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    Time-varying channel estimation method based on sliding window filtering and polynomial fitting
    JING Xinghong, SUN Guodong, HE Shibiao, LIAO Yong
    Journal of Computer Applications    2021, 41 (9): 2699-2704.   DOI: 10.11772/j.issn.1001-9081.2020122035
    Abstract361)      PDF (912KB)(250)       Save
    The Long Term Evolution based Vehicle to Everything (LTE-V2X) standard follows the LTE standard's frame format and uses a block-type pilot assisted Single-Carrier Frequency-Division Multiple Access (SC-FDMA) system for channel estimation. However, due to the time-varying characteristics of the V2X channel, large technical challenges are brought to the channel estimation at the receiver. Therefore, a time-varying channel estimation method based on sliding window filtering and polynomial fitting was designed. Aiming at the noise problem at pilot symbols, based on Least Squares (LS) method, an adaptive-length sliding window filtering was adopted for noise reduction, so as to ensure the channel estimation accuracy of pilot symbols. Furthermore, according to the size of the Doppler frequency shift of data symbols, an adaptive-order polynomial fitting method was designed to track the channel changes at data symbols. The simulation results show that the proposed method has a good denoising effect based on LS method. In the case of low-speed movement, the estimation accuracy of the proposed method is between those of LS method and Linear Minimum Mean Square Error (LMMSE) method. In the case of high-speed movement, the proposed method can fit the time-varying channel characteristics better, and its performance exceeds that of the channel estimation method of LMMSE method combined with linear interpolation. The above results show that the proposed method has better adaptability than the comparison methods and is suitable for LTE-V2X communication scenarios with different channel noises and terminal moving speeds.
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    Local differential privacy protection mechanism for mobile crowd sensing with edge computing
    LI Zhuo, SONG Zihui, SHEN Xin, CHEN Xin
    Journal of Computer Applications    2021, 41 (9): 2678-2686.   DOI: 10.11772/j.issn.1001-9081.2020111787
    Abstract387)      PDF (1255KB)(465)       Save
    Aiming at the problem of the difficulty in privacy protection and the cost increase caused by privacy protection in the user data submission stage in Mobile Crowd Sensing (MCS), CS-MVP algorithm for joint privacy protection and CS-MAP algorithm for independent privacy protection of the attributes of user submitted data were designed based on the principle of Local Differential Privacy (LDP). Firstly, the user submitted privacy model and the task data availability model were constructed on the basis of the attribute relationships. And CS-MVP algorithm and CS-MAP algorithm were used to solve the availability maximization problem under the privacy constraint. At the same time, in the edge computing supported MCS scenarios, the three-layer architecture for MCS under privacy protection of the user submitted data was constructed. Theoretical analysis proves the optimality of the two algorithms under the data attribute joint privacy constraint and data attribute independent privacy constraint respectively. Experimental results show that under the same privacy budget and amount of data, compared with LoPub and PrivKV, the accuracy of user submitted data recovered to correct sensor data based on CS-MVP algorithm and CS-MAP algorithm is improved by 26.94%, 84.34% and 66.24%, 144.14% respectively.
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    Phase shift model design for 6G reconfigurable intelligent surface
    WANG Dan, LIANG Jiamin, LIU Jinzhi, ZHANG Youshou
    Journal of Computer Applications    2021, 41 (9): 2694-2698.   DOI: 10.11772/j.issn.1001-9081.2020111836
    Abstract468)      PDF (808KB)(362)       Save
    In order to solve the problem of high energy consumption of relay communication and high difficulty in the construction of 5G base stations, the research on Reconfigurable Intelligent Surface (RIS) technology was introduced in 6G mobile communication. Aiming at the problem of characteristic loss and instability of the truncated Hadamard matrix and Discrete Fourier Transform (DFT) matrix when constructing intelligent surfaces, a new RIS phase shift model design scheme of constructing unitary matrix based on Hankel matrix and Toeplitz matrix was proposed. The characteristics of the unitary matrix were used to minimize the channel error and improve the reliability of the communication channel. The simulation results show that compared with that of non-RIS-assisted communication, the user receiving rate of RIS-assisted communication can obtain a gain of 1 (bit·s -1)/Hz when the number of RIS units is 15. With the increase of the number of RIS units, the gain of the user receiving rate will be more and more significant. When the number of RIS units is 4, compared to the method of using DFT matrix to construct intelligent reflecting surfaces, the methods of using the two obtained unitary matrices to construct reflecting surfaces have higher reliability, and can obtain the performance gain of about 0.5 dB.
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    Deep learning-based joint channel estimation and equalization algorithm for C-V2X communications
    CHEN Chengrui, SUN Ning, HE Shibiao, LIAO Yong
    Journal of Computer Applications    2021, 41 (9): 2687-2693.   DOI: 10.11772/j.issn.1001-9081.2020111779
    Abstract393)      PDF (1086KB)(439)       Save
    In order to effectively improve the Bit Error Rate (BER) performance of communication system without significantly increasing the computational complexity, a deep learning based joint channel estimation and equalization algorithm named V-EstEqNet was proposed for Cellular-Vehicle to Everything (C-V2X) communication system by using the powerful ability of deep learning in data processing. Different from the traditional algorithms, in which channel estimation and equalization in the communication system reciever were carried out in two stages respectively, V-EstEqNet considered them jointly, and used the deep learning network to directly correct and restore the received data, so that the channel equalization was completed without explicit channel estimation. Specifically, a large number of received data were used to train the network offline, so that the channel characteristics superimposed on the received data were learned by the network, and then these characteristics were utilized to recover the original transmitted data. Simulation results show that the proposed algorithm can track channel characteristics more effectively in different speed scenarios. At the same time, compared with the traditional channel estimation algorithms (Least Squares (LS) and Linear Minimum Mean Square Error (LMMSE)) combining with the traditional channel equalization algorithms (Zero Forcing (ZF) equalization algorithm and Minimum Mean Square Error (MMSE) equalization algorithm), the proposed algorithm has a maximum BER gain of 6 dB in low-speed environment and 9 dB in high-speed environment.
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    Relay selection and performance analysis of multi-relay cooperative spatial modulation
    LI Tong, QIU Runhe
    Journal of Computer Applications    2021, 41 (7): 2019-2025.   DOI: 10.11772/j.issn.1001-9081.2020081238
    Abstract243)      PDF (1001KB)(176)       Save
    A relay selection scheme based on the location of relay node was proposed for the selection problem in a multi-relay cooperative Spatial Modulation (SM) system, and the Bit Error Rate (BER) performance of the system was analyzed. The SM technique was used at the source node by the system, only one transmitting antenna was activated in each time slot, and based on the location information of the relay node, the Amplify Forward (AF) relay closest to the midpoint between the source node and the destination node was selected among all relays in each time slot for forwarding. The approach of moment generating function was used to derive the solution of the pairwise error probability of the system under Rayleigh fading channel, and therefore the theoretical BER of the system was given. Simulation results show that this relay selection method can achieve better BER performance of the system compared with the relay random selection and cyclic forwarding methods.
