11,304 research outputs found
Signal and System Design for Wireless Power Transfer : Prototype, Experiment and Validation
A new line of research on communications and signals design for Wireless
Power Transfer (WPT) has recently emerged in the communication literature.
Promising signal strategies to maximize the power transfer efficiency of WPT
rely on (energy) beamforming, waveform, modulation and transmit diversity, and
a combination thereof. To a great extent, the study of those strategies has so
far been limited to theoretical performance analysis. In this paper, we study
the real over-the-air performance of all the aforementioned signal strategies
for WPT. To that end, we have designed, prototyped and experimented an
innovative radiative WPT architecture based on Software-Defined Radio (SDR)
that can operate in open-loop and closed-loop (with channel acquisition at the
transmitter) modes. The prototype consists of three important blocks, namely
the channel estimator, the signal generator, and the energy harvester. The
experiments have been conducted in a variety of deployments, including
frequency flat and frequency selective channels, under static and mobility
conditions. Experiments highlight that a channeladaptive WPT architecture based
on joint beamforming and waveform design offers significant performance
improvements in harvested DC power over conventional
single-antenna/multiantenna continuous wave systems. The experimental results
fully validate the observations predicted from the theoretical signal designs
and confirm the crucial and beneficial role played by the energy harvester
nonlinearity.Comment: Accepted to IEEE Transactions on Wireless Communication
Joint Wireless Information and Energy Transfer with Reduced Feedback in MIMO Interference Channels
To determine the transmission strategy for joint wireless information and
energy transfer (JWIET) in the MIMO interference channel (IFC), the information
access point (IAP) and energy access point (EAP) require the channel state
information (CSI) of their associated links to both the information-decoding
(ID) mobile stations (MSs) and energy-harvesting (EH) MSs (so-called local
CSI). In this paper, to reduce th e feedback overhead of MSs for the JWIET in
two-user MIMO IFC, we propose a Geodesic energy beamforming scheme that
requires partial CSI at the EAP. Furthermore, in the two-user MIMO IFC, it is
proved that the Geodesic energy beamforming is the optimal strategy. By adding
a rank-one constraint on the transmit signal covariance of IAP, we can further
reduce the feedback overhead to IAP by exploiting Geodesic information
beamforming. Under the rank-one constraint of IAP's transmit signal, we prove
that Geodesic information/energy beamforming approach is the optimal strategy
for JWIET in the two-user MIMO IFC. We also discuss the extension of the
proposed rank-one Geodesic information/energy beamforming strategies to general
K-user MIMO IFC. Finally, by analyzing the achievable rate-energy performance
statistically under imperfect partial CSIT, we propose an adaptive bit
allocation strategy for both EH MS and ID MS.Comment: accepted to IEEE Journal of Selected Areas in Communications (IEEE
JSAC), Special Issue on Wireless Communications Powered by Energy Harvesting
and Wireless Energy Transfe
The Impact of Channel Feedback on Opportunistic Relay Selection for Hybrid-ARQ in Wireless Networks
This paper presents a decentralized relay selection protocol for a dense
wireless network and describes channel feedback strategies that improve its
performance. The proposed selection protocol supports hybrid
automatic-repeat-request transmission where relays forward parity information
to the destination in the event of a decoding error. Channel feedback is
employed for refining the relay selection process and for selecting an
appropriate transmission mode in a proposed adaptive modulation transmission
framework. An approximation of the throughput of the proposed adaptive
modulation strategy is presented, and the dependence of the throughput on
system parameters such as the relay contention probability and the adaptive
modulation switching point is illustrated via maximization of this
approximation. Simulations show that the throughput of the proposed selection
strategy is comparable to that yielded by a centralized selection approach that
relies on geographic information.Comment: 30 pages, 9 figures, submitted to the IEEE Transactions on Vehicular
Technology, revised March 200
A Game-Theoretic Approach to Energy-Efficient Modulation in CDMA Networks with Delay QoS Constraints
A game-theoretic framework is used to study the effect of constellation size
on the energy efficiency of wireless networks for M-QAM modulation. A
non-cooperative game is proposed in which each user seeks to choose its
transmit power (and possibly transmit symbol rate) as well as the constellation
size in order to maximize its own utility while satisfying its delay
quality-of-service (QoS) constraint. The utility function used here measures
the number of reliable bits transmitted per joule of energy consumed, and is
particularly suitable for energy-constrained networks. The best-response
strategies and Nash equilibrium solution for the proposed game are derived. It
is shown that in order to maximize its utility (in bits per joule), a user must
choose the lowest constellation size that can accommodate the user's delay
constraint. This strategy is different from one that would maximize spectral
efficiency. Using this framework, the tradeoffs among energy efficiency, delay,
throughput and constellation size are also studied and quantified. In addition,
the effect of trellis-coded modulation on energy efficiency is discussed.Comment: To appear in the IEEE Journal on Selected Areas in Communications
(JSAC): Special Issue on Non-Cooperative Behavior in Networking, August 200
Distributed Game Theoretic Optimization and Management of Multichannel ALOHA Networks
The problem of distributed rate maximization in multi-channel ALOHA networks
is considered. First, we study the problem of constrained distributed rate
maximization, where user rates are subject to total transmission probability
constraints. We propose a best-response algorithm, where each user updates its
strategy to increase its rate according to the channel state information and
the current channel utilization. We prove the convergence of the algorithm to a
Nash equilibrium in both homogeneous and heterogeneous networks using the
theory of potential games. The performance of the best-response dynamic is
analyzed and compared to a simple transmission scheme, where users transmit
over the channel with the highest collision-free utility. Then, we consider the
case where users are not restricted by transmission probability constraints.
Distributed rate maximization under uncertainty is considered to achieve both
efficiency and fairness among users. We propose a distributed scheme where
users adjust their transmission probability to maximize their rates according
to the current network state, while maintaining the desired load on the
channels. We show that our approach plays an important role in achieving the
Nash bargaining solution among users. Sequential and parallel algorithms are
proposed to achieve the target solution in a distributed manner. The
efficiencies of the algorithms are demonstrated through both theoretical and
simulation results.Comment: 34 pages, 6 figures, accepted for publication in the IEEE/ACM
Transactions on Networking, part of this work was presented at IEEE CAMSAP
201
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