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25 August 2022, Volume 43 Issue 8

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Papers

Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning

Wenjun XU, Silei WU, Fengyu WANG, Lan LIN, Guojun LI, Zhi ZHANG

2022, 43(8):  1-16.  doi:10.11959/j.issn.1000-436x.2022131

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In order to quickly restore emergency communication services for large-scale post-disaster users, a distributed intellicise coverage optimization architecture based on multi-agent reinforcement learning (RL) was proposed, which could address the significant differences and dynamics of communication services caused by a large number of access users, and the difficulty of expansion caused by centralized algorithms.Specifically, a distributed k-sums clustering algorithm considering service differences of users was designed in the network characterization layer, which could make each unmanned aerial vehicle base station (UAV-BS) adjust the local networking natively and simply, and obtain states of cluster center for multi-agent RL.In the trajectory control layer, multi-agent soft actor critic (MASAC) with distributed-training-distributed-execution structure was designed for UAV-BS to control trajectory as intelligent nodes.Furthermore, ensemble learning and curriculum learning were integrated to improve the stability and convergence speed of training process.The simulation results show that the proposed distributed k-sums algorithm is superior to the k-means in terms of average load efficiency and clustering balance, and MASAC based trajectory control algorithm can effectively reduce communication interruptions and improve the spectrum efficiency, which outperforms the existing RL algorithms.

Data popularity-based encrypted deduplication scheme without third-party servers

Guanxiong HA, Qiaowen JIA, Hang CHEN, Chunfu JIA

2022, 43(8):  17-29.  doi:10.11959/j.issn.1000-436x.2022151

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It is effective to balance data security and storage efficiency for setting different levels of security protection for data based on popularity in encrypted deduplication systems.Existing schemes all need introduce a trusted third-party for recording data popularity, while the third party is prone to a single point of failure and efficiency bottleneck.To address this problem, a popularity-based encrypted deduplication scheme without third-party servers was proposed, which accurately recorded the data popularity based on the Count-Min sketch algorithm and Merkle Puzzles protocol, and achieved encrypted deduplication of unpopular data through the sPAKE protocols performed among users.Security analysis and experimental evaluation show that the proposed scheme is secure and efficient.

Forwarding efficiency aware traffic scheduling algorithm based on deep reinforcement learning

Zongxuan SHA, Ru HUO, Chuang SUN, Shuo WANG, Tao HUANG

2022, 43(8):  30-40.  doi:10.11959/j.issn.1000-436x.2022148

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The software defined network separates the control plane from the data plane to achieve flexible traffic scheduling, which can use network resources more efficiently.However, with the increase of the number of flow entries, load rate, the number of connected hosts, and other factors, the forwarding efficiency of the SDN switch will be reduced, which will affect the end-to-end transmission delay.To solve the above problems, the forwarding efficiency aware traffic scheduling algorithm based on deep reinforcement learning was proposed.First, the switch state was integrated into the perception model, and the mapping relationship between switch state information and forwarding efficiency was established based on neural network.Then, combined with network state and traffic information, traffic scheduling policy was generated through deep reinforcement learning.Finally, the expert samples generated by the shortest path and load balance algorithms could guide the model training, which enabled the model to learn knowledge from expert samples to improve performance and accelerated the training process.The experimental results show that the proposed algorithm not only reduces the average end-to-end transmission delay by 15.31%, but also ensures the overall load balance of the network, compared with other algorithms.

Online placement algorithm of service function chain based on knowledge graph

Zexi XU, Lei ZHUANG, Kunli ZHANG, Mingyu GUI

2022, 43(8):  41-51.  doi:10.11959/j.issn.1000-436x.2022154

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The emergence of new network services such as immersive cloud XR and holographic communication puts forward higher requirements for network service quality.To ensure the availability of network services, the network service delay and reliability must be controlled within a certain quality of service according to the attributes and dependencies of network functions.However, the traditional network representation forms, such as bitmap and matrix, cannot cover these key network information, resulting in the information loss in the input stage of the algorithm, which leads to the deviation of the calculation results.Therefore, in order to accurately extract user needs and reflect the dynamic changes of network resources, knowledge graph was adopted to represent the network and its services, an online placement algorithm of service function chain based on knowledge graph was proposed.Based on this, a relationship alignment method based on editing distance was designed to guide the online placement of service function chains under complex dependency relationships.Experimental results show that the proposed algorithm can improve the placement accuracy of service function chain by 10%~15% and reduce the average network energy consumption by about 13%.The proposed algorithm has low complexity and high timeliness.

