1,473 research outputs found
Spatial Throughput Maximization of Wireless Powered Communication Networks
Wireless charging is a promising way to power wireless nodes' transmissions.
This paper considers new dual-function access points (APs) which are able to
support the energy/information transmission to/from wireless nodes. We focus on
a large-scale wireless powered communication network (WPCN), and use stochastic
geometry to analyze the wireless nodes' performance tradeoff between energy
harvesting and information transmission. We study two cases with battery-free
and battery-deployed wireless nodes. For both cases, we consider a
harvest-then-transmit protocol by partitioning each time frame into a downlink
(DL) phase for energy transfer, and an uplink (UL) phase for information
transfer. By jointly optimizing frame partition between the two phases and the
wireless nodes' transmit power, we maximize the wireless nodes' spatial
throughput subject to a successful information transmission probability
constraint. For the battery-free case, we show that the wireless nodes prefer
to choose small transmit power to obtain large transmission opportunity. For
the battery-deployed case, we first study an ideal infinite-capacity battery
scenario for wireless nodes, and show that the optimal charging design is not
unique, due to the sufficient energy stored in the battery. We then extend to
the practical finite-capacity battery scenario. Although the exact performance
is difficult to be obtained analytically, it is shown to be upper and lower
bounded by those in the infinite-capacity battery scenario and the battery-free
case, respectively. Finally, we provide numerical results to corroborate our
study.Comment: 15 double-column pages, 8 figures, to appear in IEEE JSAC in February
2015, special issue on wireless communications powered by energy harvesting
and wireless energy transfe
Wireless Power Transfer and Data Collection in Wireless Sensor Networks
In a rechargeable wireless sensor network, the data packets are generated by
sensor nodes at a specific data rate, and transmitted to a base station.
Moreover, the base station transfers power to the nodes by using Wireless Power
Transfer (WPT) to extend their battery life. However, inadequately scheduling
WPT and data collection causes some of the nodes to drain their battery and
have their data buffer overflow, while the other nodes waste their harvested
energy, which is more than they need to transmit their packets. In this paper,
we investigate a novel optimal scheduling strategy, called EHMDP, aiming to
minimize data packet loss from a network of sensor nodes in terms of the nodes'
energy consumption and data queue state information. The scheduling problem is
first formulated by a centralized MDP model, assuming that the complete states
of each node are well known by the base station. This presents the upper bound
of the data that can be collected in a rechargeable wireless sensor network.
Next, we relax the assumption of the availability of full state information so
that the data transmission and WPT can be semi-decentralized. The simulation
results show that, in terms of network throughput and packet loss rate, the
proposed algorithm significantly improves the network performance.Comment: 30 pages, 8 figures, accepted to IEEE Transactions on Vehicular
Technolog
Resource Allocation in Wireless Networks with RF Energy Harvesting and Transfer
Radio frequency (RF) energy harvesting and transfer techniques have recently
become alternative methods to power the next generation of wireless networks.
As this emerging technology enables proactive replenishment of wireless
devices, it is advantageous in supporting applications with quality-of-service
(QoS) requirement. This article focuses on the resource allocation issues in
wireless networks with RF energy harvesting capability, referred to as RF
energy harvesting networks (RF-EHNs). First, we present an overview of the
RF-EHNs, followed by a review of a variety of issues regarding resource
allocation. Then, we present a case study of designing in the receiver
operation policy, which is of paramount importance in the RF-EHNs. We focus on
QoS support and service differentiation, which have not been addressed by
previous literatures. Furthermore, we outline some open research directions.Comment: To appear in IEEE Networ
Energy Harvesting Wireless Sensor Networks: Delay Analysis Considering Energy Costs of Sensing and Transmission
Energy harvesting (EH) provides a means of greatly enhancing the lifetime of
wireless sensor nodes. However, the randomness inherent in the EH process may
cause significant delay for performing sensing operation and transmitting the
sensed information to the sink. Unlike most existing studies on the delay
performance of EH sensor networks, where only the energy consumption of
transmission is considered, we consider the energy costs of both sensing and
transmission. Specifically, we consider an EH sensor that monitors some status
environmental property and adopts a harvest-then-use protocol to perform
sensing and transmission. To comprehensively study the delay performance, we
consider two complementary metrics and analytically derive their statistics:
(i) update age - measuring the time taken from when information is obtained by
the sensor to when the sensed information is successfully transmitted to the
sink, i.e., how timely the updated information at the sink is, and (ii) update
cycle - measuring the time duration between two consecutive successful
transmissions, i.e., how frequently the information at the sink is updated. Our
results show that the consideration of sensing energy cost leads to an
important tradeoff between the two metrics: more frequent updates result in
less timely information available at the sink.Comment: submitted for possible journal publicatio
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