Abstract
Dynamic and optimal management of radio spectrum congestion is becoming a major problem in networking. Various factors can cause damage and interference between different users of the same radio spectrum. Cognitive radio provides an ideal and balanced solution to these types of problems (overload and congestion in the spectrum). The cognitive radio concept is based on the flexible use of any available frequency band of the radio spectrum that could be detected. In the world of cognitive radio, we distinguish two categories of networks, namely the primary ones, which have priority and control over access to the radio spectrum, and the secondary ones, called cognitive radio networks, which allocate the spectrum dynamically. In this paper, we focus on the dynamic management of the radio spectrum based on a multi-criteria algorithm to ensure the quality of service (QoS) of the utilization by secondary users. Our approach is to use a multi-agent system based on autonomous learning and focused on a competitive cognitive environment. In this paper, we evaluate the secondary user’s performance in an ideal environment of cognitive radio systems; we use the multi-agent platform called Java Agent Development (JADE), in which we implement a program that applies the multi-criteria TOPSIS algorithm to choose the best primary user (PU) among several PUs detected in the radio spectrum. Another paper allows scalability over 100 primary users evaluating four different types of technologies, namely voice, email, file transfer and video conferencing, and a comparison at the end of the convergence time for the latter technology with results from another paper.
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Seghiri, N., Baba-Ahmed, M.Z., Benmammar, B., Houari, N. (2022). Optimization of a Multi-criteria Cognitive Radio User Through Autonomous Learning. In: Ben Ahmed, M., Teodorescu, HN.L., Mazri, T., Subashini, P., Boudhir, A.A. (eds) Networking, Intelligent Systems and Security. Smart Innovation, Systems and Technologies, vol 237. Springer, Singapore. https://doi.org/10.1007/978-981-16-3637-0_9
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