Multi-level local differential privacy algorithm recommendation framework

Hanyi WANG, Xiaoguang LI, Wenqing BI, Yahong CHEN, Fenghua LI, Ben NIU

2022, 43(8):  52-64.  doi:10.11959/j.issn.1000-436x.2022106

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Local differential privacy (LDP) algorithm usually assigned the same protection mechanism and parameters to different users.However, it ignored the differences among the device resources and the privacy requirements of different users.For this reason, a multi-level LDP algorithm recommendation framework was proposed.The server and the users’ requirements were considered in the framework, and the multi-users’ differential privacy protections were realized by the server and the users’ multi-level management.The framework was applied to the frequency statistics scenario to form an LDP algorithm recommendation scheme.LDP algorithm was improved to ensure the availability of statistical results, and a collaborative mechanism was designed to protect users’ privacy preferences.The experimental results demonstrate the availability of the proposed scheme.

Federated learning resource management for energy-constrained industrial IoT devices

Shaoshuai FAN, Jianbo WU, Hui TIAN

2022, 43(8):  65-77.  doi:10.11959/j.issn.1000-436x.2022126

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Given the impact of limited wireless resources, a dynamic multi-dimensional resource joint management algorithm was proposed, which intended to tackle the problem of device failure and training interruption caused by the limited battery energy in federated learning network in industrial Internet of things (IIoT).Firstly, the optimization problem was decoupled into battery energy allocation, equipment resource allocation and communication resource allocation sub-problems which were interdependent with the goal of maximizing the fixed-time learning accuracy.Then, the equipment transmission and computing resource allocation problem were solved based on particle swarm optimization algorithm under the given energy budget.Thereafter, the resource block iterative matching algorithm was proposed to optimize the optimal communication resource allocation strategy.Finally, the online energy allocation algorithm was proposed to adjust the energy budget allocation.Simulation results validate the proposed algorithm can improve the model learning accuracy compared with other benchmarks, and can perform better in energy shortage scenarios.

Fault tolerant GPS-AOA-SINS integrated navigation algorithm based on federated Kalman filter

Rui JIANG, Jun LI, Youyun XU, Xiaoming WANG, Dapeng LI

2022, 43(8):  78-89.  doi:10.11959/j.issn.1000-436x.2022147

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At present, global positioning system (GPS) was widely used in outdoor positioning.However, the continuous development of cities complicated the positioning environment, resulting in a sharp decline in positioning accuracy.Therefore, the integrated positioning scheme of GPS/5G base station angle of arrival positioning/strap-down inertial navigation system (GPS-AOA-SINS) was adopted, and a fault-tolerant integrated navigation algorithm based on federated Kalman filter was proposed.Based on the GPS-AOA-SINS integrated positioning scheme, the algorithm added fault detection between the federated Kalman sub filter and the main filter, and adaptively adjusted the filter gain matrix of the fault sub filter.Experiments show that the proposed algorithm can effectively detect system faults and deal with them in real time, so as to improve the reliability of the system.

Indoor RFID localization algorithm based on adaptive bat algorithm

Liangbo XIE, Yuyang LI, Yong WANG, Mu ZHOU, Wei NIE

2022, 43(8):  90-99.  doi:10.11959/j.issn.1000-436x.2022159

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Aiming at the problem that long time-consuming and poor positioning accuracy using geometric method in the traditional UHF RFID indoor localization algorithm, an RFID indoor positioning algorithm based on adaptive bat algorithm (ABA) was proposed.Firstly, the phase of multiple frequency points was obtained by frequency hopping technology, and the location evaluation function of bat algorithm was established based on the angle information of multiple signal classification (MUSIC) algorithm and the distance information of clustering.Secondly, the bat location was initialized by tent reverse learning to increase the diversity of the population, and the adaptive weight factor was introduced to update the bat location.Finally, the target position was searched iteratively based on the position evaluation function to achieve fast centimeter level positioning.Experimental results show that the median localization error of the proposed algorithm is 7.74 cm, and the real-time performance is improved by 12 times compared with the traditional positioning algorithm based on the Chinese remainder theorem (CRT).

