channel near-field effect, resulting in the deteriorated data rate and other challenges in the practice communication systems. Meanwhile, multi-panel MIMO technology has attracted extensive attention due to its flexible configuration, low hardware cost, and wider coverage. By combining the XL-MIMO and multi-panel array structure, we construct multi-panel XL-MIMO and apply it to massive Internet of Things (IoT) access. First, we model the multi-panel XL-MIMO-based near-field channels for massive IoT access scenarios, where the electromagnetic waves corresponding to different panels have different angles of arrival/departure (AoAs/AoDs). Then, by exploiting the sparsity of the near-field massive IoT access channels, we formulate a compressed sensing based joint active user detection (AUD) and channel estimation (CE) problem which is solved by AMP-EM-MMV algorithm. The simulation results exhibit the superiority of the AMP-EM-MMV based joint AUD and CE scheme over the baseline algorithms.
  • NETWORKS & SECURITY
    Information Freshness-Oriented Trajectory Planning and Resource Allocation for UAV-Assisted Vehicular Networks
    Hao Gai, Haixia Zhang, Shuaishuai Guo, Dongfeng Yuan
    2023, 20(5): 244-262. https://doi.org/10.23919/JCC.fa.2021-0702.202305
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    In this paper, multi-UAV trajectory planning and resource allocation are jointly investigated to improve the information freshness for vehicular networks, where the vehicles collect time-critical traffic information by on-board sensors and upload to the UAVs through their allocated spectrum resource. We adopt the expected sum age of information (ESAoI) to measure the network-wide information freshness. ESAoI is jointly affected by both the UAVs trajectory and the resource allocation, which are coupled with each other and make the analysis of ESAoI challenging. To tackle this challenge, we introduce a joint trajectory planning and resource allocation procedure, where the UAVs firstly fly to their destinations and then hover to allocate resource blocks (RBs) during a time-slot. Based on this procedure, we formulate a trajectory planning and resource allocation problem for ESAoI minimization. To solve the mixed integer nonlinear programming (MINLP) problem with hybrid decision variables, we propose a TD3 trajectory planning and Round-robin resource allocation (TTP-RRA). Specifically, we exploit the exploration and learning ability of the twin delayed deep deterministic policy gradient algorithm (TD3) for UAVs trajectory planning, and utilize Round Robin rule for the optimal resource allocation. With TTP-RRA, the UAVs obtain their flight velocities by sensing the locations and the age of information (AoI) of the vehicles, then allocate the RBs to the vehicles in a descending order of AoI until the remaining RBs are not sufficient to support another successful uploading. Simulation results demonstrate that TTP-RRA outperforms the baseline approaches in terms of ESAoI and average AoI (AAoI).
  • NETWORKS & SECURITY
    Multimodal Fraudulent Website Identification Method Based on Heterogeneous Model Ensemble
    Shengli Zhou, Linqi Ruan, Qingyang Xu, Mincheng Chen
    2023, 20(5): 263-274. https://doi.org/10.23919/JCC.fa.2022-0234.202305
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    The feature analysis of fraudulent websites is of great significance to the combat, prevention and control of telecom fraud crimes. Aiming to address the shortcomings of existing analytical approaches, i.e. single dimension and venerability to anti-reconnaissance, this paper adopts the Stacking, the ensemble learning algorithm, combines multiple modalities such as text, image and URL, and proposes a multimodal fraudulent website identification method by ensembling heterogeneous models. Cross-validation is first used in the training of multiple largely different base classifiers that are strong in learning, such as BERT model, residual neural network (ResNet) and logistic regression model. Classification of the text, image and URL features are then performed respectively. The results of the base classifiers are taken as the input of the meta-classifier, and the output of which is eventually used as the final identification. The study indicates that the fusion method is more effective in identifying fraudulent websites than the single-modal method, and the recall is increased by at least 1%. In addition, the deployment of the algorithm to the real Internet environment shows the improvement of the identification accuracy by at least 1.9% compared with other fusion methods.
