In order to improve the physical layer security of the device-to-device(D2D)cellular network,we propose a collaborative scheme for the transmit antenna selection and the optimal D2D pair establishment based on deep le...In order to improve the physical layer security of the device-to-device(D2D)cellular network,we propose a collaborative scheme for the transmit antenna selection and the optimal D2D pair establishment based on deep learning.Due to the mobility of users,using the current channel state information to select a transmit antenna or establish a D2D pair for the next time slot cannot ensure secure communication.Therefore,in this paper,we utilize the Echo State Network(ESN)to select the transmit antenna and the Long Short-Term Memory(LSTM)to establish the D2D pair.The simulation results show that the LSTMbased and ESN-based collaboration scheme can effectively improve the security capacity of the cellular network with D2D and increase the life of the base station.展开更多
This paper is a survey of transmit antenna selection-a low-complexity, energy-efficient method for improving physical layer security in multiple-input multiple-output wiretap channels. With this method, a single anten...This paper is a survey of transmit antenna selection-a low-complexity, energy-efficient method for improving physical layer security in multiple-input multiple-output wiretap channels. With this method, a single antenna out of multiple antennas is selected at the transmitter. We review a general analytical framework for analyzing exact and asymptotic secrecy of transmit antenna selection with receive maximal ratio combining, selection combining, or generalized selection combining. The analytical results prove that secrecy is significantly improved when the number of transmit antennas increases.展开更多
Maximal-ratio transmission systems with transmit antenna selection is investigated. According to the order statistics of channel fiat fading coefficients, the closed-form expressions axe derived for average SNR with a...Maximal-ratio transmission systems with transmit antenna selection is investigated. According to the order statistics of channel fiat fading coefficients, the closed-form expressions axe derived for average SNR with any amount of RF chains and average BER with two RF chains, respectively. The algorithm for calculating the minimum of total transmit antennas is presented in terms of reduced RF chains. The method of quantizing transmit precoders is employed in this study to decrease feedback information. Simulation results demonstrate the superiority of the proposed systems under full and quantized transmit precoders. The SNR of the proposed systems has been less degraded by the quantization of transmit precoder than that of pure maximal-ratio transmission systems.展开更多
基金supported in part by the Aerospace Science and Technology Innovation Fund of China Aerospace Science and Technology Corporationin part by the Shanghai Aerospace Science and Technology Innovation Fund (No. SAST2018045, SAST2016034, SAST2017049)+1 种基金in part by the China Fundamental Research Fund for the Central Universities (No. 3102018QD096)in part by the Seed Foundation of Innovation and Creation for Graduate Students in Northwestern Polytechnical University (No. ZZ2019024)
文摘In order to improve the physical layer security of the device-to-device(D2D)cellular network,we propose a collaborative scheme for the transmit antenna selection and the optimal D2D pair establishment based on deep learning.Due to the mobility of users,using the current channel state information to select a transmit antenna or establish a D2D pair for the next time slot cannot ensure secure communication.Therefore,in this paper,we utilize the Echo State Network(ESN)to select the transmit antenna and the Long Short-Term Memory(LSTM)to establish the D2D pair.The simulation results show that the LSTMbased and ESN-based collaboration scheme can effectively improve the security capacity of the cellular network with D2D and increase the life of the base station.
文摘This paper is a survey of transmit antenna selection-a low-complexity, energy-efficient method for improving physical layer security in multiple-input multiple-output wiretap channels. With this method, a single antenna out of multiple antennas is selected at the transmitter. We review a general analytical framework for analyzing exact and asymptotic secrecy of transmit antenna selection with receive maximal ratio combining, selection combining, or generalized selection combining. The analytical results prove that secrecy is significantly improved when the number of transmit antennas increases.
基金the National Natural Science Foundation of China (60472103)Shanghai Excellent Academic Leader Project (05XP14027)Shanghai Leading Academic Discipline Project(T0102).
文摘Maximal-ratio transmission systems with transmit antenna selection is investigated. According to the order statistics of channel fiat fading coefficients, the closed-form expressions axe derived for average SNR with any amount of RF chains and average BER with two RF chains, respectively. The algorithm for calculating the minimum of total transmit antennas is presented in terms of reduced RF chains. The method of quantizing transmit precoders is employed in this study to decrease feedback information. Simulation results demonstrate the superiority of the proposed systems under full and quantized transmit precoders. The SNR of the proposed systems has been less degraded by the quantization of transmit precoder than that of pure maximal-ratio transmission systems.
