The possibility of jointly optimizing location sensing and communication resources, facilitated by the existence of communication and sensing spectrum sharing, is what promotes the system performance to a higher level. However, the rapid mobility of user equipment (UE) can result in inaccurate location estimation, which can severely degrade system performance. Therefore, the precise UE location sensing and resource allocation issues are investigated in a spectrum sharing sixth generation network. An approach is proposed for joint subcarrier and power optimization based on UE location sensing, aiming to minimize system energy consumption. The joint allocation process is separated into two key phases of operation. In the radar location sensing phase, the multipath interference and Doppler effects are considered simultaneously, and the issues of UE’s location and channel state estimation are transformed into a convex optimization problem, which is then solved through gradient descent. In the communication phase, a subcarrier allocation method based on subcarrier weights is proposed. To further minimize system energy consumption, a joint subcarrier and power allocation method is introduced, resolved via the Lagrange multiplier method for the non-convex resource allocation problem. Simulation analysis results indicate that the location sensing algorithm exhibits a prominent improvement in accuracy compared to benchmark algorithms. Simultaneously, the proposed resource allocation scheme also demonstrates a substantial enhancement in performance relative to baseline schemes.

中文翻译：

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6G 网络中的联合雷达感知、定位和通信资源优化


由于通信和传感频谱共享的存在，联合优化位置传感和通信资源的可能性将系统性能提升到更高的水平。然而，用户设备（UE）的快速移动可能导致位置估计不准确，从而严重降低系统性能。因此，在频谱共享第六代网络中研究精确的UE位置感知和资源分配问题。提出了一种基于UE位置感知的联合子载波和功率优化方法，旨在最小化系统能耗。联合分配过程分为两个关键的操作阶段。在雷达定位感知阶段，同时考​​虑多径干扰和多普勒效应，将UE的位置和信道状态估计问题转化为凸优化问题，然后通过梯度下降来求解。在通信阶段，提出了一种基于子载波权重的子载波分配方法。为了进一步最小化系统能耗，引入了联合子载波和功率分配方法，通过拉格朗日乘子法解决非凸资源分配问题。仿真分析结果表明，与基准算法相比，位置感知算法在精度上有显着的提高。同时，所提出的资源分配方案还证明了相对于基准方案性能的显着提高。