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25 January 2022, Volume 43 Issue 1

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Topics: Key Technologies for Terahertz Communications

Terahertz joint communication and sensing waveform:status and prospect

Zhiqing WEI, Zhiyong FENG, Yiheng LI, Hao MA, Jinzhu JIA

2022, 43(1):  3-10.  doi:10.11959/j.issn.1000-436x.2022007

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To meet the requirements of machine communication and immersive service in the 6G era for high precision perception and high speed communication, communication perception integration technology emerges at the right moment.Based on this, the scenarios, waveform design methods and future prospects of terahertz communication perception integrated waveform were described and summarized.First of all, the scenarios and requirements of terahertz integrated waveform design were summarized, including perception-assisted communication scenarios, new business scenarios generated by perception, etc.Then, from the propagation characteristics of terahertz electromagnetic wave, the characteristics of terahertz devices, and the requirements of communication and perception on waveform, the characteristics of terahertz communication and perception integrated waveform were analyzed, and the research status of terahertz communication integrated waveform was summarized.Finally, the future research direction of terahertz synesthesia integrated waveform was pointed out.

Photonics-aided broadband terahertz communication technology

Jianjun YU, Wen ZHOU, Xinyi WANG, Kaihui WANG

2022, 43(1):  11-23.  doi:10.11959/j.issn.1000-436x.2022012

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Firstly, the key technologies in photonics-aided broadband terahertz communication systems were introduced, and then the research progress in large-capacity and long-distance terahertz communication technologies was introduced.Using these key technologies, wireless transmission of THz signals had been successively achieved exceeding 1 Tbit/s, wireless transmission of THz signals exceeding 100 Gb/s for 54.6 meters without a THz amplifier.The use of air-core optical fiber to transmit terahertz signals exceeding 100 Gbit/s was also introduced.

Analysis of propagation and coverage performance of indoor single-carrier radio signals in the terahertz bands

Mugen PENG, Chuang YANG, Tianhang ZHOU

2022, 43(1):  24-33.  doi:10.11959/j.issn.1000-436x.2022014

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To tackle the problem that radio signal in the terahertz band had different features compared to that in the conventional spectrum, which restricted its application to indoor communication scenarios, a modified propagation model of terahertz radio signal was proposed.Based on the model, the propagation and coverage performances of wide-band single-carrier terahertz radio signal were analyzed.In particular, the wide-band terahertz channel transfer function was constructed, taking the absorption loss introduced by the thickness of the obstacles into account.Using the ray tracing technique, the impacts of the obstacles’ thickness and the bandwidth on the propagation and coverage performances were examined, showing that the coverage performance can be improved by leveraging the reflections from the non-line-of-sight obstacles.Moreover, the trade-off between the coverage radius and the capacity of terahertz communications is revealed, and it is further found that the theoretical spectral efficiency decreases as the carrier frequency of terahertz radio signal increases.

Terahertz wave propagation and channel characterization

Haofan YI, Ke GUAN, Danping HE, Bo AI, Zhengrong LAI, Zhangdui ZHONG

2022, 43(1):  34-48.  doi:10.11959/j.issn.1000-436x.2022013

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Firstly, the different characteristics of terahertz waves compared to lower frequency bands were summarized, including the influence of meteorological factors and rough surfaces of materials on THz waves.Next, it was proposed to use ray-tracing (RT) technology to calibrate the three-dimensional (3D) environment model and electromagnetic parameters of materials in the target scenarios through very limited channel measurement data.Then, the reversed parameters were utilized to perform in a similar but more general scenario, instead of a large amount of channel measurement data.Finally, the channel characteristics were analyzed by extraction of the channel key parameters, such as path loss, shadow fading, Rician K-factor, delay spread, angular spread, and doppler parameters in a mobile scenario.Representing two ends of 6G THz use cases from indoor scenario to outdoor scenario, case studies were made for wireless connections on a desktop and vehicular communications, respectively.As for the outdoor scenario, the influences of meteorological factors were additionally considered.The work is of great significance for the design and evaluation of the THz communication system.

