Abstract
Wireless power transfer (WPT) is an effective way to prolong the lifetime of the energy-constraint networks. In this paper, we investigate a wireless powered cooperative non-orthogonal multiple access (WP-CNOMA) system, consisting of a power beacon (PB), an information transmitter (S), multiple relays (R) and two information receiving devices with near device <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$D_{1}$ </tex-math></inline-formula> and far device <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$D_{2}$ </tex-math></inline-formula> . We assume both S and R are energy-constraint and there is no direct link between S and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$D_{2}$ </tex-math></inline-formula> . With the help of PB, S and R can harvest energy from it to restart the communication for WP-CNOMA network. For such a system, low-complexity but effective relay and antenna selection schemes are applied. To characterize the performance, outage probabilities and average throughput are derived for linear and non-linear energy harvesting (EH) models, respectively. Moreover, to maximize the average throughput, invoking the unimodal feature for average throughput with respect to the EH time, we find the optimal EH time via Golden section search method. Simulation results validate the accuracy of analytical results, and reveal the performance gain for our system over the benchmark schemes. Also, it can be seen that the non-linear EH model shows different outage behaviors from the linear one. On the other hand, considering the practical application and to improve the performance, the optimization for a simple WP-CNOMA system with single-antenna PB and single relay is also investigated, in which we aim to maximize the minimum throughput by jointly optimizing EH time and power allocation. A low-complexity analytical method is developed to find the max-min rate. Numerical results show that through optimization, the system performance can be improved significantly.
Highlights
W IRELESS power transfer (WPT) has emerged as a promising means to prolong the lifetime of the energy-constraint wireless networks, such as wireless sensor network (WSN) and mesh network in the field or postdisaster emergency communication [1]
As mentioned in [30], the devices in WSN or in the Internet of Things (IoT) are characterized by low power and low cost, and here we focus on the optimal design for a simple WP-cooperative relaying and NOMA (CNOMA) system with K = 1 and N = 1, where |hSR|2 < |hS1|2
It has been shown that the theoretical analyses are in good agreement with the simulated results and the superiority of WP-CNOMA system over the corresponding orthogonal multiple access (OMA) one has been validated with proper power allocation and energy harvesting (EH) time
Summary
W IRELESS power transfer (WPT) has emerged as a promising means to prolong the lifetime of the energy-constraint wireless networks, such as wireless sensor network (WSN) and mesh network in the field or postdisaster emergency communication [1]. There are two kinds of WPT-based network: one is simultaneous wireless information and power transfer (SWIPT) [2], in which radio frequency (RF) signals can carry information and energy simultaneously and time switching (TS) or power splitting (PS) protocol is utilized at the receiver to harvest energy and decode signals separately; the other is wireless powered communication network (WPCN) [3], in which the energy-constraint nodes firstly harvest energy from the dedicated power station, such as power beacon (PB) or hybrid access point (HAP), and use the harvested energy to perform the wireless information transfer (WIT). For WPCN, the related works mainly include the applications into relaying network [9], [10], cognitive radio network [11], [12], cellular network [13] and unmanned aerial vehicle (UAV)-assisted communication [14]
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