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Towards Adaptive Network Resource Orchestration for Cognitive Radio Networks

Yi-Wei Ma,
Jiann-Liang Chen,
Yu-Liang Tang,
Kuan-Hung Lai,


This work proposes an adaptive resource orchestration system for a Wireless Local Area Network (WLAN) that is based on the operating principle of Cognitive Radio (CR) technology. By collecting environmental parameters, including the retransmission rate and the channel occupancy rate, the proposed system has “knowledge” of overall transmission behavior and can regulate transmission resources. An Adaptive Connection Assignment (ACA) mechanism is proposed for end devices; it find out target end devices with poor transmission performance, analyzes their alternative Access Point (AP) availability and causes them to change connections to improve transmission performance. An Adaptive Channel Utilization (ACU) mechanism is designed for APs to identify a target AP that is suffering from interference, to analyze its alternative channel availability and to require it to change its working channel to improve transmission efficiency. Results of simulations of various scenarios indicate that the throughput of end devices is increased by 15 to 24%, the throughput of APs is increased by 6 to 47% and the retransmission rate of APs is reduced by 0.4 to 5.3%.


Cognitive Radio Networks, Resource orchestrator, Resource availability, Adaptive resource allocation

Citation Format:
Yi-Wei Ma, Jiann-Liang Chen, Yu-Liang Tang, Kuan-Hung Lai, "Towards Adaptive Network Resource Orchestration for Cognitive Radio Networks," Journal of Internet Technology, vol. 23, no. 5 , pp. 1087-1097, Sep. 2022.

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