Performance analysis of RIS-assisted mixed RF/THz system

Sai LI, Liang YANG, Qimei CUI, Siyuan YU

2022, 43(1):  49-58.  doi:10.11959/j.issn.1000-436x.2022005

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To solve the problem of the short transmission distance of terahertz (THz) links, the performance of the reconfigurable intelligent surface (RIS)-assisted mixed dual-hop radio frequency (RF)/THz system was studied.An RIS was used to enhance signal strength, thereby improving the system performance.Using the fixed-gain amplify-and-forward protocol, the cumulative distribution function and probability density function of the end-to-end signal-to-noise ratio of the RF/THz link were derived.Capitalizing on the statistical characteristics, the analytical expressions of outage probability, average bit error rate, and average channel capacity of the mixed relaying system were further derived.In addition, the asymptotic analyses of the outage probability and the average bit error rate were carried out to obtain the diversity order of the mixed RF/THz system.Simulation results show that the RIS can effectively improve the performance of the mixed RF/THz system.Furthermore, the system performance is related to the channel fading, pointing errors, and propagation distance.

Papers

Efficient model-and-data based channel estimation algorithm

Kai MEI, Haitao ZHAO, Xiaoran LIU, Jun LIU, Jun XIONG, Baoquan REN, Jibo WEI

2022, 43(1):  59-70.  doi:10.11959/j.issn.1000-436x.2022019

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For orthogonal frequency division multiplexing (OFDM) systems, a hybrid model and data driven channel estimation algorithm was proposed.Combined with two existing channel estimation methods, including a low complex learning-based channel estimation method and the linear minimum mean square error (LMMSE) channel estimation, the estimator with the ability was facilitated to employ online training to improve estimation performance.Meanwhile, the pilot overhead consumed by generating online training data was saved due to the use of the model-based method in the proposed algorithm, which improved the spectrum efficiency.The simulation results demonstrate that the proposed algorithm has better performance under low signal-to-noise ratio (SNR) and better adaptation to practical imperfections compared with conventional channel estimation methods.

Two-dimensional pseudo-random coupled map lattices system based on partitioned elementary cellular automata and its dynamic properties

Youheng DONG, Geng ZHAO, Yingjie MA

2022, 43(1):  71-82.  doi:10.11959/j.issn.1000-436x.2022001

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To solve the weak chaos in the spatiotemporal chaotic system based on coupled map lattices under some control parameters and the un-uniformity of sequences generated by the coupled map lattices, a two-dimensional pseudo-random coupled map lattices (2D-PRCML) system was proposed.Firstly, the two-dimensional partitioned elementary cellular automata (2D-PECA) was designed to establish pseudo-random coupling.Secondly, iterative results of 2D-PECA were utilized to perturb the 2D-PRCML system.The chaotic behaviors of the proposed system, such as the bifurcation diagram, Kolmogorov-Sinai entropy, were investigated.Moreover, the uniformity of sequences generated by the 2D-PRCML system was discussed, and the correlation coefficients between any two sequences generated by different lattices were acquired.The analyses and tests indicate that the 2D-PRCML system exhibits stronger chaotic behavior.Furthermore, the sequence generated by the proposed system possesses better uniformity, randomness, and unpredictability.The outstanding properties of the 2D-PRCML system prove that it is more suitable for applying in cryptography and chaotic secure communication.

Automatic exploitation generation method of write-what-where vulnerability

Huafeng HUANG, Purui SU, Yi YANG, Xiangkun JIA

2022, 43(1):  83-95.  doi:10.11959/j.issn.1000-436x.2022003

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To solve the problem that the current vulnerability automatic exploitation generation methods cannot automatically generate control-flow-hijacking exploitation from write-what-where, a method of automatic exploitation generation for write-what-where was proposed.First, the write-what-where vulnerability was detected based on the memory address control strength dynamic taint analysis method.Then, the vulnerability exploitation elements were searched based on the vulnerability exploitation modes, and the exploitation of write-what-where vulnerability was generated automatically by constraint solving.The experimental results show that the proposed method can effectively detect write-what-where vulnerability, search exploitation elements, and automatically generate the control-flow-hijacking exploitation from write-what-where.

