Development of multi-objective cognitive radio network with energy harvesting for medical data transmission

Cognitive Radio Sensor Network (CRSN) is the fusion of opportunistic spectrum access technology and wireless network. It has considered the problems based on the energy and dynamic spectrum derived from the wireless network and caused by the Cognitive Radio Network (CRN). CRSN contains several challenges in the research sector while developing an effective topology control to communicate over the network. The main advantage to extend the lifespan of the network is to harvest energy through Radio Frequency (RF) transmission or from other ambient sources. Hence, this paper plans to develop a new CRSN routing protocol for medical data transmission with energy harvesting, where the hybrid optimization algorithm of named Hybrid Cuckoo Search Elephant Herding Optimization (HCSEHO) is proposed for determining the optimal path between the source and destination node and extending the lifetime of network with optimal energy harvesting model. The main goal is to select the path that has better efficiency to guarantee reliable energy-efficient medical data transmission by setting the initial energy harvesting to avoid the nodes being dead. Here, the proposed multi-objective function considers the constraints such as energy harvesting, hop count, throughput, and outage probability. Simulation results show that the proposed CRSN routing protocol improves network performance and provides more energy efficiency compared to some recent existing protocols.

Automated summary

This paper proposes a new CRSN routing protocol for medical data transmission with energy harvesting, using a hybrid optimization algorithm to determine the optimal path between the source and destination node. Simulation results show that the proposed protocol improves network performance and energy efficiency compared to recent existing protocols.