• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.10A
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• pp.823-829
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• 2011

Recently, wireless body area network (WBAN) has received much attention as an application for the ubiquitous healthcare system. In WBAN, each sensor nodes and a personal base station such as PDA have an energy constraint and computation overhead should be minimized due to node's limited computing power and memory constraint. The reliable data transmission also must be guaranteed because it handles vital signals. In this paper, we propose a systematic network coding scheme for WBAN to reduce the network coding overhead as well as total energy consumption for completion the transmission. We model the proposed scheme using Markov chain. To minimize the total energy consumption for completing the data transmission, we made the problem as a minimization problem and find an optimal solution. Our simulation result shows that large amount of energy reduction is achieved by proposed systematic network coding. Also, the proposed scheme reduces the computational overhead of network coding imposed on each node by simplify the decoding process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1357-1372
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• 2017

Energy harvesting techniques, particularly radio frequency energy harvesting (RF-EH) techniques, which are known to provide feasible solutions to enhance the performance of energy constrained wireless communication systems, have gained increasing attention. In this paper, we consider a wireless-powered cooperative communication network (WPCCN) for transferring energy in the downlink and forwarding signals in the uplink. The objective is to maximize the average transmission rate of the system, subject to the total network power constraint. We formulate such a problem as a form of wireless energy transmission based on resource allocation that searches for the joint subcarrier pairing and the time and power allocation, and this can be solved by using a dual approach. Simulation results show that the proposed joint optimal scheme can efficiently improve system performance with an increase in the number of subcarriers and relays.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1854-1868
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• 2018

A wireless body-sensor network (WBSN) refers to a network-configured environment in which sensors are placed on both the inside and outside of the human body. The sensors are much smaller and the energy is more constrained when compared to traditional wireless sensor network (WSN) environments. The critical nature of the energy-constraint issue in WBSN environments has led to numerous studies on the reduction of energy consumption of WBSN sensors. The transmission-power-control (TPC) technique adjusts the transmission-power level (TPL) of sensors in the WBSN and reduces the energy consumption that occurs during communications. To elaborate, when transmission sensors and reception sensors are placed in various parts of the human body, the transmission sensors regularly send sensor data to the reception sensors. As the reception sensors receive data from the transmission sensors, real-time measurements of the received signal-strength indication (RSSI), which is the value that indicates the channel status, are taken to determine the TPL that suits the current-channel status. This TPL information is then sent back to the transmission sensors. The transmission sensors adjust their current TPL based on the TPL that they receive from the reception sensors. The initial TPC algorithm made linear or binary adjustments using only the information of the current-channel status. However, because various data in the WBSN environment can be utilized to create a more efficient TPC algorithm, many different types of TPC algorithms that combine human movements or fuse TPC with other algorithms have emerged. This paper defines and discusses the design and development process of an efficient TPC algorithm for WBSNs. We will describe the WBSN characteristics, model, and closed-loop mechanism, followed by an examination of recent TPC studies.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2686-2708
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• 2020

This paper investigates the energy efficiency of energy harvesting (EH) bidirectional cooperative sensor networks, in which the considered system model enables the uplink information transmission from the sensor (SN) to access point (AP) and the energy supply for the amplify-and-forward (AF) relay and SN using power-splitting (PS) or time-switching (TS) protocol. Considering the minimum EH activation constraint and quality of service (QoS) requirement, energy efficiency is maximized by jointly optimizing the resource division ratio and transmission power. To cope with the non-convexity of the optimizations, we propose the low complexity iterative algorithm based on fractional programming and alternative search method (FAS). The key idea of the proposed algorithm first transforms the objective function into the parameterized polynomial subtractive form. Then we decompose the optimization into two convex sub-problems, which can be solved by conventional convex programming. Simulation results validate that the proposed schemes have better output performance and the iterative algorithm has a fast convergence rate.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.738-743
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• 1991

