Tracking Secondary User in Cognitive radio for 5G Communication

Cognitive Radio (CR) is a promising technology which resolves the spectrum scarcity issues and allows secondary user (SU) to use the vacant spectrum space without causing interference to the primary user (PU). Many secondary users are allocated different spectrum bands to enhance spectrum utilization. SU co-exists with the PU in the CR network and continuously monitors PU activities in order to use vacant space of PU in the spectrum. The movement of SU in the CR network is random and therefore it is necessary to track the position of SU and measure radio signal strength indicator (RSSI) in order to avoid interference with the PU. In this work, we present the implementation and comparison of two algorithms KALMAN Filter and State Space Least Mean Square (SSLMS) to track the position of SU in the CR network under log distance and log normal shadowing path loss models. Both algorithms track the position of SU by measuring RSSI and Signal to Noise Ratio (SNR) from the PU; however SSLMS gives better performance as compared to KALMAN Filter.