Space-time division cluster DoA estimation algorithm based on UWA spread spectrum signal

Feng ZHOU, Baosheng ZHANG, Wenbo ZHANG

2022, 43(8):  100-108.  doi:10.11959/j.issn.1000-436x.2022164

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To solve the problems of poor stability, low resolution, and performance degradation under low signal-to-noise ratio (SNR) of the direction of arrival (DoA) estimation, a space-time division cluster (STDC) DoA estimation algorithm was proposed for under water acoustic (UWA) spread spectrum signal.The idea of the time-frequency two-dimensional search was used to combine the conventional beamforming with the spread spectrum sequence, set the angle interval to search the incidence angle and the arrival delay of the spread-spectrum signal, and increased the spatial spectrum to the delay angle spectrum, which kept the high resolution.STDC-DoA estimation can be anti-interference and stable operation under low SNR by using the characteristics of spread spectrum sequence.Finally, through simulation and pool experiment, it was proved that compared with the traditional DoA estimation algorithm, the proposed algorithm has better performance in anti-interference, resolution, and anti-noise.Meanwhile, the proposed algorithm does not need signal source number estimation and angle prediction and has more robust performance.

Quantum anonymous one-vote veto protocol based on BB84 states

Runhua SHI, Hui YU, Weiyang KE, Xiaotong XU

2022, 43(8):  109-120.  doi:10.11959/j.issn.1000-436x.2022157

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In order to construct unconditionally secure one-vote veto protocol, a primitive protocol of secure multiparty computations was defined, i.e., secure multiparty disjunction.Furthermore, by introducing a quantum cloud, a quantum secure multiparty disjunction (QSMD) protocol was proposed.BB84 states were took as quantum resources and only single-photon operations and measurements were needed.To avoid the flaws of infeasibility, i.e., most of existing quantum voting protocols need to perform operations and measurements in high-dimensional Hilbert space, a quantum anonymous one-vote veto protocol with a quantum cloud (QAOVC) was designed by using the QSMD protocol.In addition, to decentralize, a quantum anonymous one-vote veto (QAOV) protocol without any third party was presented.Compared with related protocols, the proposed protocols require less quantum resources and simpler operations, so they have better feasibility.Under the semi-honest model, quantum perfect encryption and classical one-time pad can ensure the unconditional security of the proposed protocols, i.e., it can completely meet secure requirements of one-vote veto and perfectly protect the privacy of the voters.Finally, simulation experiments are implemented on IBM Qiskit, and the experimental results show that the protocols are correct and feasible.

Research on power allocation of integrated VLPC based on deep reinforcement learning

Shuai MA, Bing LI, Haihong SHENG, Rongyan GU, Hui ZHOU, Hongmei WANG, Yue WANG, Shiyin LI

2022, 43(8):  121-130.  doi:10.11959/j.issn.1000-436x.2022163

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A power allocation scheme for integrated visible light position and communication (VLPC) system based on deep reinforcement learning was proposed to achieve power allocation for communication positioning integration.First, the frame structure design of integrated VLPC was proposed.Then the channel state information could be estimated by using the positioning information, and the CRLB of the positioning error was derived.Furthermore, the internal coupling relationship between positioning accuracy and communication rate was clarified.On this basis, a dynamic power allocation scheme based on deep deterministic policy gradient was proposed.Simulation results show that the proposed scheme can simultaneously achieve high-precision positioning and high-speed communication.

Privacy protection scheme based on fair blind signature and hierarchical encryption for consortium blockchain

Xuewang ZHANG, Zhihong LI, Jinzhao LIN

2022, 43(8):  131-141.  doi:10.11959/j.issn.1000-436x.2022162

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To solve the security hazards of identity information and transaction data and the time-consuming problem of traditional single-level encryption methods in the current application scenarios of consortium blockchain, a privacy protection scheme of consortium blockchain based on fair blind signature and hierarchical encryption was proposed.Considering the strong centrality and poor security of the existing fair blind signature scheme, it was redesigned with zero-knowledge proof technology to be applicable for consortium blockchain application scenario.Based on the Paillier homomorphic encryption algorithm, a supervisable hierarchical encryption method was designed, and the method realized the supervision of encrypted transaction data information and reduced the time cost of the encryption and decryption process.The security analysis and simulation results show that the proposed scheme can effectively resist malicious attacks such as tampering and eavesdropping and significantly improve the encryption efficiency.

