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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
    Abstract192)      PDF (912KB)(136)       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
    Abstract166)      PDF (1255KB)(334)       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
    Abstract209)      PDF (808KB)(182)       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
    Abstract161)      PDF (1086KB)(251)       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
    Abstract106)      PDF (1001KB)(88)       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
    Abstract176)      PDF (1128KB)(169)       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
    Abstract143)      PDF (1004KB)(157)       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
    Abstract106)      PDF (956KB)(319)       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
    Abstract153)      PDF (1102KB)(261)       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
    Abstract163)      PDF (916KB)(360)       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
    Abstract160)      PDF (1270KB)(430)       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
    Abstract155)      PDF (1133KB)(434)       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
    Abstract204)      PDF (950KB)(592)       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
    Abstract197)      PDF (994KB)(413)       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
    Abstract153)      PDF (1325KB)(713)       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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2023 Vol.43 No.1

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Honorary Editor-in-Chief: ZHANG Jingzhong
Editor-in-Chief: XU Zongben
Associate Editor: SHEN Hengtao XIA Zhaohui
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