Outage Performance Analysis of Wireless Energy Harvesting Relay-Assisted Random Underlay Cognitive Networks

• Published in: IEEE internet of things journal Vol. 5; no. 4; pp. 2691 - 2699
• Main Authors: Yan, Zhi, Chen, Shuang, Zhang, Xing, Liu, Hong-Li
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.08.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Cognitive radio; Cognitive relay networks; Energy consumption; Energy harvesting; Energy transmission; Internet of Things; Nodes; outage probability; Power supplies; Receivers; Relay; Relays; stochastic geometry; Transmitters; Wireless communication; wireless energy harvesting; Wireless sensor networks
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2018.2800716

The dramatic development of Internet of Things (IoT) is not only leading to the spectrum crunch, but is also resulting in exorbitant energy consumption. It is thus desirable to liberate IoT from the constraint of the spectrum scarcity and to rein in the growing energy consumption. Wireless energy harvesting relay-assisted underlay cognitive networks (WEH-CRNs), which combine cognitive radio and wireless energy harvesting techniques to alleviate the spectrum and energy constraints by reusing spare spectrum for data transmissions and harvesting ambient energy for power supplies, are conceived as an efficient solution for massive IoT deployments. However, all existing works about WEH-CRNs did not take into account of the spatial location distribution of nodes, which is very important for energy harvesting and information transmission. Therefore, in this paper, we develop a framework for the design and analysis of WEHCRNs with spatial randomly distributed nodes (WEH-RCRNs). We first propose an efficient relay selection strategy in WEHRCRNs to determine when and which relay should be selected to assist transmission. Then, based on the proposed relay selection strategy, we derive the expression for outage probability to measure the outage performance of WEH-RCRNs. Finally, the impacts of related network parameters on the outage probability is also explored on the basis of our analysis results.