Reconfigurable intelligent surface assist wireless channel estimation algorithm in Internet of vehicles environment

Rong ZENG, Xiao HANG

2022, 43(8):  142-150.  doi:10.11959/j.issn.1000-436x.2022150

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Aiming at the problem that multi-user channel estimation assisted by reconfigurable intelligent surface (RIS) in the uplink Internet of vehicles environment, a location assisted compressive sensing channel estimation algorithm was proposed.Based on the location information of the communication equipment, a single RIS-assisted single-user communication model was built, and the optimal phase shift matrix was derived according to the logical relationship between the beam angle of departure (AOD) and the angle of arrival (AOA).The perception matrix was constructed and channel estimation was performed, and finally it was extended to multi-user scenarios and solved iteratively.The optimal RIS phase shift matrix was solved based on the position information obtained by the Internet of vehicles technology, which reduced the additional training overhead of the channel and further reduces the complexity of the channel estimation.Simulation results show that the proposed algorithm based on location information has high channel estimation performance.

Influence maximization algorithm based on social network

Xuan WANG, Yu ZHANG, Junfeng ZHOU, Ziyang CHEN

2022, 43(8):  151-163.  doi:10.11959/j.issn.1000-436x.2022152

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The influence maximization (IM) problem asks for a group of seed users in a social network under a given propagation model, so that the information spread is maximized through these users.Existing algorithms have two main problems.Firstly, these algorithms were difficult to be applied in large-scale social networks due to limited expected influence and high time complexity.Secondly, these algorithms were limited to specific propagation models and could only solve the IM problem under a single type of social network.When they were used in different types of networks, the effect was poor.In this regard, an efficient algorithm (MTIM) based on two classic propagation models and reverse influence sampling (RIS) was proposed.To verify the effectiveness of MTIM, experiments were conducted to compare MTIM with greedy algorithms such as IMM, TIM and PMC, and heuristic algorithms such as OneHop and Degree Discount on four real social networks.The results show that MTIM can return a $\left(1-\frac{1}{\text{e}}-\epsilon \right)$ approximate solution, effectively expand the expected influence and significantly improve the efficiency.

Joint optimization of edge computing and caching in NDN

Yu ZHANG, Min CHENG

2022, 43(8):  164-175.  doi:10.11959/j.issn.1000-436x.2022160

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Named data networking (NDN) is architecturally easier to integrate with edge computing as its routing is based on content names and its nodes have caching capabilities.Firstly, an integrated framework was proposed for implementing dynamic coordination of networking, computing and caching in NDN.Then, considering the variability of content popularity in different regions, a matrix factorization-based algorithm was proposed to predict local content popularity, and deep reinforcement learning was used to solve the the problem of joint optimization for computing and caching resource allocation and cache placement policy with the goal of maximizing system operating profit.Finally, the simulation environment was built in ndnSIM.The simulation results show that the proposed scheme has significant advantages in improving cache hit rate, reducing the average delay and the load on the remote servers.

Covert communication method of blockchain network based on transaction construction and forwarding mechanism

Lizhi XIONG, Rong ZHU, Zhangjie FU

2022, 43(8):  176-187.  doi:10.11959/j.issn.1000-436x.2022161

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Aiming at the problems of multiple copies and permanent storage of the transactions containing secret information in the existing storage-based covert communication schemes in blockchain network, as well as the issue of low hidden capacity of the existing time-based schemes, a covert communication method of blockchain network based on transaction construction and forwarding mechanism was proposed.First, an invalid transaction was created by the sender with the help of the transaction construction mechanism, and the secret information was embedded in it, and then the transaction forwarding mechanism was used to send the invalid transaction to the neighbor nodes to form a covert communication channel model, enabling that the transactions containing secret information were spread between nodes and did not exist in the blockchain ledger, so as to achieve the purpose of information concealment and safe transmission.Experimental results show that the transmission capacity of the proposed method is higher than that of the existing schemes, and the single communication time is reduced to 2.5 s.

