Communicate or Sense? AP Mode Selection in mmWave Cell-Free Massive MIMO-ISAC
Weixian Yan, Ozan Alp Topal, Zinat Behdad, Ozlem Tugfe Demir, Cicek Cavdar
TL;DR
The paper addresses energy-efficient AP mode selection in mmWave cell-free massive MIMO-ISAC by assigning APs to ISAC transmitters, sensing receivers, or shutdown while guaranteeing UE SINR and CRLB-based sensing performance. It formulates a non-convex optimization problem and presents three suboptimal schemes—Alternating Optimization, Sequential Optimization, and a Heuristic—that transform SINR constraints into SOC form and leverage CRLB-based sensing metrics. Experiments in a realistic outdoor scenario show that Sequential Optimization achieves comparable performance to Alternating Optimization but with about 50% fewer active APs and roughly 8× faster runtimes, while the Heuristic is faster but less efficient. The work demonstrates a practical, energy-aware approach to ISAC in dense mmWave networks, enabling dynamic adaptation to user and target mobility.
Abstract
Integrated sensing and communication (ISAC) is a promising technology for future mobile networks, enabling sensing applications to be performed by existing communication networks, consequently improving the system efficiency. Millimeter wave (mmWave) signals provide high sensing resolution and high data rate but suffer from sensitivity to blockage. Cell-free massive multiple-input multiple-output (MIMO), with a large number of distributed access points (APs), can overcome this challenge by providing macro diversity against changing blockages and can save energy consumption by deactivating unfavorable APs. Thus, in this work, we propose a joint dynamic AP mode selection and power allocation scheme for mmWave cell-free massive MIMO-ISAC, where APs are assigned either as ISAC transmitters, sensing receivers, or shut down. Due to the large size of the original problem, we propose three different sub-optimal algorithms that minimize the number of active APs while guaranteeing the sensing and communication constraints. Numerical results demonstrate that assigning ISAC transmitters only satisfying communication constraints, followed up by sensing receiver assignment only for sensing constraint achieves the best performance-complexity balance.