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Average Power Consumption
The Experts below are selected from a list of 5025 Experts worldwide ranked by ideXlab platform
Victor C. M. Leung – One of the best experts on this subject based on the ideXlab platform.

QueueAware Power Consumption Minimization in TwoTier Heterogeneous Networks
IEEE Transactions on Vehicular Technology, 2018CoAuthors: Fancheng Kong, Victor C. M. LeungAbstract:In this paper, we study the network Average Power Consumption minimization problem in a twotier heterogeneous network by optimally tuning the activation ratio of micro base stations (BSs) under the quality of service (QoS) constraints of the network mean queueing delay and the network signaltointerference ratio (SIR) coverage. With the consideration of dynamic packets arrivals, each BS can either be busy or be idle depending on its queueing status. The network performance is thus critically determined by the traffic intensity of each BS. With the assumption of universal frequency reuse, the Average traffic intensity of each tier is characterized by a set of fixedpoint equations, which can be solved by a proposed iterative method. By using the approximation that BSs of the same tier have the same SIR coverage, the cumulative distribution function of the traffic intensity of each tier is further obtained. On that basis, the network Average Power Consumption per area, the network mean queueing delay, and the network SIR coverage are characterized. Numerical results demonstrate that if the idle Power coefficient is below a certain threshold, then the optimal activation ratio equals the one to minimize the network Average Power Consumption per area; otherwise, the optimal activation ratio can be obtained according to the QoS constraints. It is further shown that universal frequency reuse outperforms spectrum partitioning in terms of both the network Average Power Consumption and the network SIR coverage in the considered scenario.

WCNC – QueueAware Small Cell Activation for Energy Efficiency in TwoTier Heterogeneous Networks
2017 IEEE Wireless Communications and Networking Conference (WCNC), 2017CoAuthors: Fancheng Kong, Victor C. M. LeungAbstract:In heterogeneous networks (HetNets), the network energy efficiency is critically determined by the base station (BS) deployment density. In this paper, we consider a BS density optimization problem by turning on only a fraction of micro BSs according to an activation ratio to minimize the network Average Power Consumption per area in a 2 tier HetNet. In contrast to previous studies where a BS is assumed to be transmitting packets all the time, such that the network Power Consumption monotonically increases as the BS density increases, we assume that each BS can be busy or idle depending on the dynamic packet arrivals. The network Power Consumption is thus closely related to the Average traffic intensity of each tier. With the assumption of universal spectrum reuse, the Average traffic intensity of each tier is found to be uniquely determined by a set of fixedpoint equations, based on which the network Average Power Consumption per area is characterized. Simulation results demonstrate that the network Average Power Consumption per area can be minimized by properly tuning the activation ratio. It is further revealed that the optimal activation ratio increases as the mean packet arrival rate of each user increases.
Fancheng Kong – One of the best experts on this subject based on the ideXlab platform.

QueueAware Power Consumption Minimization in TwoTier Heterogeneous Networks
IEEE Transactions on Vehicular Technology, 2018CoAuthors: Fancheng Kong, Victor C. M. LeungAbstract:In this paper, we study the network Average Power Consumption minimization problem in a twotier heterogeneous network by optimally tuning the activation ratio of micro base stations (BSs) under the quality of service (QoS) constraints of the network mean queueing delay and the network signaltointerference ratio (SIR) coverage. With the consideration of dynamic packets arrivals, each BS can either be busy or be idle depending on its queueing status. The network performance is thus critically determined by the traffic intensity of each BS. With the assumption of universal frequency reuse, the Average traffic intensity of each tier is characterized by a set of fixedpoint equations, which can be solved by a proposed iterative method. By using the approximation that BSs of the same tier have the same SIR coverage, the cumulative distribution function of the traffic intensity of each tier is further obtained. On that basis, the network Average Power Consumption per area, the network mean queueing delay, and the network SIR coverage are characterized. Numerical results demonstrate that if the idle Power coefficient is below a certain threshold, then the optimal activation ratio equals the one to minimize the network Average Power Consumption per area; otherwise, the optimal activation ratio can be obtained according to the QoS constraints. It is further shown that universal frequency reuse outperforms spectrum partitioning in terms of both the network Average Power Consumption and the network SIR coverage in the considered scenario.

WCNC – QueueAware Small Cell Activation for Energy Efficiency in TwoTier Heterogeneous Networks
2017 IEEE Wireless Communications and Networking Conference (WCNC), 2017CoAuthors: Fancheng Kong, Victor C. M. LeungAbstract:In heterogeneous networks (HetNets), the network energy efficiency is critically determined by the base station (BS) deployment density. In this paper, we consider a BS density optimization problem by turning on only a fraction of micro BSs according to an activation ratio to minimize the network Average Power Consumption per area in a 2 tier HetNet. In contrast to previous studies where a BS is assumed to be transmitting packets all the time, such that the network Power Consumption monotonically increases as the BS density increases, we assume that each BS can be busy or idle depending on the dynamic packet arrivals. The network Power Consumption is thus closely related to the Average traffic intensity of each tier. With the assumption of universal spectrum reuse, the Average traffic intensity of each tier is found to be uniquely determined by a set of fixedpoint equations, based on which the network Average Power Consumption per area is characterized. Simulation results demonstrate that the network Average Power Consumption per area can be minimized by properly tuning the activation ratio. It is further revealed that the optimal activation ratio increases as the mean packet arrival rate of each user increases.
Fernando Silveira – One of the best experts on this subject based on the ideXlab platform.

Average Power Consumption Breakdown of Wireless Sensor Network Nodes Using IPv6 over LLNs
2015 International Conference on Distributed Computing in Sensor Systems, 2015CoAuthors: Javier Schandy, Leonardo Steinfeld, Fernando SilveiraAbstract:This paper presents a simple but still Powerful approach for the analysis of the Average Power Consumption of a sensor node using the IPv6 over Low Power and Lossy Networks (LLN) stack, which is one of the most widely adopted and promising communication stacks. Power Consumption is broken down according to the node states (i.e. CPU, IRQ, LPM, Tx, Rx) and according to the network protocols (e.g. CoAP, RPL, 6LoWPAN, Contiki MAC), identifying the relative weight of each protocol in the total energy Consumption for several configurations. Results show that the Low Power Listening (LPL) mechanism of the radio duty cycling layer and RPL control messages have the highest impact on the total energy Consumption, while the application’s report rate has a very low impact for periods over 60 seconds.

DCOSS – Average Power Consumption Breakdown of Wireless Sensor Network Nodes Using IPv6 over LLNs
2015 International Conference on Distributed Computing in Sensor Systems, 2015CoAuthors: Javier Schandy, Leonardo Steinfeld, Fernando SilveiraAbstract:This paper presents a simple but still Powerful approach for the analysis of the Average Power Consumption of a sensor node using the IPv6 over Low Power and Lossy Networks (LLN) stack, which is one of the most widely adopted and promising communication stacks. Power Consumption is broken down according to the node states (i.e. CPU, IRQ, LPM, Tx, Rx) and according to the network protocols (e.g. CoAP, RPL, 6LoWPAN, Contiki MAC), identifying the relative weight of each protocol in the total energy Consumption for several configurations. Results show that the Low Power Listening (LPL) mechanism of the radio duty cycling layer and RPL control messages have the highest impact on the total energy Consumption, while the application’s report rate has a very low impact for periods over 60 seconds.