Modern networks rely on a variety of technologies to sense the environment for static or locomotive objects, in particular their shapes, distances, directions, or velocities. Sensing is a key feature in these networks and enables for example autonomous driving, motion sensing in health applications, target detection in smart cities, or optimal beam selections in millimeter wave communication. Besides these exciting new applications, sensing remains an important feature also for traditional applications such as temperature monitoring, or earthquake or fire detection, where new technologies are exploited including continuous feature monitoring over the entire range of an optical fiber network. The purpose of this special issue is to report on new exciting applications of sensing in modern networks, novel sensing architectures, innovative signal processing mechanisms related to sensing, as well as new results on the fundamental performance limits (resolution, sample complexity, robustness) of sensing systems. Particular focus will be on joint systems that integrate sensing with other tasks, for example communication, information retrieval (estimation, feature extraction, localization), super-resolution.
Sensing has emerged as a key feature of modern wireless communication systems and networks. Traditionally, advances in the design, optimization and deployment of sensing and communication systems have evolved somewhat independently of each other. In recent times however, we are beginning to appreciate the benefits offered by the synergy between sensing and related areas in communication, largely driven by modern applications such as autonomous driving, motion sensing in health applications, target detection and localization in smart cities, dual-function radar and communication systems, and optimal beam selection and alignment in millimeter wave communication. We are pleased to announce that in this special issue we have collected exciting recent results on a broad range of different domains and applications that rely on sensing, with a focus on fundamental contributions that explore the performance limits of sensing problems and offer innovative solutions.