A multiobjective analysis technique was applied for the optimum operation of pumps and reservoirs in service water transmission systems. Three major objectives were identified and assessed on the normally operating service water transmission systems. They are, 1) stability of pump operation; 2) economic point of view in minimizing the energy cost for pumping; 3) reliability in meeting the stochasticaly varying demands. The measures of these objectives were required times of pump on-offs in stability, required total energy cost in economics, and minimum required storage during the operating horizon in reliability. In order to find the best meeting solution to the decision maker, a set of non-dominated solutions which show the tradeoff relationships between the considering objectives were generated. The DM selects the best solution from this explicit tradeoff relationships using his heuristic decision rules or experience. The theory was verified by applying to the Kumi Service Water System. A combined technique of the ${\varepsilon}-constraint$ and the weighting methods was used to generate the nondominated solutions, and the dynamic programming algorithm was applied to find the optimal solution for the discretized multi-objective analysis problems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7A
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• pp.660-668
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• 2010

In energy resource constrained networks, the network lifetime can be enhanced by optimally allocating energy resource among users based on the available channel state information and the residual energy information at each node. In this paper, we propose the relay selection scheme and power allocation scheme to maximize the network lifetime in wireless relay networks with capacity constraint. The computer simulation results show that the proposed scheme increase the network lifetime in comparison to the conventional schemes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5B
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• pp.327-337
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• 2012

There have been lots of researches on the optimal relay selection in relay-based systems. However, most researches have been focused on the maximization of transmission capacity with a constraint of sum power at both transmitter and relays. In Ad-hoc networks where relays have batteries of limited power, it is imperative to minimize the energy consumption while maintaining the required quality-of-service (QoS). In this paper, we propose an optimal relay selection strategy to minimize the relay power consumption while satisfying the required signal-to-noise ratio (SNR). Through intensive simulations, we show the proposed method is more effective in terms of energy consumption and guarantee lower transmission failure probability in multi-hop Ad-hoc environments.

• Journal of IKEEE
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• v.22 no.3
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• pp.862-865
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• 2018

The proposed scheme minimizes the Idle time under the residual energy of the sensor node to adjust the Sleep-Wakeup period and minimize unnecessary energy consumption. It is The proposed scheme minimizes the Idle time under the residual energy of the sensor node to adjust the Sleep-Wakeup period and minimize unnecessary energy consumption. It is an important process to control the Application Packet Framework including the PHY and the MAC layer at each node's Idle time with the Idle time mechanism state before the proposed function is executed. The Current Control Level of the Report Attribute is fixed at one sending / receiving node where power consumption can occur, by changing Sleep-Wakeup time, the low power consumption efficiency was improved while satisfying the transmission requirement of the given delay time constraint.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.3B
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• pp.247-254
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• 2009

Over the last decade multiple-input and multiple-output (MIMO) systems have been actively researched and started to be deployed in wireless communications owing to the significant increase in channel capacity. In this paper, we propose a energy saving MAC protocol in systems by focusing on energy efficiency instead of capacity maximization. We considers the energy consumption together with the tradeoff between reliability (i.e., diversity) and throughput (i.e., multiplexing gain), and dynamically chooses an appropriate number of antennas for transmission. In computing the total energy consumption, we counts circuit energy as well as transmission energy. Naturally the circuit energy consumption is directly proportional to the number of active antennas. Through numerical analysis, we confirm that our power saving MAC scheme for MIMO considerably saves energy consumption compared to conventional capacity maximization schemes that use a fixed number of MIMO channels, for a given outage constraint. Our finding is that the capacity maximizing communication which possibly can be regarded best in terms of energy efficiency gives a different solution from the energy minimizing communication.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.3-9
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• 2015

Under the maximum transmit power constraint and the minimum rate constraint, we propose the optimal number of transmit antennas and transmit power which maximize energy-efficiency (EE) in multi-user multiple-input multiple-output (MIMO) downlink system with the maximal ratio transmission (MRT) precoding. Because the optimization problem for the instantaneous channel is difficult to solve, we use independence of individual channel, average channel gain and path loss to approximate the objective function. Since the approximated EE optimization problem is two-dimensional search problem, we find the optimal number of transmit antennas and transmit power using Lagrange multipliers and our proposed algorithm. Simulation results show that the number of transmit antennas and power obtained by proposed algorithm are almost identical to the value by the exhaustive search.