Performance analysis of cognitive radio based internet-of-things network for energy efficiency and spectrum utilization

Abstract

Energy and Spectrum are the two basic requirements in the realm of Internet-of-Things (IoT). The network of IoT is becoming larger day by day and the design of spectrum and energy efficient solution is a quite challenging task because of the rapid increase of connecting devices in IoT network. To make the system more energy and spectral efficient, energy harvesting and cognitive radio (CR) are the proficient solutions, respectively. This paper introduces a spectral and energy efficient design for CR based sensor networks. We present a network architecture, in which nodes or other sensing devices can use the spectrum opportunistically and energy harvesting can be done from different ambient sources. We then propose an 1) energy alancing scheme for heterogeneous network in which nodes will have different energy levels and 2) Cluster head (CH) selection scheme which will only be performed on the few nodes of network having the highest current energy to accomplish the ultimate goal of energy balancing in network, this analysis is performed with in the cluster. Furthermore, for the spectral efficiency, we propose a channel management scheme based on cognitive radio to allot the best available channel having highest reliability in respect of the bit error rate (BER) using. Comprehensive results exhibit the effectiveness in the performance of the proposed spectral and energy efficient schemes and show better performance over other schemes.