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STARS Assisted Semi-Grant-Free NOMA communications

IEEE Transactions on Wireless communications 2025年第6期24卷 4904-4919页

作者： Xie, Jin Yue, Xinwei Zhao, Jingjing Zou, Yixuan Liu, Yuanwei Liu, Rongke Ding, Zhiguo Key Laboratory of Information and Communication Systems China Beijing Information Science and Technology University Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing100101 China Beihang University School of Electronic and Information Engineering Beijing100191 China Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong Hong Kong Kyung Hee University Department of Electronic Engineering Gyeonggi-do Yongin-si17104 Korea Republic of Khalifa University Department of Computer and Information Engineering Abu Dhabi United Arab Emirates

This paper investigates the performance of simultaneously transmitting and reflecting surface (STARS) assisted semi-grant-free non-orthogonal multiple access network with randomly distributed users. By deploying STARS, the transmit signals of grant-based user (GBU) and grant-free users (GFUs) can be exquisitely adjusted to reduce interference. We propose a maximum channel scheduling (MCS) protocol that allows a GFU to access GBU’s channel with the assistance of STARS. In particular, the impacts of perfect/imperfect successive interference cancellation (pSIC/ipSIC) on MCS protocol are taken into account. To characterize the performance of STARS aided MCS (STARS-MCS) network, we derive the expressions of outage probability for GBU and GFU with pSIC/ipSIC. By applying convolution theorem and Laplace transform, the asymptotic expressions of outage probability and diversity orders for GBU and GFU are attained. We further design a STARS-based power control (SPC) strategy to eliminate the outage probability error floor and improve the outage performance. Numerical results show that: 1) The performance of STARS-MCS outperforms the existing benchmarks in terms of outage probability and system throughput;2) The SPC strategy can effectively improve the performance of the STARS-MCS network and eliminate the outage probability error floor at high signal-to-noise ratios;and 3) By adjusting reflection and transmission coefficients of STARS, the outage performance of GBU and GFU can be greatly enhanced. © 2025 IEEE. All rights reserved.

关键词： Laplace transforms

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An Optimized Method of Packet Loss Rate under Backup Path Protection in OBS Network 3

An Optimized Method of Packet Loss Rate under Backup Path Pr...

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2020 3rd International Conference on Modeling, Simulation and Optimization Technologies and Applications, MSOTA 2020

作者： Meng, Aodong Chen, Yucheng Dai, Jiahao Chen, Yongqun Science and Technology on Communication Information Security Control Laboratory Jiaxing China No.36 Research Institute of Cetc Jiaxing China

In order to calculate the packet loss rate in OBS network, this paper proposes a method, which performs good in both accuracy and rapidity, based on Erlang B formula to estimate the packet loss probability in OBS network using backup path protection mechanism. This method can be used to optimize the design of OBS network protocol, and it also provides an accurate and efficient approximate calculation method of packet loss rate in OBS network and can be conductive to the study of using copy transmission to enhance the network survivability. Based on the formula of Erlang B, this paper briefly introduces the derivation process and principle of this method. The basic experimental principles of simulation and estimation processes are designed in this paper, and the experimental results of the proposed method under a typical network topology (ARPA network) with no protection mechanism and 1 and 2 backup paths protection mechanisms are analyzed to verify its rapidity and accuracy. The results of experiments show the accuracy and efficiency of this method. © Published under licence by IOP Publishing Ltd.

关键词： Network topology

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Coastal Regions Sea Surface Salinity Retrieval of SMAP MISSION Based on Light Gradient Boosting Model

Coastal Regions Sea Surface Salinity Retrieval of SMAP MISSI...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Haoming Song Yifan Zhang Biao Zhang Yanfang Lv Lanjie Zhang Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing Information Science and Technology University China Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