Two-layer grouped Byzantine fault tolerance algorithm for UAV swarm

Yu CHEN, Lianxing JIA

2022, 43(1):  96-103.  doi:10.11959/j.issn.1000-436x.2022021

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To reduce the communication complexity and improve the robustness of blockchain network, a two-layer grouped Byzantine fault tolerance algorithm for unmanned ariel vehicle (UAV) swarm was proposed.First, nodes were divided into several groups according to the formation results of UAV swarm.A portion of high-reputation nodes were selected from each group to form a committee, and other nodes were used as shared nodes.Threshold signature techniques were employed to reduce communication complexity.In that way, nodes from other groups only needed to communicate with the committee nodes of the current group, thus greatly reducing the average communication delay.In addition, the hierarchical structure, which made the identity of the primary node hidden in the committee, reduced the risk of being adaptively attacked by the Byzantine nodes and improves the robustness of the system.Experimental results demonstrates that the proposed algorithm significantly reduces the delay of the consensus process and can effectively ensure the aliveness of the system compared with the comparison algorithm.

Hybrid precoding based on distributed partially-connected structure for multiuser massive MIMO

Lei ZHANG, Qin WANG

2022, 43(1):  104-116.  doi:10.11959/j.issn.1000-436x.2022008

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For multiuser massive multiple-input multiple-output (MIMO) systems, to solve the problem of underutilized spatial resources caused by centralized partially-connected structure (PCS) and fixed-matching phase-control algorithm in conventional schemes, a low complexity phased zero-forcing (PZF) hybrid precoding scheme based on distributed PCS was proposed.The logical antenna subarrays with more than the number of radio frequency (RF) chains were designed, so that each RF chain could be connected to multiple distributed subarrays to provide higher spatial diversity gain.Further, by analyzing the influence of phase-control analog precoding on zero-forcing digital precoding, a phase-control analog precoding algorithm via successively maximizing users’ total subarray gains was proposed to maximize the upper bound of system spectral efficiency.Analysis and simulation results show that, compared with the conventional schemes, the proposed scheme can significantly improve the system spectral efficiency while slightly increases the computational complexity, and it is also insensitive to imperfect channel state information.

Design scheme of physical layer security for intelligent reflecting surface-assisted MISO communication system

Xiaorong JING, Zhenyuan SONG, Wei GAO, Weijia LEI, Qianbin CHEN

2022, 43(1):  117-126.  doi:10.11959/j.issn.1000-436x.2022018

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Intelligent reflecting surface (IRS) improves the physical layer security of the communication systems by adjusting the phases of the reflecting units.A scheme of physical layer security design based on alternative iteration was proposed for IRS-assisted multiple input single output (MISO) communication system.Firstly, aiming at maximizing the secrecy rate, a non-convex objective function with non-convex constraints was constructed.Secondly, the Dinkelbach algorithm and Riemannian manifold optimization algorithm were adopted to transform the non-convex problem into a series of solvable sub-problems.Finally, the alternate iteration method was used to achieve the optimization design of transmit beamforming and IRS phase shift matrix.The simulation results show that, compared with the several existing schemes, the proposed scheme can achieve a better tradeoff between computational complexity and system security rate.

Towards edge-collaborative, lightweight and privacy-preserving classification framework

Jinbo XIONG, Yongjie ZHOU, Renwan BI, Liang WAN, Youliang TIAN

2022, 43(1):  127-137.  doi:10.11959/j.issn.1000-436x.2022004

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Aiming at the problems of data leakage of perceptual image and computational inefficiency of privacy-preserving classification framework in edge-side computing environment, a lightweight and privacy-preserving classification framework (PPCF) was proposed to supports encryption feature extraction and classification, and achieve the goal of data transmission and computing security under the collaborative classification process of edge nodes.Firstly, a series of secure computing protocols were designed based on additive secret sharing.Furthermore, two non-collusive edge servers were used to perform secure convolution, secure batch normalization, secure activation, secure pooling and other deep neural network computing layers to realize PPCF.Theoretical and security analysis indicate that PPCF has excellent accuracy and proved to be security.Actual performance evaluation show that PPCF can achieve the same classification accuracy as plaintext environment.At the same time, compared with homomorphic encryption and multi-round iterative calculation schemes, PPCF has obvious advantages in terms of computational cost and communication overhead.

