In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose ...In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose a low-complexity alternating optimization(AO)based joint beamforming and RIS phase shifts optimization algorithm to maximize the achievable rate.First,with fixed RIS phase shifts,we devise the optimal closedform transmit beamforming vectors corresponding to different subcarriers.Then,with given active beamforming vectors,near-optimal RIS reflection coefficients can be determined efficiently leveraging fractional programming(FP)combined with manifold optimization(MO)or majorization-minimization(MM)framework.Additionally,we also propose a heuristic RIS phase shifts design approach based on the sum of subcarrier gain maximization(SSGM)criterion requiring lower complexity.Numerical results indicate that the proposed MO/MM algorithm can achieve almost the same rate as the upper bound achieved by the semidefinite relaxation(SDR)algorithm,and the proposed SSGM based scheme is only slightly inferior to the upper bound while has much lower complexity.These results demonstrate the effectiveness of the proposed algorithms.展开更多
Directionality of image plays a very important role in human visual system and it is important prior information of image. In this paper we propose a weighted directional total variation model to reconstruct image fro...Directionality of image plays a very important role in human visual system and it is important prior information of image. In this paper we propose a weighted directional total variation model to reconstruct image from its finite number of noisy compressive samples. A novel self-adaption, texture preservation method is designed to select the weight. Inspired by majorization-minimization scheme, we develop an efficient algorithm to seek the optimal solution of the proposed model by minimizing a sequence of quadratic surrogate penalties. The numerical examples are performed to compare its performance with four state-of-the-art algorithms. Experimental results clearly show that our method has better reconstruction accuracy on texture images than the existing scheme.展开更多
For near-field multiuser communications based on hybrid beamforming(HBF)architectures,high-quality effective channel estimation is required to obtain the channel state information(CSI)for the design of the digital bea...For near-field multiuser communications based on hybrid beamforming(HBF)architectures,high-quality effective channel estimation is required to obtain the channel state information(CSI)for the design of the digital beamformer.To simplify the system reconfiguration and eliminate the pilot overhead required by effective channel estimation,we consider an analog-only beamforming(AoBF)architecture in this study.AoBF is designed to maximize the sum rate,it is transformed into a problem maximizing the power transmitted to the target user equipment(UE)and meanwhile minimizing the power leaked to the other UEs.To solve this problem,we use beam focusing and beam nulling and propose two AoBF schemes based on the majorization-minimization algorithm.First,the AoBF scheme based on perfect CSI is proposed,with the focus on beamforming performance and regardless of CSI acquisition.Then,the AoBF scheme based on imperfect CSI is proposed,where low-dimensional imperfect CSI is obtained by beam sweeping based on a near-field codebook.Simulation results demonstrate that the two AoBF schemes can approach HBF schemes in terms of the sum rate and outperform HBF schemes in terms of energy efficiency.展开更多
基金supported in part by the National Natural Science Foundation of China under Grants 61971126 and 61921004ZTE CorporationState Key Laboratory of Mobile Network and Mobile Multimedia Technology.
文摘In this paper,we investigate the reconfigurable intelligent surface(RIS)-enabled multiple-input-single-output orthogonal frequency division multiplexing(MISO-OFDM)system under frequency-selective channels,and propose a low-complexity alternating optimization(AO)based joint beamforming and RIS phase shifts optimization algorithm to maximize the achievable rate.First,with fixed RIS phase shifts,we devise the optimal closedform transmit beamforming vectors corresponding to different subcarriers.Then,with given active beamforming vectors,near-optimal RIS reflection coefficients can be determined efficiently leveraging fractional programming(FP)combined with manifold optimization(MO)or majorization-minimization(MM)framework.Additionally,we also propose a heuristic RIS phase shifts design approach based on the sum of subcarrier gain maximization(SSGM)criterion requiring lower complexity.Numerical results indicate that the proposed MO/MM algorithm can achieve almost the same rate as the upper bound achieved by the semidefinite relaxation(SDR)algorithm,and the proposed SSGM based scheme is only slightly inferior to the upper bound while has much lower complexity.These results demonstrate the effectiveness of the proposed algorithms.
基金the National Natural Science Foundation of China(Nos.11401318 and 11671004)the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(No.15KJB110018)the Scientific Research Foundation of NUPT(No.NY214023)
文摘Directionality of image plays a very important role in human visual system and it is important prior information of image. In this paper we propose a weighted directional total variation model to reconstruct image from its finite number of noisy compressive samples. A novel self-adaption, texture preservation method is designed to select the weight. Inspired by majorization-minimization scheme, we develop an efficient algorithm to seek the optimal solution of the proposed model by minimizing a sequence of quadratic surrogate penalties. The numerical examples are performed to compare its performance with four state-of-the-art algorithms. Experimental results clearly show that our method has better reconstruction accuracy on texture images than the existing scheme.
基金supported by the National Natural Science Foundation of China(Nos.U22B2007 and 62071116)。
文摘For near-field multiuser communications based on hybrid beamforming(HBF)architectures,high-quality effective channel estimation is required to obtain the channel state information(CSI)for the design of the digital beamformer.To simplify the system reconfiguration and eliminate the pilot overhead required by effective channel estimation,we consider an analog-only beamforming(AoBF)architecture in this study.AoBF is designed to maximize the sum rate,it is transformed into a problem maximizing the power transmitted to the target user equipment(UE)and meanwhile minimizing the power leaked to the other UEs.To solve this problem,we use beam focusing and beam nulling and propose two AoBF schemes based on the majorization-minimization algorithm.First,the AoBF scheme based on perfect CSI is proposed,with the focus on beamforming performance and regardless of CSI acquisition.Then,the AoBF scheme based on imperfect CSI is proposed,where low-dimensional imperfect CSI is obtained by beam sweeping based on a near-field codebook.Simulation results demonstrate that the two AoBF schemes can approach HBF schemes in terms of the sum rate and outperform HBF schemes in terms of energy efficiency.
