In this paper,we formulate the precoding problem of integrated sensing and communication(ISAC)waveform as a non-convex quadratically constrained quadratic programming(QCQP),in which the weighted sum of communication m...In this paper,we formulate the precoding problem of integrated sensing and communication(ISAC)waveform as a non-convex quadratically constrained quadratic programming(QCQP),in which the weighted sum of communication multi-user interference(MUI)and the gap between dual-use waveform and ideal radar waveform is minimized with peak-toaverage power ratio(PAPR)constraints.We propose an efficient algorithm based on alternating direction method of multipliers(ADMM),which is able to decouple multiple variables and provide a closed-form solution for each subproblem.In addition,to improve the sensing performance in both spatial and temporal domains,we propose a new criteria to design the ideal radar waveform,in which the beam pattern is made similar to the ideal one and the integrated sidelobe level of the ambiguity function in each target direction is minimized in the region of interest.The limited memory Broyden-Fletcher-Goldfarb-Shanno(LBFGS)algorithm is applied to the design of the ideal radar waveform which works as a reference in the design of the dual-function waveform.Numerical results indicate that the designed dual-function waveform is capable of offering good communication quality of service(QoS)and sensing performance.展开更多
Integrated sensing and communication(ISAC)is regarded as a pivotal technology for 6G communication.In this paper,we employ Kullback-Leibler divergence(KLD)as the unified performance metric for ISAC systems and investi...Integrated sensing and communication(ISAC)is regarded as a pivotal technology for 6G communication.In this paper,we employ Kullback-Leibler divergence(KLD)as the unified performance metric for ISAC systems and investigate constellation and beamforming design in the presence of clutters.In particular,the constellation design problem is solved via the successive convex approximation(SCA)technique,and the optimal beamforming in terms of sensing KLD is proven to be equivalent to maximizing the signal-to-interference-plus-noise ratio(SINR)of echo signals.Numerical results demonstrate the tradeoff between sensing and communication performance under different parameter setups.Additionally,the beampattern generated by the proposed algorithm achieves significant clutter suppression and higher SINR of echo signals compared with the conventional scheme.展开更多
在下一代无线通信网络中,通信感知一体化(Integrated Sensing and Communications, ISAC)通过频谱共享、硬件共享、信号共享等方式实现感知与通信的融合,从而在进行信息传递的同时,感知环境中的物体的方位角度、距离、速度等信息。为进...在下一代无线通信网络中,通信感知一体化(Integrated Sensing and Communications, ISAC)通过频谱共享、硬件共享、信号共享等方式实现感知与通信的融合,从而在进行信息传递的同时,感知环境中的物体的方位角度、距离、速度等信息。为进一步提高资源利用率和一体化系统集成度,一体化信号设计和信号处理成为了ISAC的主要任务之一。作为信号处理中的一项基本流程,信道估计是高速数据传输和波束成形的先决条件,也是环境感知和参数估计的基础,因此准确的信道估计结果对感知和数据传输都至关重要。本文针对基于正交频分复用(Orthogonal Frequency Division Multiplexing, OFDM)信号在动态场景下的高导频开销问题,设计并实现了一种高效的时变信道估计与解调方案,并将其运用到通信感知一体化系统中。首先,本文设计了一种无导频的OFDM信号作为ISAC信号,仅依靠较短的前导码获取合适的初始信道估计值;接着提出了联合时变信道估计与数据解调的迭代算法,旨在利用数据辅助信道估计;最后,为了进一步提高动态场景下的信道估计精度,本文提出了一种鲁棒的基于卡尔曼滤波技术的数据辅助的时变信道跟踪算法。仿真表明本文设计的联合信号处理算法能在降低导频开销的同时,仅仅使用几次迭代就能显著提升时变信道估计和数据解调性能;本文还通过蒙特卡洛实验统计了所提方案的最大有效频谱效率,结果表明本文所提方法相比较传统能提高在高动态场景下的效率、鲁棒性和实用性;最后,本文还通过数值实验验证在多径环境中的目标感知功能,表明了本文的一体化信号适用于感知通信一体化系统,且本文设计的算法能提升通信和感知性能。展开更多
