To reduce the negative impact of channel quantization errors, a low-complexity transceiver joint design scheme for both the transmit beamformers and receive combining vectors is proposed in the two-user multiple-input...To reduce the negative impact of channel quantization errors, a low-complexity transceiver joint design scheme for both the transmit beamformers and receive combining vectors is proposed in the two-user multiple-input multiple-output （MIMO） system. In the scheme, the channel nullspace quantization vector is used as the transmit beamformer of the interference user directly based on channel null-space feedback. Since the interference can be determined at the receiver, interference rejection combining （IRC） is jointly utilized to cancel the inter-user interference. Simulation re- sults show that the proposed scheme can provide substantial sum-rate improvement especially at high SNR.展开更多
Cognitive Radio(CR) is a promising technique for the next generation mobile communi-cation system for its capability to solve the conflicts between the scarcity and underutilization of spectrum.In this paper,aiming at...Cognitive Radio(CR) is a promising technique for the next generation mobile communi-cation system for its capability to solve the conflicts between the scarcity and underutilization of spectrum.In this paper,aiming at maximizing the system capacity of a multi-antenna CR system on the premise that avoid interference to the primary system in the same band simultaneously,a resource allocation method which is able to avoid interference between PRimary(PR) and CR users by pro-jecting the transmit signals of CR users on the null space of the PR users' channels is proposed.CR users with better channel condition are selected,and the interference from CR system to PR users can be removed completely by projecting the transmit signals of CR system on the null-space of PR users' channels.Parallel sub-channels are constructed for CR users through Singular Value Decomposition(SVD).At last,waterfilling is also adopted to increase the CR users' capacity.Simulation result demonstrates that compared with existing methods,our method can improve the achievable sum rate of CR users as well as reduce the outage probability of PR users.展开更多
A number of previous papers have studied the problem of recovering low-rank matrices with noise, further combining the noisy and perturbed cases, we propose a nonconvex Schatten p-norm minimization method to deal with...A number of previous papers have studied the problem of recovering low-rank matrices with noise, further combining the noisy and perturbed cases, we propose a nonconvex Schatten p-norm minimization method to deal with the recovery of fully perturbed low-rank matrices. By utilizing the p-null space property (p-NSP) and the p-restricted isometry property (p-RIP) of the matrix, sufficient conditions to ensure that the stable and accurate reconstruction for low-rank matrix in the case of full perturbation are derived, and two upper bound recovery error estimation ns are given. These estimations are characterized by two vital aspects, one involving the best r-approximation error and the other concerning the overall noise. Specifically, this paper obtains two new error upper bounds based on the fact that p-RIP and p-NSP are able to recover accurately and stably low-rank matrix, and to some extent improve the conditions corresponding to RIP.展开更多
基金Supported by the Sino-Swedish IMT-Advanced and Beyond Cooperative Program(2008DFA11780)
文摘To reduce the negative impact of channel quantization errors, a low-complexity transceiver joint design scheme for both the transmit beamformers and receive combining vectors is proposed in the two-user multiple-input multiple-output （MIMO） system. In the scheme, the channel nullspace quantization vector is used as the transmit beamformer of the interference user directly based on channel null-space feedback. Since the interference can be determined at the receiver, interference rejection combining （IRC） is jointly utilized to cancel the inter-user interference. Simulation re- sults show that the proposed scheme can provide substantial sum-rate improvement especially at high SNR.
文摘Cognitive Radio(CR) is a promising technique for the next generation mobile communi-cation system for its capability to solve the conflicts between the scarcity and underutilization of spectrum.In this paper,aiming at maximizing the system capacity of a multi-antenna CR system on the premise that avoid interference to the primary system in the same band simultaneously,a resource allocation method which is able to avoid interference between PRimary(PR) and CR users by pro-jecting the transmit signals of CR users on the null space of the PR users' channels is proposed.CR users with better channel condition are selected,and the interference from CR system to PR users can be removed completely by projecting the transmit signals of CR system on the null-space of PR users' channels.Parallel sub-channels are constructed for CR users through Singular Value Decomposition(SVD).At last,waterfilling is also adopted to increase the CR users' capacity.Simulation result demonstrates that compared with existing methods,our method can improve the achievable sum rate of CR users as well as reduce the outage probability of PR users.
文摘A number of previous papers have studied the problem of recovering low-rank matrices with noise, further combining the noisy and perturbed cases, we propose a nonconvex Schatten p-norm minimization method to deal with the recovery of fully perturbed low-rank matrices. By utilizing the p-null space property (p-NSP) and the p-restricted isometry property (p-RIP) of the matrix, sufficient conditions to ensure that the stable and accurate reconstruction for low-rank matrix in the case of full perturbation are derived, and two upper bound recovery error estimation ns are given. These estimations are characterized by two vital aspects, one involving the best r-approximation error and the other concerning the overall noise. Specifically, this paper obtains two new error upper bounds based on the fact that p-RIP and p-NSP are able to recover accurately and stably low-rank matrix, and to some extent improve the conditions corresponding to RIP.