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    Power allocation algorithm for CR-NOMA system based on tabu search and Q-learning
    ZHOU Shuo, QIU Runhe, TANG Minjun
    Journal of Computer Applications    2021, 41 (7): 2026-2032.   DOI: 10.11772/j.issn.1001-9081.2020081249
    Abstract350)      PDF (1128KB)(251)       Save
    For the demand of high speed and massive connections of next-generation mobile communication, improving the total secondary users' transmission rate by the optimization of power allocation in Cognitive Radio-Non-Orthogonal Multi-Access (CR-NOMA) hybrid system was studied, and an algorithm of Power Allocation based on Tabu Search and Q-learning (PATSQ) was proposed. Firstly, the users' power allocation was observed and learnt by the cognitive base station in the system environment, and the secondary users used NOMA to access the authorized channel. Then, the power allocation, channel state and total transmission rate in the power allocation problem were expressed as action, state and reward in the Markov decision process, which was solved by combining tabu search and Q-learning and an optimal tabu Q-table was obtained. Finally, under the constraints of primary and secondary users' Quality of Service (QoS) and maximum transmitting power, optimal power allocation factors were obtained by the cognitive base station by looking up the tabu Q-table, so as to maximize the total transmission rate of secondary users in the system. Simulation results show that under the same total power, the proposed algorithm is superior to Cognitive Mobile Radio Network (CMRN) algorithm, Secondary user First Decode Mode (SFDM) algorithm and the traditional equal power allocation algorithm in terms of the total transmission rate of secondary users and the number of users contained in the system.
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    Two-phase resource allocation technology for network slices in smart grid
    SHANG Fangjian, LI Xin, Di ZHAI, LU Yang, ZHANG Donglei, QIAN Yuwen
    Journal of Computer Applications    2021, 41 (7): 2033-2038.   DOI: 10.11772/j.issn.1001-9081.2020081343
    Abstract372)      PDF (1004KB)(317)       Save
    To satisfy the diverse demands of network slicing in smart grid, a slicing resource allocation model based on cloud-edge collaboration in smart grid was proposed. Furthermore, a two-phase cooperative slice allocation model was developed to optimize the allocation of the network slices. In the first phase, an optimization model for the resource allocation in local edge network was established to optimize the user experience, and the optimization problem was solved with the Lagrange multiplier method. In the second phase, the system was modeled as a Markov decision process, and then the deep reinforcement learning was adopted to adaptively allocate the resources to the slices of the core cloud. Experimental results show that the proposed two-phrase slice resource allocation model can effectively reduce the network delay and improve the user satisfaction.
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    Orthogonal matching pursuit hybrid precoding algorithm based on improved intelligent water drop
    LIU Ziyan, MA Shanshan, BAI He
    Journal of Computer Applications    2021, 41 (5): 1419-1424.   DOI: 10.11772/j.issn.1001-9081.2020071116
    Abstract233)      PDF (956KB)(420)       Save
    Focused on the problems of high hardware cost and high system overhead in the millimeter-Wave Massive Multi-Input Multi-Output (mmWave Massive MIMO) system, an Orthogonal Matching Pursuit based on improved Intelligent Water Drop (IWD-OMP) hybrid precoding algorithm was proposed. Firstly, based on Orthogonal Match Pursuit (OMP) algorithm, the precoding matrix was solved. Secondly, the improved Intelligent Water Drop (IWD) algorithm was adopted to calculate the global optimal index vector in the matrix. Finally, the matrix solved by this method did not need to construct the candidate matrix in advance, which was able to save the system resources and reduce the complexity of matrix calculation. Experimental results demonstrate that when the number of transmitting antennas is 128 and the signal-to-noise ratio is 28 dB, compared with the OMP algorithm, the proposed method has the system achievable sum rate performance improved by about 7.71%, when the signal-to-noise ratio is 8 dB, the proposed method has the bit error rate reduced by about 19.77%. In addition, the proposed precoding algorithm has strong robustness to the imperfect Channel State Information (CSI) in the real channel environment. When the signal-to-noise ratio value is 28 dB, the proposed method has the system achievable sum rate decreased by about 1.08% for imperfect CSI compared with that for perfect CSI.
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    Selected mapping method with embedded side information to reduce PAPR of FBMC signals
    XIA Yujie, SHI Yongpeng, GAO Ya, SUN Peng
    Journal of Computer Applications    2021, 41 (5): 1425-1431.   DOI: 10.11772/j.issn.1001-9081.2020081346
    Abstract301)      PDF (1102KB)(361)       Save
    To solve the problems of the poor reduction performance of Filter Bank MultiCarrier (FBMC) signals' Peak-to-Average Power Ratio (PAPR) and the high Side Information Error Rate (SIER) of the existing Selected Mapping (SLM) method to reduce PAPR signals, an SLM method with embedded Side Information (SI) was presented to reduce PAPR. At the transmitter, a group of phase rotation vectors with embedded SI were designed, and the candidate data blocks were generated by multiplying the phase rotation vectors with the transmitting data blocks. By using the outputs of Inverse Discrete Fourier Transform (IDFT) of the real and imaginary components of the candidate data blocks, the candidate FBMC signals based on cyclic time shift were designed and the candidate signal with the lowest PAPR was selected and transmitted. At the receiver, by using the difference between the phase rotations of the SI subcarrier data, a low-complexity SI detector unrelated to modulation order of transmitted symbols was proposed. Simulation results show that the proposed method can effectively reduce the PAPR of FBMC signals at the transmitter and obtain good SI detection and Bit Error Rate (BER) performances at the receiver.
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    Data center adaptive multi-path load balancing algorithm based on software defined network
    XU Hongliang, YANG Guiqin, JIANG Zhanjun
    Journal of Computer Applications    2021, 41 (4): 1160-1164.   DOI: 10.11772/j.issn.1001-9081.2020060845
    Abstract382)      PDF (916KB)(519)       Save
    The traditional multi-path load balancing algorithms cannot effectively perceive the running state of the network, cannot comprehensively consider the real-time transmission states of the links and most of them lack adaptability. In order to solve these problems, a Software Defined Network(SDN) adaptive multi-path Load Balancing Algorithm based on Spider Monkey Optimization(SMO-LBA) was proposed based on the idea of centralized control and whole network control of SDN. Firstly, the perceptul ability of data center network was used to obtain the multi-path real-time link state information. Then, based on the global exploration and local exploitation ability of spider monkey optimization algorithm, the link idle rate was used as the adaptability value of each path, and the paths were dynamically evaluated and updated by introducing the adaptive weight. Finally, the path with the lowest link occupancy rate in data center network was determined as the optimal forwarding path. The fat tree topology was selected to carry out the simulation experiment on Mininet platform. Experimental results show that SMO-LBA can improve the throughput and average link utilization of data center network, and realize the adaptive load balancing of the network.
