• Journal of Satellite, Information and Communications
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• v.12 no.2
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• pp.89-93
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• 2017

This paper introduces an energy harvesting system that generates energy by collecting multi-band RF signals using buck-boost DC-DC converter. In an environment where the resistance of load using the collected electric energy is constantly changing, a buck-boost DC-DC converter is used in which the input resistance of the DC-DC converter does not change even if the load resistance changes. Since the frequency band of the input RF signal varies, the rectifier is designed for each band so that multiple bands can be processed, and a matching circuit is added to each band in front of the rectifier. For a rectifier to collect very small RF signals, a circuit is designed so that a constant voltage is obtained according to a very small input signal by devising a method of continuously accumulating the voltages collected and generated in each band. It is confirmed that the output efficiency can reach up to 20% even for the RF signal having the input of -20 dBm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.6
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• pp.597-611
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• 2009

With the advent of ubiquitous computing society, many advanced technologies have enabled wireless sensor networks which consist of small sensor nodes. However, the sensor nodes have limited computing resources such as small size memory, low battery life, short transmission range, and low computational capabilities. Thus, decreasing energy consumption is one of the most significant issues in wireless sensor networks. In addition, numerous applications for wireless sensor networks are recently spreading to various fields (health-care, surveillance, location tracking, unmanned monitoring, nuclear reactor control, crop harvesting control, u-city, building automation etc.). For many of them, supporting security functionalities is an indispensable feature. Especially in case wireless sensor networks should provide a sufficient variety of security functions, sensor nodes are required to have more powerful performance and more energy demanding features. In other words, simultaneously providing security features and saving energy faces a trade-off problem. This paper presents a novel energy-efficient security architecture in an IEEE 802.15.4-based wireless sensor network called the Hybrid Adaptive Security (HAS) framework in order to resolve the trade off issue between security and energy. Moreover, we present a performance analysis based on the experimental results and a real implementation model in order to verify the proposed approach.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.2
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• pp.269-276
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• 2016

Internet of Things (IoT) is based on wireless networks being able to connect things and people on a large scale. In the IoT environment, reliable broadcast plays an important role to distribute data to a large number of devices. Energy harvesting from a surrounding environment is a key technique to achieve a sustainable IoT network. In IoT networks, a problem of transmission errors and energy shortage should be mitigated for reliable broadcast. In this paper, we propose an energy-efficient and reliable broadcast method to consider packet errors and energy consumption in the environment where a large number of nodes are connected. The proposed scheme can improve data restoration probability by up to 15% and reduce energy consumption by up to 17%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.1
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• pp.268-278
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• 2017

In this paper, we propose two novel detection schemes with low-complexity based on the unified receiver architecture which minimizes a fundamental tradeoff at rate-energy region in SWIPT system. The proposed detection schemes are twofold: The two-stage detection scheme and Euclidean distance combination detection scheme. The two-stage detection scheme detects amplitude information of symbols from rectified signals for energy harvesting. In the sequel, it detects symbols based on phase information of baseband signals for information decoding. The Euclidean distance combination detection scheme detects symbols using linear positive-weighted sum of two metrics: Euclidean distance based on baseband signals for information decoding and Euclidean distance based on rectified signals for energy harvesting. For numerical results, we confirm that the proposed detection scheme can achieve better performance than the conventional scheme in terms of symbol error rate, symbol success rate-energy region and achievable rate-energy region.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.1900-1911
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• 2015

In this paper, we introduce backscatter communication for power-limited sensors to enable long-range transmission in wireless sensor networks, and envision a way to avoid doubly near-far problem in wireless-powered communication network (WPCN) with this technology. In backscatter based WPCN, users harvest energy from both the signal broadcasted by the hybrid access point and the carrier signal transmitted by the carrier emitter in the downlink, and then transmit their own information in a passive way via the reflection of the carrier signal using frequency-shift keying modulation in the uplink. We characterize the energy-free condition and the signal-to-noise ratio (SNR) outage zone in backscatter based WPCN. Further, we propose backscatter based harvest-then-transmit protocol to maximize the sum-throughput of the backscatter based WPCN by optimally allocating time for energy harvesting and information transmission. Numerical results demonstrate that the backscatter based WPCN increases significantly the transmission range and diminishes greatly the SNR outage zone.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2399-2418
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• 2023

