Dynamic Programming and Optimal Control
Dynamic Programming and Optimal Control
Advanced Wired-wireless Networks (Multimedia Systems and Applications)
Advanced Wired-wireless Networks (Multimedia Systems and Applications)
Aware, Adaptive and Cognitive Radio: The Engineering Foundations of Radio XML
Aware, Adaptive and Cognitive Radio: The Engineering Foundations of Radio XML
Cognitive Radio, Software Defined Radio, and Adaptive Wireless Systems (Signals and Communication Technology)
Adaptive agents and multi-agent systems: adaptation and multi-agent learning
Adaptive agents and multi-agent systems: adaptation and multi-agent learning
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Owing to the increasing and diversifying service requirements of wireless communications, wireless networks must coexist with heterogeneous radio systems. To realise the interconnection between different networks, it is important for the radio access network elements, such as the cellular network base stations (BSs) and the wireless local area network (WLAN) access points (APs) to be reconfigurable based on the real-time network environment. In this paper, we propose an efficient distributed reconfiguration algorithm for heterogeneous networks: the dynamic network self-optimisation algorithm (DNSA). This algorithm is based on the Q-learning algorithm and the self-optimisation of each network entity acting as independent agents. In the proposed algorithm, multiple agents perform the optimisation cooperatively to reduce the system blocking rate and improve network revenue. The dynamic network self-optimisation problem is transformed into a multiple-agent reinforcement learning problem which has much lower complexity and better performance.