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    Indoor intrusion detection based on direction-of-arrival estimation algorithm for single snapshot
    REN Xiaokui, LIU Pengfei, TAO Zhiyong, LIU Ying, BAI Lichun
    Journal of Computer Applications    2021, 41 (4): 1153-1159.   DOI: 10.11772/j.issn.1001-9081.2020071030
    Abstract343)      PDF (1270KB)(533)       Save
    Intrusion detection methods based on Channel State Information(CSI) are vulnerable to environment layout and noise interference, resulting in low detection rate. To solve this problem, an indoor intrusion detection method based on the algorithm of Direction-Of-Arrival(DOA) estimation for single snapshot was proposed. Firstly, the CSI data received by the antenna array was mathematically decomposed by combining the feature of spatial selective fading of the wireless signals, and the unknown DOA estimation problem was transformed into an over-complete representation problem. Secondly, the sparsity of the sparse signal was constrained by l1 norm, and the accurate DOA information was obtained by solving the sparse regularized optimization problem, so as to provide the reliable feature parameters for the final detection results at data level. Finally, the Indoor Safety Index Number(ISIN) was evaluated according to the DOA changes before and after the moments, and then indoor intrusion detection was realized. In the experiment, the method was verified by real indoor scenes and compared with traditional data preprocessing methods of principal component analysis and discrete wavelet transform. Experimental results show that the proposed method can accurately detect the occurrence of intrusion in different complex indoor environments, with an average detection rate of more than 98%, and has better performance in robustness compared to comparison algorithms.
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    Adaptive network transmission mechanism based on forward error correction
    ZHU Yongjin, YIN Fei, DOU Longlong, WU Kun, ZHANG Zhiwei, QIAN Zhuzhong
    Journal of Computer Applications    2021, 41 (3): 825-832.   DOI: 10.11772/j.issn.1001-9081.2020060948
    Abstract362)      PDF (1133KB)(563)       Save
    Aiming at the performance degradation of transmission performance of Transmission Control Protocol (TCP) in wireless network caused by the loss packet retransmission mechanism triggered by packet loss, an Adaptive transmission mechanism based on Forward Error Correction (AdaptiveFEC) was proposed. In the mechanism, the transmission performance of TCP was improved by the avoidance of triggering TCP loss packet retransmission mechanism, which realized by reducing data segment loss with forward error correction. Firstly, the optimal redundant segment ratio in current time was selected according to the current network status and the data transmission characteristics of the current connection. Then, the network status was estimated by analyzing the data segment sequence number in the TCP data segment, so that the redundant segment ratio was dynamically updated according to the network. Large number of experiment results show that, in the transmission environment with a round-trip delay of 20 ms and a packet loss rate of 5%, AdaptiveFEC can increase the transmission rate of TCP connection by 42% averagely compared to static forward error correction mechanism, and the download speed can be twice as much as the original speed with the proposed mechanism applied to file download applications.
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    Time of arrival positioning based on time reversal
    ZHANG Qilin, LI Fangwei, WANG Mingyue
    Journal of Computer Applications    2021, 41 (3): 820-824.   DOI: 10.11772/j.issn.1001-9081.2020060976
    Abstract393)      PDF (950KB)(707)       Save
    It is difficult for traditional algorithms to accurately find out the first direct path in indoor Ultra Wide Band (UWB) Time Of Arrival (TOA) positioning system, resulting in low positioning accuracy. In order to solve the problem, a TOA indoor UWB positioning algorithm based on Time Reversal (TR) was proposed. Firstly, the spatial-temporal focusing characteristic of TR processing was used to determine the first direct path, so as to estimate the TOA of this path. Then, the Weighted Least Squares (WLS) positioning algorithm was used to assign the corresponding weights to different estimation components for improving the positioning accuracy. The simulation results show that, compared with the traditional TOA positioning, the proposed scheme has the Root Mean Square Error (RMSE) reduced by 28.6% under the low signal-to-noise ratio condition. It can be seen that the proposed scheme improves the system positioning accuracy significantly.
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    Node redeployment strategy based on firefly algorithm for wireless sensor network
    SUN Huan, CHEN Hongbin
    Journal of Computer Applications    2021, 41 (2): 492-497.   DOI: 10.11772/j.issn.1001-9081.2020060803
    Abstract391)      PDF (994KB)(525)       Save
    Node deployment is one of the important problems in Wireless Sensor Network (WSN). Concerning the problem of energy hole in the process of node employment, a Node Redeployment Based on the Firefly Algorithm (NRBFA) strategy was proposed. Firstly, the k-means algorithm was used to cluster nodes and the redundant nodes were introduced into the sensor network where nodes are randomly deployed. Then, the Firefly Algorithm (FA) was used to move the redundant nodes to share the load of Cluster Heads (CHs) and balance the energy consumption of nodes in the network. Finally, the redundant nodes were updated after finding the target node by reusing the FA. In the proposed strategy, the reduction of moving distances of nodes and the decrease of the network energy consumption were achieved through moving the redundant nodes effectively. Experimental results show that the proposed strategy can alleviate the "energy hole" problem effectively. Compared with the partition node redeployment algorithm based on virtual force, the proposed strategy reduces the complexity of the algorithm, and can better improve the energy efficiency of the network, balance the network load, as well as prolong the network lifetime by nearly 10 times.
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    Forward collision warning strategy based on vehicle-to-vehicle communication
    HUI Fei, XING Meihua, GUO Jing, TANG Shuyu
    Journal of Computer Applications    2021, 41 (2): 498-503.   DOI: 10.11772/j.issn.1001-9081.2020060773
    Abstract314)      PDF (1325KB)(837)       Save
    In the delay time of the Forward Collision Warning (FCW) system under Vehicle-to-Vehicle (V2V) communication, the traditional model assumes uniform speed of the host vehicle and error-free Global Positioning System (GPS), so as to significantly underestimate the risk of collision. Aiming at this problem, a new FCW strategy was proposed with correcting GPS errors and considering the movement state of the host vehicle within the delay time. Firstly, the overall workflow of the FCW system based on V2V communication was analyzed, and the key delays in the system were modeled by using the Gaussian model. Then, a collision avoidance model was established with correcting GPS errors and taking the movement state of the host vehicle within the delay time into consideration. And different warning strategies were formulated corresponding to three scenarios of the constant speed, acceleration and deceleration of the remote vehicle. Finally, in view of the situation where the host vehicle accelerated in the delay time, Matlab was used to simulate the proposed FCW strategy. Simulation results show that the average successful collision avoidance rate of the proposed warning strategy can reach 96%, verifying the effectiveness of it in different scenarios.
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    Channel estimation based on compressive sensing in RIS-assisted millimeter wave system
    Yi WANG, Liu YANG, Tongkuai ZHANG
    Journal of Computer Applications    2022, 42 (12): 3870-3875.   DOI: 10.11772/j.issn.1001-9081.2021101808
    Abstract421)   HTML11)    PDF (1756KB)(228)       Save