Sea surface salinity (SSS) as an important indicator of ocean water circulation, affects global ecology and climate change. However, the accuracy of L-band satellite sea surface salinity retrieval products has been severely affected in coastal regions due to factors such as Radio Frequency Interference (RFI) and Land Sea Continuation (LSC). In this study, coastal regions observational data from the Soil Motion Active Passive (SMAP) satellite, and established the LGBM model for SSS retrieval. The results indicated that LGBM performed excellently in the retrieval of SSS in coastal regions. In comparison to in-situ SSS, the LGBM SSS demonstrated a mean bias (MB) of 0.11psu, a root mean squares error (RMSE) of 0.68psu. This paper also added the bias between LGBM SSS and in situ SSS for secondary correction of LGBM. This correction reduced the MB to 0.03psu, the RMSE to 0.54psu. This study affirms the feasibility of using LGBM for SSS retrieval in coastal regions. Future efforts will focus on integrating more auxiliary data that may influence SSS in coastal regions, aiming to further enhance the precision of the coastal regions’ SSS retrieval product.

关键词： Accuracy Sea surface salinity Biological system modeling Satellite broadcasting Sea measurements Soil Data models

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A Long Synthetic Aperture Passive Localization Method Using Two Planes

A Long Synthetic Aperture Passive Localization Method Using ...

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2021 CIE International Conference on Radar, Radar 2021

作者： Chen, Bowei Wang, Yuqi Sun, Guang-Cai Xing, Mengdao Zhang, Zijing Yang, Xiaoniu Xidian University National Laboratory of Radar Signal Processing Xi'an China Science and Technology on Communication Information Security Control Laboratory Jiaxing China

ISBN: (纸本)9781665498142

A long synthetic aperture passive localization algorithm is proposed in this paper. First of all, the Doppler change rate of signal can be measured by the image contrast and then, grid points are divided within the maximum possible latitude and longitude of the emitter location, the Doppler change rate at each grid point can be calculated by using known position and velocity of the receiver. The grid points at which the calculated Doppler change rate is equal to the value measured by the received signal form an isoline. Two receivers can draw two isolines on the ground and the intersection of the isolines gives estimate of the emitter location. © 2021 IEEE.

关键词： Azimuth focusing Doppler change rate Passive localization Synthetic aperture localization

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Mitigation of Non-stationary Jammings with Missing Samples for GNSS Using Sparse Representation

Mitigation of Non-stationary Jammings with Missing Samples f...

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2022 International Conference on Computer Engineering and Artificial Intelligence, ICCEAI 2022

作者： Ren, Yuetao Zhi, Yongfeng Zhang, Jun School of Automation Northwestern Polytechnical University Xi'an710072 China Science and Technology on Electro-Optical Information Security Control Laboratory Tianjin300308 China

ISBN: (数字)9781665468039

ISBN: (纸本)9781665468039

Global navigation satellite systems (GNSS) are widely used in most civil and military applications. However, GNSS receivers suffer from severe performance degradation when jammed by electromagnetic interference. This paper considers the mitigation problem of non-stationary jammings with missing samples for GNSS. We propose to reconstruct the interference by sparse representation utilizing the sparsity of jammings in the time-frequency (TF) domain. The GNSS signal is recovered by eliminating the reconstructed interference from the received signal. First, the instantaneous frequencies (IFs) of jammings are extracted from adaptive directional TF distributions. Then, we construct the over-complete atomic dictionary based on the estimated IFs. The interference is reconstructed by orthogonal matching pursuit (OMP) algorithm. The proposed method can achieve the mitigation of non-stationary jamming and the acquisition of GNSS signals in the presence of missing samples. We confirm the effectiveness of the algorithm by simulations. © 2022 IEEE.

关键词： Jamming

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Interference Utilization with Bandwidth Allocation in DFRC Systems

Interference Utilization with Bandwidth Allocation in DFRC S...