    • EMERGING TECHNOLOGIES & APPLICATIONS
  • EMERGING TECHNOLOGIES & APPLICATIONS
    AI Enlightens Wireless Communication: Analyses and Solutions for DMRS Channel Estimation
    Bule Sun, Zhiqin Wang, Ang Yang, Xiaofeng Liu, Shi Jin, Peng Sun, Rakesh Tamrakar, Dajie Jiang
    2023, 20(5): 275-287. https://doi.org/10.23919/JCC.fa.2022-0201.202305
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    In this paper, a systematic description of the artificial intelligence (AI)-based channel estimation track of the 2nd Wireless Communication AI Competition (WAIC) is provided, which is hosted by IMT-2020(5G) Promotion Group 5G+AI Work Group. Firstly, the system model of demodulation reference signal (DMRS) based channel estimation problem and its corresponding dataset are introduced. Then the potential approaches for enhancing the performance of AI based channel estimation are discussed from the viewpoints of data analysis, pre-processing, key components and backbone network structures. At last, the final competition results composed of different solutions are concluded. It is expected that the AI-based channel estimation track of the 2nd WAIC could provide insightful guidance for both the academia and industry.
    • EMERGING TECHNOLOGIES ＆ APPLICATIONS
  • EMERGING TECHNOLOGIES ＆ APPLICATIONS
    An Integrated Image Task Planning in Satellite Networks: From Instruction Release and Observation Perspective
    Di Zhou, Yixin Wang, Min Sheng, Chengyuan Tang, Jiandong Li
    2023, 20(5): 288-301. https://doi.org/10.23919/JCC.2023.00.004
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    The unreasonable observation arrangements in the satellite operation control center (SOCC) may result in the observation data cannot be downloaded as scheduled. Meanwhile, if the operation instructions released by the satellite telemetry tracking center (STTC) for the on-board payloads are not injected on the specific satellites in time, the corresponding satellites cannot perform the observation operations as planned. Therefore, there is an urgent need to design an integrated instruction release, and observation task planning (I-IRO-TP) scheme by efficiently collaborating the SOCC and STTC. Motivated by this fact, we design an interaction mechanism between the SOCC and the STTC, where we first formulate the I-IRO-TP problem as a constraint satisfaction problem aiming at maximizing the number of completed tasks. Furthermore, we propose an interactive imaging task planning algorithm based on the analysis of resource distribution in the STTC during the previous planning periods to preferentially select the observation arcs that not only satisfy the requirements in the observation resource allocation phase but also facilitate the arrangement of measurement and control instruction release. We conduct extensive simulations to demonstrate the effectiveness of the proposed algorithm in terms of the number of completed tasks.

    • EMERGING TECHNOLOGIES & APPLICATIONS
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Task Offloading Optimization for AGVs with Fixed Routes in Industrial IoT Environment
    Peng Liu, Zifu Wu, Hangguan Shan, Fei Lin, Qi Wang, Qingshan Wang
    2023, 20(5): 302-314. https://doi.org/10.23919/JCC.2023.00.009
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    In order to solve the delay requirements of computing intensive tasks in industrial Internet of things, edge computing is moving from theoretical research to practical applications. Edge servers (ESs) have been deployed in factories, and on-site auto guided vehicles (AGVs), besides doing their regular transportation tasks, can partly act as mobile collectors and distributors of computing data and tasks. Since AGVs may offload tasks to the same ES if they have overlapping path segments, resource allocation conflicts are inevitable. In this paper, we study the problem of efficient task offloading from AGVs to ESs, along their fixed trajectories. We propose a multi-AGV task offloading optimization algorithm (MATO), which first uses the weighted polling algorithm to preliminarily allocate tasks for individual AGVs based on load balancing, and then uses the Deep Q-Network (DQN) model to obtain the updated offloading strategy for the AGV group. The simulation results show that, compared with the existing methods, the proposed MATO algorithm can significantly reduce the maximum completion time of tasks and be stable under various parameter settings.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    A Distributed Newton Method for Processing Signals Defined on the Large-Scale Networks
    Yanhai Zhang, Junzheng Jiang, Haitao Wang, Mou Ma
    2023, 20(5): 315-329. https://doi.org/10.23919/JCC.2023.00.002