基金supported in part by the National Natural Science Foundation of China under Grant 62271142in part by the Key Research and Development Program of Jiangsu Province BE2023021+2 种基金in part by the Jiangsu Key Research and Development Program Project under Grant BE2023011-2in part by the Young Scholar Funding of Southeast Universityin part by the Fundamental Research Funds for the Central Universities 2242022k60001。
文摘In this paper,we formulate the precoding problem of integrated sensing and communication(ISAC)waveform as a non-convex quadratically constrained quadratic programming(QCQP),in which the weighted sum of communication multi-user interference(MUI)and the gap between dual-use waveform and ideal radar waveform is minimized with peak-toaverage power ratio(PAPR)constraints.We propose an efficient algorithm based on alternating direction method of multipliers(ADMM),which is able to decouple multiple variables and provide a closed-form solution for each subproblem.In addition,to improve the sensing performance in both spatial and temporal domains,we propose a new criteria to design the ideal radar waveform,in which the beam pattern is made similar to the ideal one and the integrated sidelobe level of the ambiguity function in each target direction is minimized in the region of interest.The limited memory Broyden-Fletcher-Goldfarb-Shanno(LBFGS)algorithm is applied to the design of the ideal radar waveform which works as a reference in the design of the dual-function waveform.Numerical results indicate that the designed dual-function waveform is capable of offering good communication quality of service(QoS)and sensing performance.
基金supported in part by National Key R&D Program of China under Grant No.2021YFB2900200in part by National Natural Science Foundation of China under Grant Nos.U20B2039 and 62301032in part by China Postdoctoral Science Foundation under Grant No.2023TQ0028.
文摘Integrated sensing and communication(ISAC)is regarded as a pivotal technology for 6G communication.In this paper,we employ Kullback-Leibler divergence(KLD)as the unified performance metric for ISAC systems and investigate constellation and beamforming design in the presence of clutters.In particular,the constellation design problem is solved via the successive convex approximation(SCA)technique,and the optimal beamforming in terms of sensing KLD is proven to be equivalent to maximizing the signal-to-interference-plus-noise ratio(SINR)of echo signals.Numerical results demonstrate the tradeoff between sensing and communication performance under different parameter setups.Additionally,the beampattern generated by the proposed algorithm achieves significant clutter suppression and higher SINR of echo signals compared with the conventional scheme.
文摘在下一代无线通信网络中,通信感知一体化(Integrated Sensing and Communications, ISAC)通过频谱共享、硬件共享、信号共享等方式实现感知与通信的融合,从而在进行信息传递的同时,感知环境中的物体的方位角度、距离、速度等信息。为进一步提高资源利用率和一体化系统集成度,一体化信号设计和信号处理成为了ISAC的主要任务之一。作为信号处理中的一项基本流程,信道估计是高速数据传输和波束成形的先决条件,也是环境感知和参数估计的基础,因此准确的信道估计结果对感知和数据传输都至关重要。本文针对基于正交频分复用(Orthogonal Frequency Division Multiplexing, OFDM)信号在动态场景下的高导频开销问题,设计并实现了一种高效的时变信道估计与解调方案,并将其运用到通信感知一体化系统中。首先,本文设计了一种无导频的OFDM信号作为ISAC信号,仅依靠较短的前导码获取合适的初始信道估计值;接着提出了联合时变信道估计与数据解调的迭代算法,旨在利用数据辅助信道估计;最后,为了进一步提高动态场景下的信道估计精度,本文提出了一种鲁棒的基于卡尔曼滤波技术的数据辅助的时变信道跟踪算法。仿真表明本文设计的联合信号处理算法能在降低导频开销的同时,仅仅使用几次迭代就能显著提升时变信道估计和数据解调性能;本文还通过蒙特卡洛实验统计了所提方案的最大有效频谱效率,结果表明本文所提方法相比较传统能提高在高动态场景下的效率、鲁棒性和实用性;最后,本文还通过数值实验验证在多径环境中的目标感知功能,表明了本文的一体化信号适用于感知通信一体化系统,且本文设计的算法能提升通信和感知性能。
