• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.3
• /
• pp.1325-1344
• /
• 2019

Recently, to satisfy mobile users' increasing data transmission requirement, energy efficiency (EE) resource allocation in distributed antenna systems (DASs) has become a hot topic. In this paper, we aim to maximize EE in DASs subject to constraints of the minimum data rate requirement and the maximum transmission power of distributed antenna units (DAUs) with different density distributions. Virtual cell is defined as DAUs selected by the same user equipment (UE) and the size of virtual cells is dependent on the number of subcarriers and the transmission power. Specifically, the selection rule of DAUs is depended on different scenarios. We develop two scenarios based on the density of DAUs, namely, the sparse scenario and the dense scenario. In the sparse scenario, each DAU can only be selected by one UE to avoid co-channel interference. In order to make the original non-convex optimization problem tractable, we transform it into an equivalent fractional programming and solve by the following two sub-problems: optimal subcarrier allocation to find suitable DAUs; optimal power allocation for each subcarrier. Moreover, in the dense scenario, we consider UEs could access the same channel and generate co-channel interference. The optimization problem could be transformed into a convex form based on interference upper bound and fractional programming. In addition, an energy-efficient DAU selection scheme based on the large scale fading is developed to maximize EE. Finally, simulation results demonstrate the effectiveness of the proposed algorithm for both sparse and dense scenarios.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.4
• /
• pp.572-580
• /
• 2021

In order to reduce transmission delay and increase reliability in networks, mainly high-performance and high-power network equipment is used to guarantee network quality. In this paper, we propose an optimization algorithm to minimize the energy consumed when transmitting traffic in networks with a bundle link composed of multiple physical cables. The proposed optimization algorithm is a meta-heuristic method, which uses tabu search algorithm. In addition, it is designed to minimize transmission energy by minimizing the cables on the paths of the source and destination nodes for each traffic. In the proposed optimization algorithm, performance evaluation was performed in terms of the number of cables used in the transmission and the link utilization for all traffic on networks, and the performance evaluation result confirmed the superior performance than the previously proposed method.

• Advances in Energy Research
• /
• v.2 no.2
• /
• pp.61-72
• /
• 2014

This paper's aim is to do a global evaluation (considering four dimensions: technical-economic, environmental, social and political) in the ways of natural gas transportation (gas pipelines, GNL and GTL) and electric transmission, in order to supply the energy demands of Mato Grosso do Sul, a brazilian state. The transport ways had been compared between itself using a software of decision taking (Decision Lens Suite), which determined a better way for transporting natural gas in this case. In a generalized manner the gas pipeline is the best way of transporting natural gas, therefore it takes advantage in the majority of the analyzed dimensions.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.13 no.1
• /
• pp.109-114
• /
• 2013

In underwater wireless sensor networks, sensing data such temperature and salinity can be merged by averaging them. Data aggregation is a good choice to reduce the amount of packets and save energy in underwater wireless sensor networks. However, data aggregation could bring about packet delay and non-directional transmission to the sink. In this paper, we propose a new path building algorithm based on data aggregation to mitigate these problems. The paper reduces the delay without wireless interferences and maximizes the energy efficiency by removing the non-directional transmission to the sink. Experimental results show that the proposed algorithm outperforms in terms of the energy efficiency and the packet delay.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.10
• /
• pp.3321-3341
• /
• 2014

This paper investigates the outage performance and optimization for the four-phase two-way transmission network with an energy harvesting (EH) relay. To enable the simultaneous information processing and energy harvesting at the relay, we firstly propose a power splitting-based two-way relaying protocol (PSTWR). Then, we discuss its outage performance theoretically and derive an explicit expression for the system outage probability. In order to find the optimal system configuration parameters such as the optimal power splitting ratio and the optimal transmit power redistribution factor, we formulate an outage-minimized optimization problem. As the problem is difficult to solve, we design a genetic algorithm (GA) based algorithm for it. Besides, we also investigate the effects of the power splitting ratio, the power redistribution factor at the relay, and the source to relay distance on the system outage performance. Finally, extensive simulation results are provided to demonstrate the accuracy of the analytical results and the effectiveness of the GA-based algorithm. Moreover, it is also shown that, the relay position greatly affects the system performance, where relatively worse outage performance is achieved when the EH relay is placed in the middle of the two sources.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2007.05a
• /
• pp.870-872
• /
• 2007

Sensor networks have been widely applied for data collection. Due to the energy limitation of the sensor nodes and the most energy consuming data transmission, we should allocate as much work as possible to the sensors, such as data compression and aggregation, to reduce data transmission and save energy. Querying extreme values is a general query type in wireless sensor networks. In this paper, we propose a novel querying method called Two-Level Filter (TLF) for querying extreme values in wireless sensor networks. We first divide the whole sensor network into domains using the Distributed Data Aggregation Model (DDAM). The sensor nodes report their data to the cluster heads using push method. The advantages of two-level filter lie in two aspects. When querying extreme values, the number of pull operations has the lower boundary. And the query results are less affected by the topology changes of the wireless sensor network. Through this method, the sensors preprocess the data to share the burden of the base station and it combines push and pull to be more energy efficient.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.5
• /
• pp.1929-1950
• /
• 2020

Reliable and secure data transmission in the application environment assisted by the wireless sensor network is one of the major challenges. Problem like blind forwarding and data inaccessibility affect the efficiency of overall infrastructure performance. This paper proposes routing protocol for forwarding and error recovery during packet loss. The same is achieved by energy and hops distance-based formulation of the routing mechanism. The reachability of the intermediate node to the source node is the major factor that helps in improving the lifetime of the network. On the other hand, intelligent hop selection increases the reliability over continuous data transmission. The number of hop count is factor of hop weight and available energy of the node. The comparison over the previous state of the art using QualNet-7.4 network simulator shows the effectiveness of proposed work in terms of overall energy conservation of network and reliable data delivery. The simulation results also show the elimination of blind forwarding and data inaccessibility.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.11 no.3
• /
• pp.31-39
• /
• 2012

In this paper, we propose an energy-aware source routing protocol for maximizing a network lifetime in mobile ad hoc network environments. The proposed routing protocol is based on the source routing and chooses a path that maximize the path lifetime, by considering both transmit/receive power consumption and residual battery power in the mobile nodes from the perspective of source-destination end-to-end. This paper proposes a new routing cost and designs a new routing protocol for minimizing the control packet overhead occurred during the route discovery. Simulation results show that the proposed scheme has similar performances to the conventional routing schemes in terms of the number of transmission hops, transmission rate and total energy consumption, but achieves the performance improvement of 20 percent with respect to the lifetime.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.45 no.3
• /
• pp.80-85
• /
• 2008

Capsule endoscopes generally use primary cells as a power source due to its limited space. However, the primary cells have several limitations such as high cost, limited power and no reuse. To solve these problems, a new wireless energy transmission method is proposed. The proposed approach uses air-gap transformer concepts and LC resonance to transmit energy from transmitter(primary side) to capsule endoscopes(secondary side). The ferrite core with 3-axis winding is used to increase energy transfer efficiency regardless of direction and location. The experimental results show that the proposed method stably supplies 30mW power to secondary circuit.

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