Action recognition method based on fusion of skeleton and apparent features

Hongyan WANG, Hai YUAN

2022, 43(1):  138-148.  doi:10.11959/j.issn.1000-436x.2022020

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Focusing on the issue that traditional skeletal feature-based action recognition algorithms were not easy to distinguish similar actions, an action recognition method based on the fusion of deep joints and manual apparent features was considered.The joint spatial position and constraints was firstly input into the long short-term memory (LSTM) model equipped with spatio-temporal attention mechanism to acquire spatio-temporal weighted and highly separable deep joint features.After that, heat maps were introduced to locate the key frames and joints, and manually extract the apparent features around the key joints that could be considered as an effective complement to the deep joint features.Finally, the apparent features and the deep skeleton features could be fused frame by frame to achieve effectively discriminating similar actions.Simulation results show that, compared with the state-of-the-art action recognition methods, the proposed method can distinguish similar actions effectively and then the accuracy of action recognition is promoted rather obviously.

PCA-based membership inference attack for machine learning models

Changgen PENG, Ting GAO, Huilan LIU, Hongfa DING

2022, 43(1):  149-160.  doi:10.11959/j.issn.1000-436x.2022009

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Aiming at the problem of restricted access failure in current black box membership inference attacks, a PCA-based membership inference attack was proposed.Firstly, in order to solve the restricted access problem of black box membership inference attacks, a fast decision membership inference attack named fast-attack was proposed.Based on the perturbation samples obtained by the distance symbol gradient, the perturbation difficulty was mapped to the distance category for membership inference.Secondly, in view of the low mobility problem of fast-attack, a PCA-based membership inference attack was proposed.Combining the algorithmic ideas based on the perturbation category in the fast-attack and the PCA technology to suppress the low-migration behavior caused by excessive reliance on the model.Finally, experiments show that fast-attack reduces the access cost while ensuring the accuracy of the attack.PCA-based attack is superior to the baseline attack under the unsupervised setting, and the migration rate of model is increased by 10% compared to fast-attack.

Step-by-step classification detection algorithm of SPPM based on K-means clustering

Huiqin WANG, Wenbin HOU, Qingbin PENG, Minghua CAO, Rui HUANG, Ling LIU

2022, 43(1):  161-171.  doi:10.11959/j.issn.1000-436x.2022010

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In view of the high computational complexity in spatial pulse position modulation systems when using maximum likelihood detection algorithm, a step-by-step classification detection algorithm based on K-means clustering was proposed according to the characteristics of signal matrix with spatial pulse position modulation.The signal vector detection algorithm was utilized to detect the index of light source in the training samples.The on K-means clustering algorithm was utilized to acquire the mapping rule between centroid of samples and modulated symbol by offline training.Subsequently, online detection of modulated symbols was achieved based on the mapping rule, and then the index of light sources was detected by exhaustive search.In addition, Monte Carlo method was used to investigate the effects of key parameters such as the number of clusters and initialization times on the system bit error rate (BER) performance.Simulation results demonstrate that the proposed algorithm can achieve an approximate BER performance as the maximum likelihood algorithm on the basis of greatly reducing the computational complexity.Compared with the linear decoding algorithms, the proposed algorithm is also applicable to scenarios where the number of detectors is less than the number of light sources.

High-precision indoor fast positioning algorithm based on carrier phase

Shaoshuai FAN, Zhiqiang RONG, Hui TIAN, Lihua LI

2022, 43(1):  172-181.  doi:10.11959/j.issn.1000-436x.2022017

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In order to improve the positioning accuracy and the speed of position solution in indoor wireless environment, a high-precision indoor fast positioning algorithm based on carrier phase was proposed.By introducing the reference terminal, the influence of clock error between devices on the accuracy of the positioning algorithm was completely eliminated by using the double difference between the carrier phase measurements of the terminal to be positioned and the reference terminal.Taking advantage of the invariability of integer ambiguity during the phase-locked loop lock-off, an iterative integer ambiguity resolution algorithm based on multi-time point measurement data was designed, and the fast integer ambiguity resolution was realized.After the integer ambiguity was solved, the terminal to be located could be located with high precision by using accurate carrier phase difference measurement.The simulation results show that the positioning algorithm proposed can completely overcome the influence of clock error on positioning performance, and can achieve centimeter-level positioning accuracy at very few sampling time points.

