Nowadays, with the extension and advancement of intelligent communication devices, the number of services and applications based on users' location has increased. The knowledge of users' position and localization has attracted the attention of many researchers. Indoor localization is a type of localization with many applications such as health services, robotics, security, and marketing. In indoor localization, conventional outdoor localization methods such as GPS cannot be used because the signals are attenuated due to collisions with obstacles and the distance between the transmitter and the receiver. For this purpose, it is necessary to introduce new methods for indoor localization. One of the appropriate methods is the position fingerprint method. This method first divides the localization environment into several specific areas and places reference points at their center. A database is created after receiving the signal by reference points and creating a fingerprint for each region. Then, each new user's fingerprint is compared with the database, and its location is estimated. Despite its simplicity and low cost, this localization method has problems such as fingerprint similarity of adjacent areas and the impact of multipath fading. The emerging and attractive technology, Reconfigurable Intelligent Surfaces(RIS), solves the above problems. RIS consists of passive elements that can adjust the communication environment and create a variety of communication channels by adjusting the amplitude and phase of the reflected signal. RIS has many applications in telecommunication systems, such as indoor localization. The appropriate RIS configuration can increase the user's location estimation accuracy. This thesis considers a multi-user location system based on RIS, which can estimate users' location with high accuracy using the position fingerprint method. This system can create different fingerprints for adjacent areas with multiple RIS configurations. The proposed approach has many advantages such as high speed and low latency, simplicity and low cost, no need to solve complex optimization problems, no need for channel estimation, availability, and the possibility of multi-user localization. Finally, the simulation results are presented to eva‎luate the performance of the proposed system. Moreover, the parameters affecting localization accuracy have been studied, and a suitable value has been obtained for them.

محمدجواد اميدي

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