The paper focuses on investigating secure transmission in wireless powered communication networks (WPCN) that involve multiple energy-constrained relays and one energy-constrained source. The energy is harvested from a power beacon (PB) while operating in the presence of a passive eavesdropper. The study primarily aims to achieve energy-efficient secure communications by examining the impact of channel estimation on the secrecy performance of WPCN under both perfect and imperfect CSI scenarios. To obtain practical insights on improving security and energy efficiency, we propose closed-form expressions for secrecy outage probability (SOP) under the linear energy harvesting (LEH) model of WPCN. Furthermore, we suggest a search method to optimize the secure energy efficiency (SEE) with limited power from PB. The research emphasizes the significance of channel estimation in maintaining the desired performance levels in WPCN in real-world applications. The theoretical results are validated through simulations to ensure their accuracy and reliability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1560-1566
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• 2015

To enable the efficient use of energy, the environment where unscheduled receivers can harvest energy from the transmitted signal is considered in next-generation wireless communication systems. In this paper, we propose a scheme for allocating subchannel and power to maximize the system throughput and harvested energy simultaneously using optimization techniques. Through simulations, we verify that the proposed scheme can increase the system throughput and harvested energy harmoniously. In particular, the proposed scheme improves the harvested energy remarkably with a negligible degradation of system throughput, compared with conventional scheme, as a result, energy can be used efficiently in the system.

• Journal of Communications and Networks
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• v.18 no.6
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• pp.926-937
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• 2016

In this paper, we study the feasibility of receiver diversity for application to downlink cellular networks, where low-energy devices are equipped with information decoding and energy harvesting receivers for simultaneous wireless information and power transfer. We compare several options that are based on selection combining and maximum ratio combining, which provide different implementation complexities. By capitalizing on the Frechet inequality, we shed light on the advantages and limitations of each scheme as a function of the transmission rate and harvested power that need to be fulfilled at the low-energy devices. Our analysis shows that no scheme outperforms the others for every system setup. It suggests, on the other hand, that the low-energy devices need to operate in an adaptive fashion, by choosing the receiver diversity scheme as a function of the imposed requirements. With the aid of stochastic geometry, we introduce mathematical frameworks for system-level analysis. We show that they constitute an important tool for system-level optimization and, in particular, for identifying the diversity scheme that optimizes wireless information and power transmission as a function of a sensible set of parameters. Monte Carlo simulations are used to validate our findings and to illustrate the trade-off that emerge in cellular networks with simultaneous wireless information and power transfer.

• Journal of Satellite, Information and Communications
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• v.12 no.4
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• pp.100-105
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• 2017

In this paper, we study an interference avoidance scenario in the presence of a interferer which can rapidly observe the transmit power of backscatter communications and effectively interrupt backscatter signals. We consider a power control with a sub-channel allocation to avoid interference attacks and a power-splitting ratio for backscattering and RF energy harvesting in sensors. We formulate the problem based on a Stackelberg game theory and compute the optimal transmit power, power-splitting ratio, and sub-channel allocation parameter to maximize a utility function against the interferer. We propose the utility maximization using Lagrangian dual decomposition for the backscatter communications and the interferer to prove the existence of the Stackelberg equilibrium. Numerical results show that the proposed algorithms effectively maximize the utility, compared to that of the algorithm based on the Nash game, so as to overcome a malicious interference in backscatter communications.

• Journal of Communications and Networks
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• v.14 no.2
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• pp.188-194
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• 2012

Cognitive networks (CNs) are capable of enabling dynamic spectrum allocation, and thus constitute a promising technology for future wireless communication. Whereas, the implementation of CN will lead to the requirement of an increased energy-arrival rate, which is a significant parameter in energy harvesting design of a cognitive user (CU) device. A well-designed spectrum-sensing scheme will lower the energy-arrival rate that is required and enable CNs to self-sustain, which will also help alleviate global warming. In this paper, spectrum sensing in a multi-user cognitive ad hoc network with a wide-band spectrum is considered. Based on the prospective spectrum sensing, we classify CN operation into two modes: Distributed and centralized. In a distributed network, each CU conducts spectrum sensing for its own data transmission, while in a centralized network, there is only one cognitive cluster header which performs spectrum sensing and broadcasts its sensing results to other CUs. Thus, a wide-band spectrum that is divided into multiple sub-channels can be sensed simultaneously in a distributed manner or sequentially in a centralized manner. We consider the energy consumption for spectrum sensing only of an analog-to-digital convertor (ADC). By formulating energy consumption for spectrum sensing in terms of the sub-channel sampling rate and whole-band sensing time, the sampling rate and whole-band sensing time that are optimal for minimizing the total energy consumption within sensing reliability constraints are obtained. A power dissipation model of an ADC, which plays an important role in formulating the energy efficiency problem, is presented. Using AD9051 as an ADC example, our numerical results show that the optimal sensing parameters will achieve a reduction in the energy-arrival rate of up to 97.7% and 50% in a distributed and a centralized network, respectively, when comparing the optimal and worst-case energy consumption for given system settings.