This paper studies integrated sensing and communication (ISAC) in the downlink of a cell-free massive multiple-input multiple-output (MIMO) system with multi-static sensing and ultra-reliable low-latency communication (URLLC) users. We propose a successive convex approximation-based power allocation algorithm that maximizes energy efficiency while satisfying the sensing and URLLC requirements. In addition, we provide a new definition for network availability, which accounts for both sensing and URLLC requirements. The impact of blocklength, sensing requirement, and required reliability as a function of decoding error probability on network availability and energy efficiency is investigated. The proposed power allocation algorithm is compared to a communication-centric approach where only the URLLC requirement is considered. It is shown that the URLLC-only approach is incapable of meeting sensing requirements, while the proposed ISAC algorithm fulfills both sensing and URLLC requirements, albeit with an associated increase in energy consumption. This increment can be reduced up to 75% by utilizing additional symbols for sensing. It is also demonstrated that larger blocklengths enhance network availability and offer greater robustness against stringent reliability requirements.

翻译：本文研究了集成感知与通信（ISAC）在多静态感知与超可靠低延迟通信（URLLC）用户共存的无蜂窝大规模多输入多输出（MIMO）系统下行链路中的应用。我们提出了一种基于逐次凸近似的功率分配算法，在满足感知与URLLC需求的同时最大化能量效率。此外，我们给出了网络可用性的新定义，该定义同时考虑感知与URLLC要求。本文研究了块长、感知需求以及以解码错误概率为函数的可靠性要求对网络可用性和能量效率的影响。将所提出的功率分配算法与仅考虑URLLC需求的通信中心方法进行了比较。结果表明，仅考虑URLLC的方法无法满足感知需求，而所提出的ISAC算法虽然会带来额外的能量消耗，但能同时满足感知与URLLC要求。通过利用额外符号用于感知，该能量消耗增量最多可降低75%。研究还表明，较大的块长能提升网络可用性，并对严苛的可靠性要求表现出更强的鲁棒性。