MmWave integrated localization, mapping, and communication: A stochastic geometry perspective

Sensing, as an underlying function of integrated sensing and communication (ISAC), can, in theory, enable numerous applications, including detection, localization, navigation, etc. However, in sixth generation (6G) and beyond, sensing data could be used in a more effective manner, while environmental mapping is a promising candidate to enhance the sensing capacity. This paper augments the conventional ISAC framework by introducing the concept of integrated localization, mapping, and communication (LMAC), exploring the feasibility of providing mapping services while maintaining localization accuracy. Closedform expressions for the communication and localization signal-to-interference-plus-noise ratios (SINRs) are analytically derived to evaluate both the communication performance and the localizability of the localization user and scatterers. Furthermore, the Cramér-Rao lower bounds (CRLBs) for localization and mapping services are provided to characterize the fundamental limits of an LMAC system. Numerical results indicate that the proposed performance bounds effectively characterize the system performance and offer valuable insights into how different network configurations influence the performance and realizable potential of LMAC.