Cognitive database for television white space communications

• Main Author: Pakzad, Armie E.
• Format: text
• Language: English
• Published: Animo Repository 2023
• Subjects: Television frequency allocation; Satellite interference geolocation technology; Electrical and Electronics; Systems and Communications
• Online Access: https://animorepository.dlsu.edu.ph/etdd_ece/5
• Institution: De La Salle University

Television White Space (TVWS) refers to the unutilized Television (TV) channels specifically assigned for TV broadcasting. The usability of TVWS can be classified in terms of frequency, time, and geographical location. Specific frequencies on the TV band may be restricted in a given area due to their usage by nearby TV transmitters, and their availability may be subject to temporal constraints. Television White Space Database (TVWSDB) is a viable approach to implementing TVWS communications. The objective of this database is to safeguard the Primary User (PU) from interference caused by the Secondary User (SU). The existing TVWSDBs are deficient in their operational capabilities, specifically in providing SUs of TVWS with access to Short Term (ST), Medium Term (MT), and Long Term (LT) availability. This inadequacy could potentially hold significance for stakeholders in both government and industry. The study presents the outcomes of a simulation that utilized a Reinforcement Learning (RL) based model. The study involved utilizing a database that contained specific parameters pertaining to the height of TVWS antennas and their elevation above the average terrain, as outlined in the specifications. This study aimed to create an RL-based system that can provide accurate and prompt information through easily accessible means. A model of an agent was constructed wherein the agent was rewarded for selecting from among the channels that were available, and, conversely, penalized for opting for alternative options during the selection process. Subsequently, a Graphical User Interface (GUI) was employed to furnish the user with the data collected by the agent. The accuracy test results indicate that the broadcast time achieved a precision rate of 94.69%, while the contours achieved a precision rate of 84.37%. The experimentation of the broadcast schedule was conducted through a comparative analysis of the data gathered from the antenna testing and the information stored in the database. The precision of the contour lines was evaluated by comparing them with the channels detected during the antenna testing process. The speed of the searching process was also considered during the assessment of the RL-driven search compared to the linear search. The rate of the former was 2,080 times faster than that of the latter.