    Since the pilot overhead using traditional channel estimation methods in the Reconfigurable Intelligent Surface (RIS)-assisted wireless communication systems is excessively high, a block sparseness based Orthogonal Matching Pursuit (OMP) channel estimation scheme was proposed. Firstly, according to the millimeter Wave (mmWave) channel model, the cascaded channel matrix was derived and transformed into the Virtual Angular Domain (VAD) to obtain the sparse representation of the cascaded channels. Secondly, by utilizing the sparse characteristics of the cascaded channels, the channel estimation problem was transformed into the sparse matrix recovery problem, and the reconstruction algorithm based on compressive sensing was adopted to recover the sparse matrix. Finally, the special row-block sparse structure was analyzed, and the traditional OMP scheme was optimized to further reduce pilot overhead and improve estimation performance. Simulation results show that the Normalized Mean Squared Error (NMSE) of the proposed optimized OMP scheme based on the row-block sparse structure decreases about 1 dB compared with that of the conventional OMP scheme. Therefore, the proposed channel estimation scheme can effectively reduce pilot overhead and obtain better estimation performance.

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    Data center flow scheduling mechanism based on differential evolution and ant colony optimization algorithm
    Rongrong DAI, Honghui LI, Xueliang FU
    Journal of Computer Applications    2022, 42 (12): 3863-3869.   DOI: 10.11772/j.issn.1001-9081.2021101766
    Abstract308)   HTML10)    PDF (2071KB)(114)       Save

