网络辅助全双工无小区ISAC系统的联合通信感知波束成形与上行功率控制
Joint Communication Sensing Beamforming and Uplink Power Control for Network-Assisted Full-Duplex Cell-Free ISAC Systems
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中文总结 AI 辅助
针对网络辅助全双工无小区ISAC系统，提出联合下行通信波束成形、感知波束成形与上行功率控制方案，通过优先级设计和SDR优化最大化感知SINR并满足通信约束。
中文摘要 AI 辅助
本文研究了在多静态集成感知与通信（ISAC）赋能的去蜂窝大规模多输入多输出（CF mMIMO）系统中，联合设计下行（DL）通信波束成形器、上行（UL）功率以及感知波束成形器的问题。为此，我们首先考虑了两种基于优先级的波束成形策略。在通信优先的感知设计中，我们首先设计通信波束成形器，然后将感知波束成形器投影到有效通信信道的零空间上，以抑制其对下行用户设备和上行接收机的额外干扰。在感知优先的通信设计中，我们首先根据目标方向选择感知波束成形器，随后使用最大最小信干噪比（SINR）公式对通信波束成形器进行优化。除了这些基于优先级的设计之外，我们制定了一个以感知为中心的联合优化问题，以确定最优的下行通信波束成形器、感知波束成形器和上行用户设备发射功率。我们的目标是在保证个体下行和上行SINR要求以及满足每个接入点（AP）和每个用户设备发射功率约束的同时，最大化感知SINR。由于所得到的问题因波束成形和上行功率变量的耦合而具有非凸性，波束成形向量被提升为半正定发射协方差矩阵，并应用了半定松弛（SDR）技术。
英文摘要
In this paper, we investigate the problem of designing joint downlink (DL) communication beamformer and uplink (UL) power as well as sensing beamformer in a multi static integrated sensing and communication (ISAC) enabled cell free massive multiple input multiple output (CF mMIMO) system. To this goal, we first consider two priority based beamforming strategies. In the communication prioritized sensing design, we first design the communication beamformers and then the sensing beamformer is projected onto the nullspace of the effective communication channels to suppress its additional interference to both the DL UEs and UL receivers. In the sensing prioritized communication design, we select the sensing beamformer first according to the target direction, while the communication beamformers are subsequently optimized using a max min SINR formulation. In addition to these priority based designs, we formulate a sensing centric joint optimization problem to determine the optimal DL communication beamformers, sensing beamformer, and UL UE transmit powers. Our objective is to maximize the sensing SINR while guaranteeing individual DL and UL SINR requirements and satisfying the per AP and per UE transmitpower constraints. Since the resulting problem is non convex because of the coupled beamforming and UL power variables, the beamforming vectors are lifted into positive semidefinite transmit covariance matrices and semidefinite relaxation (SDR) is applied.
发表机构
- Sharif University of Technology（谢里夫理工大学）
- Yazd University（亚兹德大学）
机构由 AI 辅助整理，请以论文原文为准。
