Dynamic spectrum access in cognitive radio networks with RF energy harvesting

Lu, Xiao; Wang, Ping; Niyato, Dusit; Hossain, Ekram

doi:10.1109/mwc.2014.6845054

Cited by 199 publications

(132 citation statements)

References 15 publications

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“…기술이 제안되었다 [7] . 따라서 최근 들어 RF EH와 CR 기술의 결합 연구를 통해 주파수 이용 효율과 에너지 사용 효율을 동시에 개선하고자 하는 연구들이 다양 한 접근 방식으로 활발히 진행되고 있다 [8][9][10][11][12][13] .…”

Section: ⅰ 서 론unclassified

Energy Outage Probability and Achievable Throughput of 2-Channel Sensing Secondary Users in RF Powered Cognitive Radio Networks

Wu¹,

Shin²,

Kim³

2016

The Journal of Korean Institute of Communications and Informati

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Key Words : energy harvesting, cognitive radio, Markov battery model, 2-channel sensing, energy outage, achievable throughput ABSTRACTIn this paper, we consider the secondary users (SUs) who are capable of harvesting energy from ambient radio frequency (RF) signals and are allowed to sequentially sense up to 2 different channels to find out idle channels not occupied by the primary users (PUs). The EH SUs are permitted to transmit data packets only if both idle channels and sufficient energy are available. Compared with traditional SUs, the EH SUs consume energy with data transmission and also harvest energy without additional energy supply. Consequently, the battery state is expected to be fluctuated due to energy consumption and harvesting, and therefore we develop a Markov battery model to provide energy variations at the 2-channel sensing EH SUs. With the proposed battery model, we derive the steady-state probability that the EH SUs completely run out of energy, and the achievable

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Section: ⅰ 서 론unclassified

Energy Outage Probability and Achievable Throughput of 2-Channel Sensing Secondary Users in RF Powered Cognitive Radio Networks

Wu¹,

Shin²,

Kim³

2016

The Journal of Korean Institute of Communications and Informati

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“…Opportunistic spectrum access (OSA) based cognitive radio (CR) paradigm has received significant attention from the academia as well as industrial partners [1][2][3][4][5][6][7][8][9]. In wireless networks, CR paradigm allows unlicensed users to communicate over identified vacant licensed subband(s).…”

Section: Introductionmentioning

confidence: 99%

Decision making policy for RF energy harvesting enabled cognitive radios in decentralized wireless networks

Darak

Zhang

Palicot

et al. 2017

Digital Signal Processing

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. Decision making policy for RF energy harvesting enabled cognitive radios in decentralized wireless networks. Digital Signal Processing, Elsevier, 2017Elsevier, , 60, pp.33-45. 10.1016Elsevier, /j.dsp.2016. hal-01436769 Highlights• Decision making policy for RF Energy Harvesting enabled Cognitive Radio.• Thompson Sampling algorithm based subband statistic estimation and subband access.• Proposed USRP testbed to validate the functionality of the various DMPs. Decision AbstractCognitive radio (CR) paradigm with radio frequency energy harvesting (RFEH) have significant potential to improve the network throughput by utilizing vacant spectrum using battery-operated self-sustainable radio terminals. Research efforts relevant to these paradigms are focused on the mode selection policies which decide when to switch from CR mode (i.e., opportunistic vacant spectrum access mode) to the RFEH mode (i.e., battery charging using ambient RF energy) and vice-versa. So far, very little attention has been paid to the dual but competing task of frequency band selection in CR and RFEH modes under partially observable environment in the decentralized wireless networks. Furthermore, the need of tunable bandwidth frequency band access for CRs and lower subband switching cost (SSC) for energy efficient implementation have made the design of the decision making policy (DMP) more challenging. In this paper, a new CR-RFEH DMP has been proposed for RFEH enabled CR terminals in the decentralized wireless networks. The proposed DMP consists of three sub-units: 1) Bayesian approach based tunable Thompson sampling algorithm for subband statistics estimation, 2) Thompson sampling algorithm based subband access scheme exploiting the past collision events to minimize collisions among CRs, and 3) Mode selection scheme. Simulation results show that the proposed DMP offers 10-35% improvement in the throughput of the decentralized network and 40-90% reduction in the number of subband switchings compared to existing DMPs. The simulation results are then validated using real radio signals on the proposed USRP testbed.

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“…The drawback is regarding power density, especially in an indoor area, where it is often very low [5]. Various RF power density levels for an outdoor environment in [6] have been summarized for several isotropic transmitters. In an indoor environment, a power density of 1 µW/cm 2 at 2.45 GHz spectrum has been used to drive low-power low duty cycle applications [7].…”

Section: Introductionmentioning

confidence: 99%

A Power Processing Circuit for Indoor Wi-Fi Energy Harvesting for Ultra-Low Power Wireless Sensors

Kadir

2017

Applied Sciences

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This article proposes a complete power processing circuit for an indoor 2.45 GHz Wi-Fi energy harvesting system. The proposed power processing circuit works by using power harvested from indoor Wi-Fi transmitters. The overall system of this work is simplified as an equivalent circuit and analyzed mathematically. A two-port network is analyzed in formulating the relevant equations of the equivalent circuit. The importance of matching the impedance of a harvesting antenna to the rectifier circuit is highlighted by using simulation analysis, and it is shown that the impedance matching for both components has satisfied the conditions for a high sensitivity circuit and radio frequency-to-direct current (RF-to-DC) power conversion. Actual experiments showed that the proposed power processing circuit could operate with an incident power as low as −50 dBm. It has been found that the proposed harvesting system stored 0.11 J in a 200 mF supercapacitor as the storage device in 20 hours of the experimentation periods. Moreover, actual results for the overall energy harvesting system is compared with previous research, and it has been found that the proposed system has advantages over the listed works.

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Dynamic spectrum access in cognitive radio networks with RF energy harvesting

Cited by 199 publications

References 15 publications

Energy Outage Probability and Achievable Throughput of 2-Channel Sensing Secondary Users in RF Powered Cognitive Radio Networks

Energy Outage Probability and Achievable Throughput of 2-Channel Sensing Secondary Users in RF Powered Cognitive Radio Networks

Decision making policy for RF energy harvesting enabled cognitive radios in decentralized wireless networks

A Power Processing Circuit for Indoor Wi-Fi Energy Harvesting for Ultra-Low Power Wireless Sensors

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