    As the traditional flow scheduling method for data center network is easy to cause network congestion and link load imbalance, a dynamic flow scheduling mechanism based on Differential Evolution (DE) and Ant Colony Optimization (ACO) algorithm (DE-ACO) was proposed to optimize elephant flow scheduling in data center networks. Firstly, Software Defined Network (SDN) technology was used to capture the real-time network status information and set the optimization objectives of flow scheduling. Then, DE algorithm was redefined by the optimization objectives, several available candidate paths were calculated and used as the initialized global pheromone of the ACO algorithm. Finally, the global optimal path was obtained by combining with the global network status, and the elephant flow on the congested link was rerouted. Experimental results show that compared with Equal-Cost Multi-Path routing (ECMP) algorithm and network flow scheduling algorithm of SDN data center based on ACO algorithm (ACO-SDN), the proposed algorithm increases the average bisection bandwidth by 29.42% to 36.26% and 5% to 11.51% respectively in random communication mode, reducing the Maximum Link Utilization (MLU) of the network, and achieving better load balancing of the network.

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    Joint optimization of user association and resource allocation in cognitive radio ultra-dense networks to improve genetic algorithm
    Junjie ZHANG, Runhe QIU
    Journal of Computer Applications    2022, 42 (12): 3856-3862.   DOI: 10.11772/j.issn.1001-9081.2021101777
    Abstract237)   HTML7)    PDF (2848KB)(52)       Save

    Aiming at the multi-dimensional resource allocation problem in the downlink heterogeneous cognitive radio Ultra-Dense Network (UDN), an improved genetic algorithm was proposed to jointly optimize user association and resource allocation with the objective of maximizing the throughput of femtocell users. Firstly, preprocessing was performed before the algorithm running to initialize the user’s reachable base stations and available channels matrix. Secondly, symbol coding was used to encode the matching relationships between the user and the base stations as well as the user and the channels into a two-dimensional chromosome. Thirdly, dynamic choosing best for replication + roulette was used as the selection algorithm to speed up the convergence of the population. Finally, in order to avoid the algorithm from falling into the local optimum, the mutation operator of premature judgment was added in the mutation stage, so that the connection strategy of base station, user and channel was obtained with limited number of iterations. Experimental results show that when the numbers of base stations and channels are fixed, the proposed algorithm improves the total user throughput by 7.2% and improves the cognitive user throughput by 1.2% compared with the genetic algorithm of three-dimensional matching, and the computational complexity of the proposed algorithm is lower. The proposed algorithm reduces the search space of feasible solutions, and can effectively improve the total throughput of cognitive radio UDNs with lower complexity.

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    Sink location algorithm of power domain nonorthogonal multiple access for real-time industrial internet of things
    SUN Yuan, SHEN Wenjian, NI Pengbo, MAO Min, XIE Yaqi, XU Chaonong
    Journal of Computer Applications    2023, 43 (1): 209-214.   DOI: 10.11772/j.issn.1001-9081.2021111946
    Abstract256)   HTML11)    PDF (2234KB)(91)       Save
    Aiming at the shortcoming of large access delay in industrial Internet of Things (IoT), a sink location algorithm of Power Domain NonOrthogonal Multiple Access (PD-NOMA) for real-time industrial IoT was proposed. In this algorithm, based on the PD-NOMA technology, the location of the sink was used as an optimization method to minimize access delay by realizing power division multiplexing among users as much as possible. Firstly, for any two users, an assertion that the decodable area of the qualified sink must be a circle if parallel transmissions are successful was proven, and therefore, the decodable area set of the sink was able to be obtained by combining all of the combinations of two users, and every minimal intersection of the area set must be a convex region. So, the optimal location of the sink must be included in these minimal intersection areas. Secondly, for each minimal intersection area where the sink was deployed, the minimum number of chain partition of the network generation graph in the area was computed and used as the metric for evaluating the access delay. Finally, the optimal location of the sink was determined by comparing these minimum number of chain partitioning. Experimental results show that when the decoding threshold is 2 and the number of users is 30, the average access delay of the proposed algorithm is about 36.7% of that of the classic time division multiple access, and besides, it can be decreased almost linearly with the decrease of the decoding threshold and the increase of the channel decay factor. The proposed algorithm can provide reference from the access layer perspective for massive ultra-reliable low-latency communications.
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    Design and implementation of block transmission mechanism based on remote direct memory access
    Dong SUN, Biao WANG, Yun XU
    Journal of Computer Applications    2023, 43 (2): 484-489.   DOI: 10.11772/j.issn.1001-9081.2021122243
    Abstract353)   HTML15)    PDF (1890KB)(104)       Save

    With the continuous development of blockchain technology, the block transmission delay has become a performance bottleneck of the scalability of the blockchain system. Remote Direct Memory Access (RDMA) technology, which supports high-bandwidth and low-delay data transmission, provides a new idea for block transmission with low latency. Therefore, a block catalogue structure for block information sharing was designed based on the characteristics of RDMA primitives, and the basic working process of block transmission was proposed and implemented on this basis. Experimental results show that compared with TCP(Transmission Control Protocol) transmission mechanism, the RDMA-based block transmission mechanism reduces the transmission delay between nodes by 44%, the transmission delay among the whole network by 24.4% on a block of 1 MB size, and the number of temporary forks appeared in blockchain by 22.6% on a blockchain of 10 000 nodes. It can be seen that the RDMA-based block transmission mechanism takes advantage of the performance of high speed networks, reduces block transmission latency and the number of temporary forks, thereby improving the scalability of the existing blockchain systems.