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International Conference on Computers, communications, and Systems (ICCCS)

作者： Zhan Xu Shengfeng Kang Xiaolong Yang Key Laboratory of Information and Communication Systems Ministry of Information Industry Key Laboratory of Modern Measurement and Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

ISBN: (数字)9798350350210

ISBN: (纸本)9798350350227

Dual-functional Radar and communication (DFRC) has become one of the key technologies of advanced wire-less systems. This is because of the continuous development of mobile communication, the scarcity of spectrum and the potential network applications. In this paper, we propose a symbol-level precoding optimization scheme for Multi-Input-Multi-Output (MIMO) radar and multi-user Multiple-Input-Single-Output (MU-MISO) communication systems. More specif-ically, the weight sum of communication rate and radar detection probability are maximized by jointly optimizing the precoding vector and bandwidth allocation. Meanwhile, it includes the condition of ensuring the receiving signal-to-interference-plus-noise ratio (SINR) at receivers, the interference to the radar and the transmission power budget at the base station (BS). Com-pared with the traditional beamforming based on Semidefinite Relaxation (SDR), the feasible area of the optimization problem is extended. Based on the concept of constructive interference, the harmful multi-user interference (MUI) is converted into a beneficial signal. So the communication rate is ensured and the system performance is improved. Numerical simulations show that our proposed method achieves a better result of the object function compared to benchmark methods, while obtaining a favorable bandwidth allocation.

关键词： Base stations Precoding System performance Radar detection Interference Radar Channel allocation

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Correction to: An advanced reinforcement learning control method for quadruped robots in typical urban terrains (International Journal of Machine Learning and Cybernetics, (2024), 10.1007/s13042-024-02478-9)

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International Journal of Machine Learning and Cybernetics 2025年第5期16卷 3759-3760页

作者： Yan, Chi Wang, Ning Gao, Hongbo Wang, Xinmiao Tang, Chao Zhou, Lin Li, Yuehua Wang, Yue School of Information Science and Technology University of Science and Technology of China No. 96 Jinzhai Road Anhui Hefei230026 China School of Information and Security Chongqing College of Mobile Communication No. 36 Dengying Avenue Qijiang District Sichuan Chongqing401520 China Institute of Advanced Technology University of Science and Technology of China No. 5089 Wangjiang West Road Anhui Hefei230088 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Nanyang639798 Singapore Zhejiang Lab Kechuang Avenue Zhongtai Sub-District Zhejiang Hangzhou311121 China College of Control Science and Engineering Zhejiang University Zhejiang Hangzhou310027 China

In this article, the affiliation details for Authors "Ning Wang2, Hongbo Gao1,3,4, Yuehua Li5, Yue Wang6" were interchanged and it is corrected now. Incorrect affiliation: 2Institute of Advanced technology, University of science and technology of China, No. 5089 Wangjiang West Road, Hefei 230088, Anhui, China 3School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798 Nanyang, Singapore 4Zhejiang Lab, Kechuang Avenue, Zhongtai Sub-District, Hangzhou 311121, Zhejiang, China 5College of control science and Engineering, Zhejiang University, Hangzhou 310027, Zhejiang, China 6School of information and security, Chongqing College of Mobile communication, No. 36 Dengying Avenue, Qijiang District, Chongqing 401520, Sichuan, China Correct affiliation: 2School of information and security, Chongqing College of Mobile communication, No. 36 Dengying Avenue, Qijiang District, Chongqing 401520, Sichuan, China 3Institute of Advanced technology, University of science and technology of China, No. 5089 Wangjiang West Road, Hefei 230088, Anhui, China 4School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798 Nanyang, Singapore 5Zhejiang Lab, Kechuang Avenue, Zhongtai Sub-District, Hangzhou 311121, Zhejiang, China 6College of control science and Engineering, Zhejiang University, Hangzhou 310027, Zhejiang, China The original article has been corrected. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

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A Mixed Intrusion Detection System utilizing K-means and Extreme Gradient Boosting 2

A Mixed Intrusion Detection System utilizing K-means and Ext...