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    In the graph signal processing (GSP) framework, distributed algorithms are highly desirable in processing signals defined on large-scale networks. However, in most existing distributed algorithms, all nodes homogeneously perform the local computation, which calls for heavy computational and communication costs. Moreover, in many real-world networks, such as those with straggling nodes, the homogeneous manner may result in serious delay or even failure. To this end, we propose active network decomposition algorithms to select non-straggling nodes (normal nodes) that perform the main computation and communication across the network. To accommodate the decomposition in different kinds of networks, two different approaches are developed, one is centralized decomposition that leverages the adjacency of the network and the other is distributed decomposition that employs the indicator message transmission between neighboring nodes, which constitutes the main contribution of this paper. By incorporating the active decomposition scheme, a distributed Newton method is employed to solve the least squares problem in GSP, where the Hessian inverse is approximately evaluated by patching a series of inverses of local Hessian matrices each of which is governed by one normal node. The proposed algorithm inherits the fast convergence of the second-order algorithms while maintains low computational and communication cost. Numerical examples demonstrate the effectiveness of the proposed algorithm.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Specific Order and Bisection Search Aided Joint 3D Beamforming and RIS Reflecting Optimization
    Hongxing He, Li Li, Peichang Zhang, Xiaohu Tang
    2023, 20(5): 330-339. https://doi.org/10.23919/JCC.2023.00.007
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    In this paper, a three-node transmission model is conceived, where the base station (BS) node leverages 3D beamforming, the reconfigurable intelligent surface (RIS) node can constructively reconfigure the wireless channel, the user node only has a single antenna due to a limited price. Maximization of its downlink spectral efficiency is a joint optimization problem of three variables, namely phase-shift matrix $\mathbf{\Phi}$ of RIS, tilt angle $\theta$ and beamforming vector $\mathbf{\mathop{w}}$ used in BS 3D beamforming. We solve this problem by employing the alternating optimization (AO) algorithm. But, in each iteration, a specific optimization order of firstly $\mathbf{\Phi}$, secondly $\theta$ and finally $\mathbf{\mathop{w}}$ is proposed, which facilitates the search of optimal $\theta$ in the way of narrowing its trust region and enabling unimodal property over the narrowed trust region. It finally results in a better combination of $\lbrace \mathbf{\Phi}, \theta, \mathbf{\mathop{w}} \rbrace $.
  • EMERGING TECHNOLOGIES & APPLICATIONS
    Position Optimization for Mobile Relay Communications with Constrained Energy over a Whole Horizontal Plane
    Haijun Tan, Ning Xie
    2023, 20(5): 340-350. https://doi.org/10.23919/JCC.2023.00.011
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    This paper concerns the position optimization problem of a mobile relay over a whole horizontal plane. This problem is important because the position of a mobile relay directly affects the end-to-end performance, e.g., reliability, connectivity, and data rate. In this paper, we propose a new position optimization scheme of a mobile relay over a whole horizontal plane based on the one-bit feedback information from the destination node, which improves the performance over the prior scheme whose position of the mobile relay is optimized over a fixed orbit. In the proposed scheme, the mobile relay is equipped with merely one single onboard antenna. Moreover, no prior information about the positions of both the source node and the destination node is required. Thus, the proposed scheme can work at low network resources scenario, which is particularly suitable for mobile relay communication with constrained energy, e.g., the communications in a disaster area where the infrastructure is heavily damaged, volcano monitoring, and wireless powered communication networking. According to the characteristics of the proposed scheme, we further design two heuristic implementations to calculate the optimal position of a mobile relay over a whole horizontal plane. The first implementation has better steady performance whereas the second implementation has better convergence speed. We implement the proposed scheme and conduct an extensive performance comparison between the proposed scheme and prior schemes to verify the advantages of the proposed scheme.