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    Service function chain deployment optimization method based on node comprehensive importance ranking
    Haiyan HU, Qiaoyan KANG, Shuo ZHAO, Jianfeng WANG, Youbin FU
    Journal of Computer Applications    2023, 43 (3): 860-868.   DOI: 10.11772/j.issn.1001-9081.2022020257
    Abstract242)   HTML6)    PDF (3406KB)(120)       Save

    In order to meet the requirements of high reliability and low latency in the 5G network environment, and reduce the resource consumption of network bandwidth at the same time, a Service Function Chain (SFC) deployment method based on node comprehensive importance ranking for traffic and reliability optimization was proposed. Firstly, Virtualized Network Function (VNF) was aggregated based on the rate of traffic change, which reduced the deployed physical nodes and improved link reliability. Secondly, node comprehensive importance was defined by the degree, reliability, comprehensive delay and link hop account of the node in order to sort the physical nodes. Then, the VNFs were mapped to the underlying physical nodes in turn. At the same time, by restricting the number of links, the “ping-pong effect” was reduced and the traffic was optimized. Finally, the virtual link was mapped through k-shortest path algorithm to complete the deployment of the entire SFC. Compared with the original aggregation method, the proposed method has the SFC reliability improved by 2%, the end-to-end delay of SFC reduced by 22%, the bandwidth overhead reduced by 29%, and the average long-term revenue-to-cost ratio increased by 16%. Experimental results show that the proposed method can effectively improve the link reliability, reduce end-to-end delay and bandwidth resource consumption, and play a good optimization effect.

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    Greedy synchronization topology algorithm based on formal concept analysis for traffic surveillance based sensor network
    Qing YE, Xin SHI, Mengwei SUN, Jian ZHU
    Journal of Computer Applications    2023, 43 (3): 869-875.   DOI: 10.11772/j.issn.1001-9081.2022010141
    Abstract233)   HTML4)    PDF (1587KB)(69)       Save

    Aiming at the energy efficiency and scene adaptability problems of synchronization topology, a Greedy Synchronization Topology algorithm based on Formal Concept Analysis for traffic surveillance based sensor network (GST-FCA) was proposed. Firstly, scene adaptability requirements and energy efficiency model of the synchronization topology in traffic surveillance based sensor network were analyzed. Secondly, correlation analysis was performed on the adjacent features of sensor nodes in the same layer and adjacent layers by using Formal Concept Analysis (FCA). Afterward, Broadcast Tuples (BT) were built and synchronization sets were divided according to the greedy strategy with the maximum number of neighbors. Thirdly, a backtracking broadcast was used to improve the broadcast strategy of layer detection in Timing-synchronization Protocol of Sensor Network (TPSN) algorithm. Meanwhile, an upward hosting mechanism was designed to not only extend the information sharing range of synchronous nodes but also further alleviate the locally optimal solution problem caused by the greedy strategy. Finally, GST-FCA was verified and tested in terms of energy efficiency and scene adaptability. Simulation results show that compared with algorithms such as TPSN, Linear Estimation of Clock Frequency Offset (LECFO), GST-FCA decreases the synchronization packet overhead by 11.54%, 24.59% and 39.16% at lowest in the three test scenarios of deployment location, deployment scale and road deployment. Therefore, GST-FCA can alleviate the locally optimal solution problem and reduce the synchronization packet overhead, and it is excellent in energy efficiency when the synchronization topology meets the scene adaptability requirements of the above three scenarios.

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    Fast link failure recovery method for software-defined internet of vehicles
    Yuan GU, Zhen ZHANG, Tong DUAN
    Journal of Computer Applications    2023, 43 (3): 853-859.   DOI: 10.11772/j.issn.1001-9081.2022010058
    Abstract284)   HTML5)    PDF (2543KB)(72)       Save

    Aiming at the single link failure problem in the vehicle-road real-time query communication scenario of Software-Defined Internet of Vehicles (SDIV), a fast link failure recovery method for SDIV was proposed, which considered link recovery delay and path transmission delay after link recovery. Firstly, the failure recovery delay was modeled, and the optimization goal of minimizing the delay was transformed into a 0-1 integer linear programming problem. Then, this problem was analyzed, two algorithms were proposed according to different situations, which tried to maximize the reuse of the existing calculation results. In specific, Path Recovery Algorithm based on Topology Partition (PRA-TP) was proposed when the flow table update delay was not able to be ignored compared with the path transmission delay, and Path Recovery Algorithm based on Single Link Search (PRA-SLS) was proposed when the flow table update delay was negligible because being farless than the path transmission delay. Experimental results show that compared with Dijkstra algorithm, PRA-TP can reduce the algorithm calculation delay by 25% and the path recovery delay by 40%, and PRA-SLS can reduce the algorithm calculation delay by 60%, realizing fast single link failure recovery at vehicle end.

