Design and analysis of RF energy harvesting cognitive relay systems

Abstract

The explosion of Internet of Things (IoT) applications and their integration in various aspects of everyday life necessitates the deployment of modern wireless network that can handle such exponentially rising data traffic. Massive device con nectivity, higher energy- and spectrum- efficiency, low signal latency, long battery lifetime etc., are the most important requirements to be considered for deploying the next-generation communication networks. In this regard, cognitive radio (CR) and non-orthogonal multiple access (NOMA) have emerged as promising technologies for wireless networks owing to their capability of providing massive connectivity with higher spectrum efficiency (SE). By utilizing CR technology, secondary and primary users can coexist in the same spectrum bands by effectively discarding interference and collision, and thereby improve the SE measures. Out of the many contenders of fifth-generation (5G) communications, NOMA is considered as a promising tech nology that improves SE by manifolds. This makes NOMA a prominent candidate for IoT sensor networks. The basic idea of NOMA is to employ superposition cod ing to multiplex the multiple users’ signals at the transmitter, and then to perform successive interference cancellation (SIC) at the receiver side to decode the signals in the power domain. The incorporation of NOMA into CR, referred to as cogni tive NOMA (CNOMA), has demonstrated the capability to achieve higher SE while simultaneously reducing the complexity of the power allocation (PA) design. It can potentially fulfil the peculiarity of a 5G wireless network that provides a high throughput, broad connectivity, and low latency.