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2022 2nd International Conference on communication technology and information technology, ICCTIT 2022

作者： Lv, Haifeng Ji, Xiaoyu Ding, Yong Guangxi Key Laboratory of Machine Vision and Intelligent Control WuZhou University Wuzhou China School of Computer Science and Information Security Guilin University of Electronic Technology Guilin China Guangxi Colleges and Universities Key Laboratory of Industry Software Technology Wuzhou University Wuzhou China

The intrusion detection system (IDS) plays an important part because it offers an efficient way to prevent and mitigate cyber attacks. Numerous deep learning methods for intrusion anomaly detection have been developed as a result of recent advances in artificial intelligence (AI) in order to strengthen internet security. The balance among the high detection rate (DR), the low false alarm rate (FAR) and disaster of dimensionality is the crucial apprehension while devising an effective IDS. For the binary classification of intrusion detection systems, we present in this study a mixed model called K-means-XGBoost consisting of K-means and (Extreme Gradient Boosting, XGBoost) algorithms. The distributed computation of our method is achieved in Spark platform to rapidly separate normal events and anomaly events. In phrases of accuracy, DR, F1-score, recall, precision, and error indices FAR, the proposed model's performance is measured via the well-known dataset of NSL-KDD. The experimental outcomes indicate that our method is outstandingly better among accuracy, DR, F1-score, training time, and processing speed, compared to other models which are recently created. In particular, the accuracy, F1-score, and DR of the proposed model can achieve as high as 93.28%, 94.39%, and 99.22% in the NSL-KDD dataset, respectively. © Published under licence by IOP Publishing Ltd.

关键词： Network security

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An Anti-jamming Intelligent Decision-Making Method for Multi-user communication Based on Deep Reinforcement Learning 22

An Anti-jamming Intelligent Decision-Making Method for Multi...

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22nd IEEE International Conference on communication technology, ICCT 2022

作者： Zhang, Lan Ma, Liang Tian, Feng Liang, Tianyi Science and Technology on Communication Information Security Control Laboratory Jiaxing314000 China The 36th Research Institution of China Electronics Technology Group Corporation Jiaxing341000 China Nanjing University of Posts and Telecommunications Nanjing210023 China

ISBN: (纸本)9781665470674

In order to effectively cope with the external malicious jamming from jammers and avoid mutual interference caused by competitive channels among users, an intelligent antijamming decision-making method based on deep reinforcement learning for multi-user communication is proposed in this paper. In multiple jamming modes, the base station perceives the current spectrum information of the multi-user and the jammer and makes it as the input of the deep reinforcement learning strategy neural network, then selects the joint action according to the dynamic greedy algorithm, which will help the users intelligently select the communication frequency band via the feedback from the base station. The simulation results show that the proposed method effectively overcome the communication jamming induced by external jammers and internal users. Moreover, the normalized throughput of each user in the proposed algorithm is much higher than the random frequency hopping and fixed ϵ deep reinforcement learning algorithm with faster convergence speed. © 2022 IEEE.

关键词： Reinforcement learning

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Fast Informer-Based Time Series Detection

Fast Informer-Based Time Series Detection

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International Symposium on Antennas, Propagation and EM Theory (ISAPE)

作者： Weiguo Shen Tianhao Xia Dongwei Xu Qi Xuan Yun Lin Wei Wang Science and Technology on Communication Information Security Control Laboratory Jiaxing China Zhejiang University of Technology College of Information Engineering Institute of Cyberspace Security Binjiang Institute of Artificial Intelligence HangZhou China Zhejiang University of Technology Institute of Cyberspace Security Binjiang Institute of Artificial Intelligence HangZhou China College of Information and Communication Engineering Harbin Engineering University Binjiang Institute of Artificial Intelligence Harbin China

ISBN: (数字)9798350353129

ISBN: (纸本)9798350353136

Time series data are pivotal in modern technology and industrial applications,but they are frequently impacted by anomalies due to system failures,cyberattacks,or unexpected events. Therefore,swift and accurate anomaly detection in time series is crucial. This paper introduces ‘TransIDS’,an intrusion detection method that focuses on the efficient extraction and detection of time series features. TransIDS uses the Informer model to capture temporal features within data frames more effectively,improving detection performance and reducing runtime. We also fine-tune the Informer model and introduce an automatic anomaly threshold selection method,optimizing it for anomaly detection tasks. We validate TransIDS through experiments on various datasets and compare it with three existing methods. The results show that TransIDS outperforms the compared models in detection performance.

关键词： Runtime Accuracy Antenna theory Time series analysis Intrusion detection Predictive models Feature extraction Transformers Data models Anomaly detection

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