Being an open access on-line journal, PIER gives great prominence to special issues that draw together significant and emerging works to promote key advances on specific topics. The special issues are devoted to timely, relevant, and cutting-edge research and aim to provide a unique platform for researchers interested in selected topics.We are now calling for papers for the following PIER Spe
The 43rd PIERS in Hangzhou, CHINA
21 - 25, November 2021
(from Sunday to Thursday)
--- Where microwave and lightwave communities meet
Hybrid PIERS: Onsite + Web Access
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PIER Journals are a family of journals supported by the PhotonIcs and Electromagnetics Research Symposium (PIERS), which has become a major symposium in the area related to photonics and electromagnetics. The scope includes all aspects of electromagnetic theory plus its wide-ranging applications. Hence, it includes topics motivated by mathematics, sciences as well as topics inspired by advanced technologies. The spectrum ranges from very low frequencies to ultra-violet frequencies. The length scale spans from nanometer length scale to kilometer length scale. The physics covers the classical regime as well as the quantum regime.
Sensing is a key basis for building an intelligent environment. Using channel state information (CSI) from the IEEE 802.11 physical layer in the wireless local access networks, the CSIbased device-free sensing technique has become very promising to the current sensing solutions because of its non-invasion of privacy, non-contact, easy deployment, and low cost. In recent years, the integrated communication and sensing (ICAS) technology has become one of the popular research topics in both wireless communications and computer areas. Given the fruitful advancements of ICAS, it is essential to review these advancements to synthesize and give previous research experiences and references to aid the development of relevant research fields and real-world applications. Motivated by this, this paper aims to provide a comprehensive survey of CSI-based sensing techniques. This study categorizes the surveyed works into model-based methods, data-based methods, and model-data hybrid-driven methods. Some important physical models and machine learning algorithms are also introduced. The sensing functions are classified into detection, estimation, and recognition according to specific application scenarios. Furthermore, future directions and challenges are discussed.....