Owing to the inherent central information processing and resource management ability,the cloud radio access network(C-RAN)is a promising network structure for an intelligent and simplified sixth-generation(6G)wireless...Owing to the inherent central information processing and resource management ability,the cloud radio access network(C-RAN)is a promising network structure for an intelligent and simplified sixth-generation(6G)wireless network.Nevertheless,to further enhance the capacity and coverage,more radio remote heads(RRHs)as well as high-fidelity and low-latency fronthaul links are required,which may lead to high implementation cost.To address this issue,we propose to exploit the intelligent reflecting surface(IRS)as an alternative way to enhance the C-RAN,which is a low-cost and energy-efficient option.Specifically,we consider the uplink transmission where multi-antenna users communicate with the baseband unit(BBU)pool through multi-antenna RRHs and multiple IRSs are deployed between the users and RRHs.RRHs can conduct either point-to-point(P2P)compression or Wyner-Ziv coding to compress the received signals,which are then forwarded to the BBU pool through fronthaul links.We investigate the joint design and optimization of user transmit beamformers,IRS passive beamformers,and fronthaul compression noise covariance matrices to maximize the uplink sum rate subject to fronthaul capacity constraints under P2P compression and Wyner-Ziv coding.By exploiting the Arimoto-Blahut algorithm and semi-definite relaxation(SDR),we propose a successive convex approximation approach to solve non-convex problems,and two iterative algorithms corresponding to P2P compression and Wyner-Ziv coding are provided.Numerical results verify the performance gain brought about by deploying IRS in C-RAN and the superiority of the proposed joint design.展开更多
Due to the broadcast nature of wireless transmission medium,security threats may hinder propagation of cognitive radio systems for commercial and military data application. This paper sets a channel error analytical f...Due to the broadcast nature of wireless transmission medium,security threats may hinder propagation of cognitive radio systems for commercial and military data application. This paper sets a channel error analytical framework and studies the joint impact of estimation errors and feedback delay on secrecy performance in cognitive radio networks. Under the assumption that system applies beamforming and jamming scheme,a multi-antenna cognitive base station( CBS) sends confidential signals to a secondary user( SU) in the presence of M primary users( PUs) and an eavesdropper. Assuming only imperfect channel state information( CSI) about the receivers is available,secrecy rate,outage probability,secrecy throughput are deduced to obtain a closed-form expression. It is shown that while the transmit power increases,secrecy throughput would reach to a constant. Simulation results show that feedback delay adversely impacts on secrecy rate,connection outage probability and secrecy throughput,while estimation error causes more impact on secrecy outage probability. Furthermore,the secrecy rate could increase progressively with the transmit power only if there exists no feedback delay.展开更多
We propose a distributed closedloop power control scheme for a cognitive radio network(CRN) based on our developed state space model of the CRN. The whole power control process is separated into outer control loop and...We propose a distributed closedloop power control scheme for a cognitive radio network(CRN) based on our developed state space model of the CRN. The whole power control process is separated into outer control loop and inner control loop in order to solve different problem. In outer loop, the interference temperature(IT) constraint is transformed to a performance index minimized by a state feedback controller to obtain an appropriate target signal to interference plus noise ratio(SINR) of secondary user(SU). For ideal channel model and random time-varying channel model, our designed controller is a linear quadratic regulator(LQR) and a linear quadratic Gaussian(LQG) regulator respectively. While in inner loop, SU controls its transmit power to make the instantaneous SINR track the corresponding target and ensure the IT constraint under the limited threshold. The closed-loop stability of the CRN is proved and the performance of proposed control scheme is presented by computer simulations, which shows that this scheme can effectively guarantee both the requirement of SINR and IT constraint for all SUs.展开更多
基金Project supported by the Zhejiang Provincial Natural Science Foundation of China(Nos.LY21F010008 and LD21F010001)the National Natural Science Foundation of China(No.62171412)the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University,China(No.2020D10)。
文摘Owing to the inherent central information processing and resource management ability,the cloud radio access network(C-RAN)is a promising network structure for an intelligent and simplified sixth-generation(6G)wireless network.Nevertheless,to further enhance the capacity and coverage,more radio remote heads(RRHs)as well as high-fidelity and low-latency fronthaul links are required,which may lead to high implementation cost.To address this issue,we propose to exploit the intelligent reflecting surface(IRS)as an alternative way to enhance the C-RAN,which is a low-cost and energy-efficient option.Specifically,we consider the uplink transmission where multi-antenna users communicate with the baseband unit(BBU)pool through multi-antenna RRHs and multiple IRSs are deployed between the users and RRHs.RRHs can conduct either point-to-point(P2P)compression or Wyner-Ziv coding to compress the received signals,which are then forwarded to the BBU pool through fronthaul links.We investigate the joint design and optimization of user transmit beamformers,IRS passive beamformers,and fronthaul compression noise covariance matrices to maximize the uplink sum rate subject to fronthaul capacity constraints under P2P compression and Wyner-Ziv coding.By exploiting the Arimoto-Blahut algorithm and semi-definite relaxation(SDR),we propose a successive convex approximation approach to solve non-convex problems,and two iterative algorithms corresponding to P2P compression and Wyner-Ziv coding are provided.Numerical results verify the performance gain brought about by deploying IRS in C-RAN and the superiority of the proposed joint design.
基金Supported by the National Natural Science Foundation of China(No.61371122,61471393)the China Postdoctoral Science Foundation under a Special Financial Grant(No.2013T60912)
文摘Due to the broadcast nature of wireless transmission medium,security threats may hinder propagation of cognitive radio systems for commercial and military data application. This paper sets a channel error analytical framework and studies the joint impact of estimation errors and feedback delay on secrecy performance in cognitive radio networks. Under the assumption that system applies beamforming and jamming scheme,a multi-antenna cognitive base station( CBS) sends confidential signals to a secondary user( SU) in the presence of M primary users( PUs) and an eavesdropper. Assuming only imperfect channel state information( CSI) about the receivers is available,secrecy rate,outage probability,secrecy throughput are deduced to obtain a closed-form expression. It is shown that while the transmit power increases,secrecy throughput would reach to a constant. Simulation results show that feedback delay adversely impacts on secrecy rate,connection outage probability and secrecy throughput,while estimation error causes more impact on secrecy outage probability. Furthermore,the secrecy rate could increase progressively with the transmit power only if there exists no feedback delay.
基金supported by the National Natural Science Foundation of China (Grant No. 61571209)
文摘We propose a distributed closedloop power control scheme for a cognitive radio network(CRN) based on our developed state space model of the CRN. The whole power control process is separated into outer control loop and inner control loop in order to solve different problem. In outer loop, the interference temperature(IT) constraint is transformed to a performance index minimized by a state feedback controller to obtain an appropriate target signal to interference plus noise ratio(SINR) of secondary user(SU). For ideal channel model and random time-varying channel model, our designed controller is a linear quadratic regulator(LQR) and a linear quadratic Gaussian(LQG) regulator respectively. While in inner loop, SU controls its transmit power to make the instantaneous SINR track the corresponding target and ensure the IT constraint under the limited threshold. The closed-loop stability of the CRN is proved and the performance of proposed control scheme is presented by computer simulations, which shows that this scheme can effectively guarantee both the requirement of SINR and IT constraint for all SUs.