Intra-group mutual authentication key agreement protocol based on Chinese remainder theorem in VANET system

Haibo ZHANG, Zhou CHEN, Hongwu HUANG, Xiaofan HE

2022, 43(1):  182-193.  doi:10.11959/j.issn.1000-436x.2022002

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Aiming at the problem that vehicles in the vehicular ad-hoc network (VANET) system were vulnerable to malicious attacks when communicating with each other on the public network, a mutual authentication key agreement protocol in the VANET was proposed.A dynamic vehicle group was established by the Chinese remainder theorem to adapt to the rapid changes in the VANET topology.Signature information was used by both parties in communication to quickly authenticate the identity of the message sender, and key agreement was conduct through the semigroup of Chebyshev chaotic mapping.The pseudonym update and private key update mechanism were adopted to protect the privacy and security of the vehicle’s identity.The identities of malicious vehicles were tracked accurately by using signature information, and were revoked quickly by modifying the public key information.In addition, the semantic security of the protocol was proved by the BAN logic model.The simulation results show that the proposed protocol can effectively reduce the communication consumption and significantly reduce the computational consumption compared with the existing similar literature.

Honeypot contract detection of blockchain based on deep learning

Hongxia ZHANG, Qi WANG, Dengyue WANG, Ben WANG

2022, 43(1):  194-202.  doi:10.11959/j.issn.1000-436x.2022011

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Aiming at the problems of low accuracy of current detection methods and poor generalization of model, a honeypot contract detection method based on KOLSTM deep learning model was proposed.Firstly, by analyzing the characteristics of honeypot contract, the concept of key opcode was proposed, and a keyword extraction method which could be used to select the key opcode in smart contract was designed.Secondly, by adding the key opcode weight mechanism to the traditional LSTM model, a KOLSTM model which could simultaneously capture the sequence features and key opcode features hidden in the honeypot contract was constructed.Finally, the experimental results show that the model had a high recognition accuracy.Compared with the existing methods, the F-score is improved by 2.39% and 19.54% respectively in the two classification and multi-classification detection scenes.

Correspondences

Statistics release and privacy protection method of location big data based on deep learning

Yan YAN, Yiming CONG, Mahmood Adnan, Quanzheng SHENG

2022, 43(1):  203-216.  doi:10.11959/j.issn.1000-436x.2022006

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Aiming at the problems of the unreasonable structure and the low efficiency of the traditional statistical partition and publishing of location big data, a deep learning-based statistical partition structure prediction method and a differential publishing method were proposed to enhance the efficacy of the partition algorithm and improve the availability of the published location big data.Firstly, the two-dimensional space was intelligently partitioned and merged from the bottom to the top to construct a reasonable partition structure.Subsequently, the partition structure matrices were organized as a three-dimensional spatio-temporal sequence, and the spatio-temporal characteristics were extracted via the deep learning model in a bid to realize the prediction of the partition structure.Finally, the differential privacy budget allocation and Laplace noise addition were implemented on the prediction partition structure to realize the privacy protection of the statistical partition and publishing of location big data.Experimental comparison of the real location big data sets proves the advantages of the proposed method in improving the querying accuracy of the published location big data and the execution efficiency of the publishing algorithm.

HRDA-Net: image multiple manipulation detection and location algorithm in real scene

Ye ZHU, Yilin YU, Yingchun GUO

2022, 43(1):  217-226.  doi:10.11959/j.issn.1000-436x.2022016

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Aiming at the problems that the fake image just contains one tampered operation in mainstream manipulation datasets and the artifact is a common problem in manipulation location.The multiple manipulation dataset (MM Dataset) was constructed for real scene, which contained both splicing and removal in each images.Based on this, an end-to-end high-resolution representation dilation attention network (HRDA-Net) was proposed for multiple manipulation detection and localization, which fused the RGB and SRM features through the top-down dilation convolutional attention (TDDCA).Finally, the mixed dilated convolution (MDC) would respectively extract the features of splicing and removal, which could realize multiple manipulation location and confidence prediction.The cosine similarity loss was proposed as auxiliary loss to improve the efficiency of network.Experimental results on MM Dataset indicate that the performance and robustness of HRDA-Net is better than semantic segmentation methods.Furthermore, the scores of F1 and AUC are greater than state-of-the-art manipulation location methods in CASIA and NIST datasets.