• Journal of Communications and Networks
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• v.18 no.3
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• pp.320-326
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• 2016

In existing literature on multiple-input multiple-output (MIMO) relaying communication systems, antenna selection is often implemented by maximizing the channel capacity or the output single-to-noise ratio (SNR). In this paper, we propose an energy-efficient low-complexity antenna selection scheme for MIMO relaying communication systems. The proposed algorithm is based on beamforming and maximizing the Frobenius norm to jointly optimize the transmit power, number of active antennas, and antenna subsets at the source, relaying and destination. We maximize the energy efficiency between the link of source to relay and the link of relay to destination to obtain the maximum energy efficiency of the system, subject to the SNR constraint. Compared to existing antenna selection methods forMIMO relaying communication systems, simulation results demonstrate that the proposed method can save more power in term of energy efficiency, while having lower computational complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3771-3788
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• 2015

This paper studies the distributed energy efficient resource management in the Internet of Things (IoT). Wireless communication networks support the IoT without limitation of distance and location, which significantly impels its development. We study the communication channel and energy management in the wireless communication network supported IoT to improve the ability of connection, communication, share and collaboration, by using the game theory and distributed learning algorithm. First, we formulate an energy efficient neighbor collaborative game model and prove that the proposed game is an exact potential game. Second, we design a distributed energy efficient channel selection learning algorithm to obtain the global optimum in a distributed manner. We prove that the proposed algorithm will asymptotically converge to the global optimum with geometric speed. Finally, we make the simulations to verify the theoretic analysis and the performance of proposed algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.607-608
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• 2012

Data aggregation is a fundamental problem in wireless sensor networks which attracts great attention in recent years. Delay and energy efficiencies are two crucial issues of designing a data aggregation scheme. In this paper, we propose a distributed, energy efficient algorithm for collecting data from all sensor nodes with the minimum latency called Delay-aware Power-efficient Data Aggregation algorithm (DPDA). The DPDA algorithm minimizes the latency in data collection process by building a time efficient data aggregation network structure. It also saves sensor energy by decreasing node transmission distances. Energy is also well-balanced between sensors to achieve acceptable network lifetime. From intensive experiments, the DPDA scheme could significantly decrease the data collection latency and obtain reasonable network lifetime compared with other approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.2946-2962
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• 2017

An improved energy-efficient compressed network coding method is proposed for the data communication in the wireless sensor networks (WSNs). In the method, the compressed sensing and network coding are jointly used to improve the energy efficiency, and the two-hop neighbor information is employed to choose the next hop to further reduce the number of the transmissions. Moreover, a new packet format is designed to facilitate the intermediate node selection. To theoretically verify the efficiency of the proposed method, the expressions for the number of the transmissions and receptions are derived. Simulation results show that, the proposed method has higher energy efficiency compared with the available schemes, and it only requires a few packets to reconstruct measurements with reasonable quality.

• ETRI Journal
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• v.34 no.6
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• pp.922-931
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• 2012

With the increasing demands for mobile wireless sensor networks in recent years, designing an energy-efficient clustering and routing protocol has become very important. This paper provides an analytical model to evaluate the power consumption of a mobile sensor node. Based on this, a clustering algorithm is designed to optimize the energy efficiency during cluster head formation. A genetic algorithm technique is employed to find the near-optimal threshold for residual energy below which a node has to give up its role of being the cluster head. This clustering algorithm along with a hybrid routing concept is applied as the near-optimal energy-efficient routing technique to increase the overall efficiency of the network. Compared to the mobile low energy adaptive clustering hierarchy protocol, the simulation studies reveal that the energy-efficient routing technique produces a longer network lifetime and achieves better energy efficiency.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.601-602
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• 2011

In wireless sensor networks, coverage problem is a fundamental issue that has attracted considerable attention in recent years. Most node scheduling patterns utilize the adjustable range of sensor to minimize the sensing energy consumption. However, a large source of consumption of communication energy of sensor is not strictly taken into account. In this paper, we introduce an energy-efficient pattern that is used to minimize the communication energy consumption of a sensor network. Calculations and extensive simulation are conducted to evaluate the efficiency of the new pattern comparing to existing ones.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.114-130
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• 2021

With the drastic growth of Information and Communication Technology (ICT) industry, global energy consumption is exponentially increased by mobile communications. The huge energy consumption and increased environmental awareness have triggered great interests on the research of dynamic distribution of cell user and traffic, and then designing the energy efficient cellular network. In this paper, we explore the temporal and spatial characteristics of human mobility and traffic distribution using real data set. The analysis results of cell traffic illustrate the tidal effect in temporal and spatial dimensions and obvious periodic characteristics which can be used to design Base Station (BS) dynamic with sleeping or shut-down strategy. At the same time, we designed a new Cell Zooming and BS cooperation mode. Through simulation experiments, we found that running in this mode can save about 35% of energy consumption and guarantee the required quality of service.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.108-112
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• 2021

For smart mobile devices, the wireless communication module is one of the hardware modules that consume the most energy. If we can build a multi-channel multi-interface environment using heterogeneous communication modules and operate them dynamically, data transmission performance can be highly improved by increasing the parallelism. Also, because these heterogeneous modules have different data rates, transmission ranges, and power consumption, we can save energy by exploiting a power efficient and low speed wireless interface module to transmit/receive sporadic small data. In this paper, we propose a power efficient data transmission method using heterogeneous communication networks. We also compared the performance of our proposed scheme to a conventional scheme, and proved that our proposed scheme can save energy while guaranteeing reasonable data delivery time.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06d
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• pp.267-268
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• 2011

Recent research activities in cooperative communication focus on achieving energy efficiency and reliability. Relay selection strategy for cooperative communication improves the performance significantly. However, due to imbalance consumption of power, network might die earlier and more than 90% energy remains unused. In this paper, we provide a framework of an energy-efficient medium access control protocol that minimizes these problems and improves energy efficiency.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.3-9
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• 2014

We propose energy efficient transmit and receive strategies for nomadic M2M devices. Recently, communication applications consume more and more battery. Hence, the efficient battery management is becoming increasingly important. Turbo code as a channel coding is being widely used in many communication areas. Accordingly, the efficient energy management in using turbo code is an important issue. In this paper, we optimize joint transmit and receive energy for M2M devices pair. We first model the transmit energy and receive energy. Then, we develop the energy efficient transmit and receive strategies.