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    Multivariate communication system based on discrete bidirectional associative memory neural network
    Weikang CHEN, Qiqing ZHAI, Youguo WANG
    Journal of Computer Applications    2023, 43 (3): 848-852.   DOI: 10.11772/j.issn.1001-9081.2022010151
    Abstract212)   HTML6)    PDF (2244KB)(56)       Save

    Aiming at the problem that noise increases the error probability of the transmission signals of nonlinear digital communication system, a multivariate communication system based on discrete Bidirectional Associative Memory (BAM) neural network was proposed. Firstly, the appropriate number of neurons and memory vectors were selected according to the signals to be transmitted, the weight matrix was calculated, and BAM neural network was generated. Secondly, the multivariate signals were mapped to the initial input vectors with modulation amplitude and continuously input into the system. The input was iterated through the neural network and Gaussian noise was added to each neuron. After that, the output was sampled according to the code element interval, and then transmitted in the lossless channel, and the decision was decoded by the receiver according to the decision rule. Finally, in the field of image processing, the proposed system was used to transmit the compressed image data and decode the recovered image. Simulation results show that for weakly modulated signals with large code element interval, with the increase of noise intensity, the error probability firstly decreases and then increases, and the stochastic resonance phenomenon is relatively obvious. At the same time, the error probability is positively correlated with the radix number of the signal, and negatively correlated with the signal amplitude, code element interval and the number of neurons. Under certain conditions, the error probability can reach 0. These results show that BAM neural network can improve the reliability of digital communication system through noise. In addition, the similarity of the image restored by decoding shows the improvement of moderate noise on image restoration effect, extending the application of BAM neural network and stochastic resonance in image compression coding.

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    Wireless traffic prediction based on federated learning
    Shangjing LIN, Ji MA, Bei ZHUANG, Yueying LI, Ziyi LI, Tie LI, Jin TIAN
    Journal of Computer Applications    2023, 43 (6): 1900-1909.   DOI: 10.11772/j.issn.1001-9081.2022050721
    Abstract386)   HTML15)    PDF (4071KB)(258)       Save

    Wireless communication network traffic prediction is of great significance to operators in network construction, base station wireless resource management and user experience improvement. However, the existing centralized algorithm models face the problems of complexity and timeliness, so that it is difficult to meet the traffic prediction requirements of the whole city scale. Therefore, a distributed wireless traffic prediction framework under cloud-edge collaboration was proposed to realize traffic prediction based on single grid base station with low complexity and communication overhead. Based on the distributed architecture, a wireless traffic prediction model based on federated learning was proposed. Each grid traffic prediction model was trained synchronously, JS (Jensen-Shannon) divergence was used to select grid traffic models with similar traffic distributions through the center cloud server, and Federated Averaging (FedAvg) algorithm was used to fuse the parameters of the grid traffic models with similar traffic distributions, so as to improve the model generalization and describe the regional traffic accurately at the same time. In addition, as the traffic in different areas within the city was highly differentiated in features, on the basis of the algorithm, a federated training method based on coalitional game was proposed. Combined with super-additivity criteria, the grids were taken as participants in the coalitional game, and screened. And the core of the coalitional game and the Shapley value were introduced for profit distribution to ensure the stability of the alliance, thereby improving the accuracy of model prediction. Experimental results show that taking Short Message Service (SMS) traffic as an example, compared with grid-independent training, the proposed model has the prediction error decreased most significantly in the suburb, with a decline range of 26.1% to 28.7%, the decline range is 0.7% to 3.4% in the urban area, and 0.8% to 4.7% in the downtown area. Compared with the grid-centralized training, the proposed model has the prediction error in the three regions decreased by 49.8% to 79.1%.

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    Time synchronization method based on precision time protocol in industrial wireless sensor networks
    Feiqiao SHAN, Zhaowei WANG, Yue SHEN
    Journal of Computer Applications    2023, 43 (7): 2255-2260.   DOI: 10.11772/j.issn.1001-9081.2022060825
    Abstract249)   HTML4)    PDF (1545KB)(107)       Save

    Concerning the dynamic change of link delay, clock timing interference, and uncertainty of timestamp acquisition caused by complex link environment and temperature fluctuation in Industrial Wireless Sensor Networks (IWSNs), a time synchronization method based on Precision Time Protocol (PTP) in IWSNs was proposed. Firstly, the clock state space model and observation model were constructed by integrating the clock timing interference and asymmetric link delay noise in PTP bidirectional time synchronization process. Secondly, a reverse adaptive Kalman filter algorithm was constructed to remove the noise interference. Thirdly, the rationality of the noise statistical model was evaluated by using the clock state normalized innovation ratio of the reverse estimation and the forward estimation. Finally, the process noise of the clock state was dynamically adjusted after setting the detection threshold, thereby achieving precise estimation of clock parameters. Simulation results show that compared with the classical Kalman filter algorithm and PTP protocol, the proposed algorithm has the clock offset and skew estimation with smaller and more stable error standard deviations under different clock timing precision. The reverse adaptive Kalman filter can effectively solve the problem of Kalman filter divergence caused by reasons such as noise uncertainty, and improve the reliability of time synchronization.

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    Physical layer security precoding design based on channel state information in passive eavesdropping scenario
    Hongliang FU, Chaonan KANG, Weiliang HAN, Yang WANG
    Journal of Computer Applications    2023, 43 (S1): 182-186.   DOI: 10.11772/j.issn.1001-9081.2022091383
    Abstract126)   HTML0)    PDF (1450KB)(91)       Save

    In the multipath channel scenario of passive eavesdropping, the EaVEsdropper (Eve) only performs passive eavesdropping without transmitting any radio signals. The transmitter (Alice) is unable to determine any information of Eve, which brings great challenges to the secure transmission of information. In order to guarantee the secure transmission of information, under the condition that Alice knew the Channel State Information (CSI) of the legitimate receiver (Bob) but not Eve’s CSI, a precoding scheme to guarantee the physical layer security of legitimate Bob was proposed, and the security performance of the system was improved by enhancing the quality of the received signals of Bob. Firstly, without considering Eve, the precoding scheme for the upper bound on the reachable channel capacity of Bob was given based on the known CSI of Bob. Stable security capacity was obtained by using the channel specificity between Alice-Bob and Alice-Eve links. Then, the accurate closed-form expression for Bob’s average Bit Error Rate (BER) was derived from Bob’s outage probability in a Rayleigh flat fading environment. Simulation experimental results show that the proposed scheme can ensure Bob’s channel capacity always better than Eve’s channel capacity without changing the complexity of the receiver. At the same time, the proposed scheme can effectively improve the BER performance of Bob under the condition that the BER performance of Eve is greatly suppressed. And the security capacity is always guaranteed even when the Eve’s location condition is better than that of Bob.