Comprehensive Reviews

Integrated sensing and communications for Internet of vehicles：current status and development trend

Xiang CHENG, Haotian ZHANG, Zonghui YANG, Ziwei HUANG, Sijiang LI, Anlan YU

2022, 43(8):  188-202.  doi:10.11959/j.issn.1000-436x.2022137

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The Internet of vehicles, the most important component of intelligent transportation system (ITS) in the future, is one of the most important technologies to achieve smart traffic and convenient travel for the people.With the vigorous development and continuous utilization of sensing and communication functions, the combination of these two functions, that is, integrated sensing and communications (ISAC) technology of vehicular communication networks, has become the current research hotspot and is of great significance to the development of ITS.Firstly, two different models of ISAC system, i.e., functional ISAC and signaling ISAC were defined and differentiated.Then, for the two different ISAC models, the existing works were reviewed and analyzed comprehensively.Finally, the future development directions and technical challenges of ISAC design in vehicular communication networks were proposed.

Survey of capacity limits and implementation techniques in wireless covert communication

Weiyu CHEN, Junshan LUO, Fanggang WANG, Haiyang DING, Shilian WANG, Guojiang XIA

2022, 43(8):  203-218.  doi:10.11959/j.issn.1000-436x.2022153

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The differences and connections between wireless covert communication (WCC) and related concepts were clarified.The WCC research based on hypothesis testing theory and information theory was focused.The basic research model and the categories of specific models were introduced.The existing works were classified and reviewed in two parts, namely, capacity limits and implementation techniques.The former part reviewed the works that reveal the limit rate, and divided them into two categories as per the order of the limit rate: squared root rate and positive rate.The latter part reviewed the works that analyze the performance of WCC systems and optimize the implementation schemes, and classified them as per their application scenarios.Finally, potential research directions were discussed.

Correspondences

Reversible data hiding in encrypted image based on bit-plane compression of prediction error

Youqing WU, Wenjing MA, Zhaoxia YIN, Yinyin PENG, Xinpeng ZHANG

2022, 43(8):  219-230.  doi:10.11959/j.issn.1000-436x.2022149

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To further improve the performance of reversible data hiding in encrypted image, an algorithm for lossless compression of the prediction error bit-plane using joint encoding was proposed, which could make full use of image redundancy and reserve more embedding room.Firstly, the image owner calculated the prediction error of the image and divided the prediction error bit-plane into non-overlapping blocks of the same size.Then, the prediction error bit-plane was rearranged according to blocks and the rearranged bitstream was compressed by run-length encoding and Huffman encoding to reserve room.The data hider embedded information in the reserved room of the encrypted image.At the receiving end, the legitimate receiver extracted information and recovered images losslessly and separately.Experimental results show that the proposed algorithm makes full use of the bit-plane distribution characteristics and achieves higher embedding performance.The average embedding rates in BOSSbase and BOWS-2 datasets reach 3.763 bpp and 3.642 bpp, which are at least 0.081 bpp and 0.058 bpp higher than the state-of-the-art algorithms.

Scheme and experiment of fast frequency hopping communication system based on SDR

Chengyu WEN, Conghui LIAO, Hang XIONG, Hong DU

2022, 43(8):  231-238.  doi:10.11959/j.issn.1000-436x.2022155

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A fast frequency hopping scheme based on SDR was proposed to solve the problem that the existing fast frequency hopping communication system relied on satellite timing.Firstly, a true random sequence was used to perform frequency hopping operation on the modulated signal in this scheme.And the frequency hopping table was obtained by channel down-conversion, low-pass filtering and amplitude peak detection operations.Secondly, the receiver searched for the precise starting point by the peak-to-peak distribution characteristics of the quadrature demodulation amplitude of the baseband signal after de-hopping.Finally, down-conversion was performed and the peak-to-peak amplitude of the quadrature demodulation was checked for exceeding the threshold value to achieve de-hopping for frequency hopping signals.The effectiveness and adaptability of the proposed scheme is verified by using two general-purpose SDR devices with a hopping rate of four hops per symbol period in a real channel with other continuous signals.