Multi-Hop Cognitive Wireless Powered Networks: Outage Analysis and Optimization

Abstract

This paper analyzes and optimizes the outage performance of multi-hop cognitive wireless powered networks (CWPNs) in underlay paradigms. To be specific, there are multiple power beacons (PBs) performing wireless power transfer (WPT) for multiple battery-free secondary users (SUs). Correspondingly, the SUs first harvest energy from the RF signals of PBs and then execute multi-hop cognitive data transmission in the licensed channel concurrently with the primary users (PUs). Therefore, the transmit power of SUs are subject to the energy causality constraint imposed by WPT and the interference power constraint from multiple PUs. We derive and obtain the closed-form exact and asymptotic end-to-end outage probabilities for multi-hop CWPNs over Rayleigh block fading. Furthermore, we optimize the outage performance by studying the outage minimization problem with respect to the WPT power and the WPT time. Due to the complexity of outage probability, we propose a self-adaptive particle swarm optimization (SA-PSO)-based resource allocation algorithm to jointly optimize the power and time for WPT. Extensive simulations validate the correctness of theoretical analysis and the effectiveness of the proposed optimization algorithm. INDEX TERMS Multi-hop, cognitive wireless powered networks, energy harvesting, outage probability, particle swarm optimization.

Performance Optimization for Decode and Forward Cooperative Cognitive Radio Networks

“…A concept of greenhouse gas emission was proposed in cooperative cognitive radio networks in [1], where total rate maximization, gas emission minimization, and relay selection problems were achieved simultaneous by lexicographic multiobjective optimization methods. At the constraints of wireless transfer power and time, an outage probability optimization problem was studied in [2] for battery free secondary users by particle swarm algorithm. Taking into account of the spatial randomly distributed nodes, the relay forwarding time was decided the relay forwarding time according to the outage optimization problem in [3].…”

“…The above references solved an optimization problem under certain constraints. For example, the total power and total interference constraints were considered in [1,4], while the power and time slot constraints were absorbed in [2]. Different constraints consider different actual scenarios, thereby defining different optimization problems.…”

“…Specifically, we formulate a rate minimum maximization problem. (2) In order to fully account for the impact of the two factors on the rate, without missing any possibilities, we have clarified four distinct scenarios: total interference threshold and total power budget, total interference threshold and separate power budget, separate interference threshold and total power budget, and separate interference threshold and separate power budget.…”

Sum‐throughput maximization for overlay cognitive wireless powered network with energy harvesting capability

“…In References 37,38 another type of RF‐powered CR networks has been investigated where the only energy source for the secondary users (SUs) is the RF signals radiated by PT. In this network, known as underlay multi‐hop cognitive WPCN, multiple SUs operate to harvest both the energy and spectrum from the PT.…”

“…Once enough energy is harvested, the multi‐hop cognitive data transmission is performed on a licensed channel. Optimal allocation of radio resources in References 37,38 results in maximization of end‐to‐end throughput and minimization of end‐to‐end outage probabilities in these networks, respectively.…”