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    Hybrid beamforming for multi-user mmWave relay networks using deep learning
    Xiaolin LI, Songjia YANG
    Journal of Computer Applications    2023, 43 (8): 2511-2516.   DOI: 10.11772/j.issn.1001-9081.2022081231
    Abstract247)   HTML11)    PDF (1678KB)(173)       Save

    In order to solve the problem of high computational complexity of traditional multi-user mmWave relay system beamforming methods, a Singular Value Decomposition (SVD) method based on Deep Learning (DL) was proposed to design hybrid beamforming for the optimization of the transmitter, relay and receiver. Firstly, DL method was used to design the beamforming matrix of transmitter and relay to maximize the achievable spectral efficiency. Then, the beamforming matrix of relay and receiver was designed to maximize the equivalent channel gain. Finally, a Minimum Mean Square Error (MMSE) filter was designed at the receiver to eliminate the inter-user interference. Theoretical analysis and simulation results show that compared with Alternating Maximization (AltMax) and the traditional SVD method, the hybrid beamforming method based on DL reduces the computational complexity by 12.5% and 23.44% respectively in the case of high dimensional channel matrix and many users, and has the spectral efficiency improved by 2.277% and 21.335% respectively with known Channel State Information (CSI), and the spectral efficiency improved by 11.452% and 43.375% respectively with imperfect CSI.

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    β-QoM target-barrier coverage construction algorithm for wireless visual sensor network
    Xinming GUO, Rui LIU, Fei XIE, Deyu LIN
    Journal of Computer Applications    2023, 43 (9): 2877-2884.   DOI: 10.11772/j.issn.1001-9081.2023010084
    Abstract189)   HTML8)    PDF (4482KB)(47)       Save

    Focusing on the failure of intrusion detection resulted from low captured image width of traditional Wireless Visual Sensor Network (WVSN) target-barrier, a Wireless visual sensor network β Quality of Monitoring (β-QoM) Target-Barrier coverage Construction (WβTBC) algorithm was proposed to ensure that the captured image width is not less than β. Firstly, the geometric model of the visual sensor β-QoM region was established, and it was proven that the width of intruder image captured by the target-barrier of intersection of all adjacent visual sensor β-QoM regions must be greater than or equal to β. Then, based on the linear programming modeling for optimal β-QoM target-barrier coverage of WVSN, it was proven that this coverage problem is NP-hard. Finally, in order to obtain suboptimal solution of the problem, a heuristic algorithm WβTBC was proposed. In this algorithm, the directed graph of WVSN was constructed according to the counterclockwise β neighbor relationship between sensors, and Dijkstra algorithm was used to search β-QoM target-barriers in WVSN. Experimental results show that WβTBC algorithm can construct β-QoM target-barriers effectively, and save about 23.3%, 10.8% and 14.8% sensor nodes compared with Spiral Periphery Outer Coverage (SPOC), Spiral Periphery Inner Coverage (SPIC) and Target-Barrier Construction (TBC) algorithms, respectively. In addition, under the condition of meeting the requirements of intrusion detection, with the use of WβTBC algorithm, the smaller β is, the higher success rate of building β-QoM target-barrier will be, the fewer nodes will be needed in forming the barrier, and the longer working period of WVSN for β-QoM intrusion detection will be.

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    Trade-off between energy efficiency and spectrum efficiency for decode-and-forward full-duplex relay network
    Qian ZHANG, Runhe QIU
    Journal of Computer Applications    2023, 43 (10): 3188-3194.   DOI: 10.11772/j.issn.1001-9081.2022091414
    Abstract170)   HTML10)    PDF (1778KB)(71)       Save

    In order to optimize the Energy Efficiency (EE) and Spectrum Efficiency (SE) of Decode-and-Forward (DF) full-duplex relay network, a trade-off method of EE and SE for DF full-duplex relay network was proposed. In full-duplex relay network, firstly, the EE of the network was optimized with the goal of improving the SE of the network. And the optimal power of the relay was obtained by combining the derivation and the Newton-Raphson method, then the Pareto optimal set of the objective function was given. Secondly, a trade-off factor was introduced through the weighted scalar method, a trade-off optimization function of EE and SE was constructed, and the multi-objective optimization problem of EE optimization and SE optimization was transformed into a single-objective energy-spectrum efficiency optimization problem by using normalization. At the same time, the performance of EE, SE and trade-off optimization under different trade-off factor was analyzed. Simulation results show that the SE and EE of the proposed method are higher at the same data transmission rate compared with the those of the full-duplex-optimal power method and the half-duplex-optimal relay-optimal power allocation method. By adjusting different trade-off factors, the optimal trade-off and the optimization of EE and SE can be achieved.

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2024 Vol.44 No.5

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Honorary Editor-in-Chief: ZHANG Jingzhong
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