Throughput of a Cognitive Radio Network With Energy-Harvesting Based on Primary User Signal

In this letter, we analyze an energy-harvesting-based cognitive radio (CR) system. The CR system harvests energy from the radio frequency (RF) signal of primary user (PU) during sensing time as well as the transmission time of a detection cycle if PU is present. The CR accesses the spectrum band of PU opportunistically using the energy harvested over the frames with PU present, while maintaining a quality of service (QoS) constraint on PU in terms of a collision probability. An optimal sensing time is found, which maximizes the harvested energy. The performance is investigated in terms of harvested energy, outage probability, and throughput of the network. Novel analytical expressions for average harvested energy and average throughput are developed under such a scenario, which are validated by simulation.

I. Introduction

In wireless communication, CR technology is a promising one to exploit the underutilized PU spectrum band. To exploit the PU band, CR operates in a time slotted model to sense the presence of PU. In the first phase of the detection cycle, it senses the presence of PU, and transmits data in the second phase if PU is absent. Thus the tradeoff between sensing time and throughput is an important issue in CR technology. In [1], authors investigated the optimal sensing time for a target detection probability such that the throughput is maximized. In connection with spectrum sensing and data transmission, management of energy consumption is also an important issue. In an energy constrained CR network, all the nodes are powered by typical batteries which can either be replaced or recharged. Once the battery is depleted, the node becomes dead. In such a situation energy harvesting is a good solution. In energy harvesting, the secondary user (SU) collects energy from RF signals and non RF signals such as solar, temperature etc. Energy harvesting from RF signal has received significant attention in context of wireless communication. In [2], authors proposed an optimal energy management scheme for an energy harvesting sensor node to maximize the throughput. Throughput and ergodic capacity of a wireless relay network have been investigated in [3] where the relay node harvests energy from RF signal to forward the source signal to the destination node. An optimal mode decision policy has been proposed in [4] to maximize the throughput for a non-RF energy harvester based CR system. In [5], authors investigated a spectrum sensing policy and a detection threshold in order to maximize the average throughput of an energy harvesting secondary network considering energy causality constraints and collision constraints. A hybrid underlay-overlay model for energy-harvesting CR network has been investigated in [6]. It is to be noted that both SU and CR node indicates the same thing and hence used interchangeably.