Resource Allocation for OFDM Relaying Wireless Power Transfer Based Energy-Constrained UAV Communication Network

Lu, Weidang; Fang, Shanzhen; Gong, Yi; Qian, Liping; Liu, Xin; Hua, Jingyu

doi:10.1109/iccw.2018.8403627

Cited by 11 publications

(6 citation statements)

References 19 publications

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“…The signal bandwidth w is 1MHz, and the noise power at the handset σ 2 is −114dBm. It is assumed that the WPT and WIT links work with the same channel model as in [19] and [26]. The pathloss exponent is set as 3.8, the body shadowing is modeled as a Gauss-distributed random variable with zero mean and variance 14dB, and the small-scale fading is modeled as Rayleigh fading with unit mean.…”

Section: Simulation Resultsmentioning

confidence: 99%

A Sum-Utility Maximization Approach for Fairness Resource Allocation in Wireless Powered Body Area Networks

et al. 2019

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Wireless body area networks (WBANs) are essential for monitoring physiological signals of the human body, but the lifetime of WBANs is limited by battery longevity and it is not convenient or feasible for replacing the batteries of the sensors. The newly emerged energy-harvesting technology provides the potential to break the battery limitation of WBANs. However, the radio resource of a WBAN should be carefully scheduled for the wireless power transfer links and wireless information transmission links; otherwise, severely unfair resource allocation could be incurred due to the difference of channel qualities of the sensors. In this paper, we propose a marginal utility theoretic method to allocate the radio resource to the on-/in-body sensors in a fair and efficient manner. Especially, we consider that the sensors are wireless powered by multiple pre-installed radio-frequency energy sources. First, the utility function for a sensor node is proposed, which can map the achievable throughput to a satisfaction level of network QoS. Then, the fairness resource allocation among the sensor nodes is modeled as a sum-utility maximization problem. By using the dual decomposition method, the optimal solution to the proposed problem can finally be solved in the closed form. In comparison with the sum-throughput maximization and common-throughput maximization methods, the simulation results show that the proposed sum-utility maximization method can bring a fair throughput allocation for the sensors with different channel conditions, and the performance loss to the sum-throughput maximization method is small, while the sum-throughput maximization method is extremely unfair. INDEX TERMS Wireless body area networks, wireless power transfer, utility theory, convex optimization.

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Section: Simulation Resultsmentioning

confidence: 99%

A Sum-Utility Maximization Approach for Fairness Resource Allocation in Wireless Powered Body Area Networks

et al. 2019

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“…Yin et al [30] established a typical single source and dual target system model and derived the solution of multiple parameters joint optimization with throughput maximization. Lu et al [31] proposed an energy constrained UAV communication network protocol based on OFDM relay wireless power transmission. Yin et al [32] gave several surveys for energy constrained UAV cellular network, which acts as a relay for all users to increase the uplink rate through cooperative communication.…”

Section: B Related Workmentioning

confidence: 99%

Performance Analysis of UAV Relay Assisted IoT Communication Network Enhanced With Energy Harvesting

Zhou

et al. 2019

IEEE Access

137

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This paper investigated the multiple unmanned aerial vehicle (UAV) relays' assisted network in the Internet of Things (IoT) systems enhanced with energy harvesting in order to overcome the largescale fading between source and sink as well as achieve the green cooperative communications, where time switch (TS) and power splitting (PS) strategies were typically applied for UAV relays to implement energy harvesting transmission, which was also selected via signal to noise ratio (SNR) maximization criterion so that the terminal node can obtain the optimal signal. Meanwhile, it was worth noting that the terminal node may be disturbed by aggregated interference caused by dense network signaling interaction in the future 5G/B5G systems. Therefore, after TS and PS protocols designing and utilizing, the closed-form expressions of outage probability and bit error rate (BER) for UAV relay assisted IoT systems suffered from aggregated interference were derived in detail. In addition, the throughput and delay limited state of UAV relay assisted transmission were also analyzed thoroughly. The derivations and analysis results showed that the proposed multi-parameter joint optimization of transmitting power, scaling factor, and UAV relay selection could effectively improve the system throughput and reduce the system outage probability and BER. The simulation experiments verified the effectiveness of the proposed schemes and the correctness of theoretical analysis. INDEX TERMS Unmanned aerial vehicles (UAV), relay assisted, IoT, energy harvesting, protocol design, aggregate interference.

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“…Using laser power as energy supply resource for UAV, the work in [12] maximized the UAV's communication throughput by jointly optimizing the UAV's trajectory and its transmit power allocation. The authors of [13] proposed an orthogonal frequency division multiplexing relaying based SWIPT protocol for energy-constrained UAV communication network. The authors of [14] solved the end-to-end cooperative throughput maximization problem by using UAV serves as an aerial mobile relay and its transmission capability powered with SWIPT.…”

Section: Related Workmentioning

confidence: 99%

Beacon in the Air: Optimizing Data Delivery for Wireless Energy Powered UAVs

Jin

Jin²,

Zhang

2019

Machine Learning and Intelligent Communications

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UAV-aided Internet of Things (IoT) systems enable IoT devices to relay up-to-date information to base stations with UAVs, which extends the IoT network coverage and improves data transmission efficiency. To achieve a perpetual UAV data delivery system, simultaneous wireless data and power transfer (SWIPT) is employed for energyconstrained UAVs to harvest energy from wireless chargers to support data sensing and transmission from IoT devices (e.g., sensors) deployed at different locations. In this paper, the design objective is to pursue the optimal energy charging policy for each UAV considering the system states of location, the queue length and energy storage. We formulate and solve a Markov decision process for the UAV data delivery to optimally take the actions of energy charging, and data delivery to base stations. The performance evaluation shows that the proposed MDP scheme outperforms baseline schemes in terms of lower expected overall cost and high energy efficiency.

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Resource Allocation for OFDM Relaying Wireless Power Transfer Based Energy-Constrained UAV Communication Network

Cited by 11 publications

References 19 publications

A Sum-Utility Maximization Approach for Fairness Resource Allocation in Wireless Powered Body Area Networks

A Sum-Utility Maximization Approach for Fairness Resource Allocation in Wireless Powered Body Area Networks

Performance Analysis of UAV Relay Assisted IoT Communication Network Enhanced With Energy Harvesting

Beacon in the Air: Optimizing Data Delivery for Wireless Energy Powered UAVs

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