469 research outputs found
Recent Advances in Joint Wireless Energy and Information Transfer
In this paper, we provide an overview of the recent advances in
microwave-enabled wireless energy transfer (WET) technologies and their
applications in wireless communications. Specifically, we divide our
discussions into three parts. First, we introduce the state-of-the-art WET
technologies and the signal processing techniques to maximize the energy
transfer efficiency. Then, we discuss an interesting paradigm named
simultaneous wireless information and power transfer (SWIPT), where energy and
information are jointly transmitted using the same radio waveform. At last, we
review the recent progress in wireless powered communication networks (WPCN),
where wireless devices communicate using the power harvested by means of WET.
Extensions and future directions are also discussed in each of these areas.Comment: Conference submission accepted by ITW 201
Optimized Training Design for Wireless Energy Transfer
Radio-frequency (RF) enabled wireless energy transfer (WET), as a promising
solution to provide cost-effective and reliable power supplies for
energy-constrained wireless networks, has drawn growing interests recently. To
overcome the significant propagation loss over distance, employing
multi-antennas at the energy transmitter (ET) to more efficiently direct
wireless energy to desired energy receivers (ERs), termed \emph{energy
beamforming}, is an essential technique for enabling WET. However, the
achievable gain of energy beamforming crucially depends on the available
channel state information (CSI) at the ET, which needs to be acquired
practically. In this paper, we study the design of an efficient channel
acquisition method for a point-to-point multiple-input multiple-output (MIMO)
WET system by exploiting the channel reciprocity, i.e., the ET estimates the
CSI via dedicated reverse-link training from the ER. Considering the limited
energy availability at the ER, the training strategy should be carefully
designed so that the channel can be estimated with sufficient accuracy, and yet
without consuming excessive energy at the ER. To this end, we propose to
maximize the \emph{net} harvested energy at the ER, which is the average
harvested energy offset by that used for channel training. An optimization
problem is formulated for the training design over MIMO Rician fading channels,
including the subset of ER antennas to be trained, as well as the training time
and power allocated. Closed-form solutions are obtained for some special
scenarios, based on which useful insights are drawn on when training should be
employed to improve the net transferred energy in MIMO WET systems.Comment: 30 pages, 9 figures, to appear in IEEE Trans. on Communication
Optimization of Energy Harvesting MISO Communication System with Feedback
Optimization of a point-to-point (p2p) multipleinput single-output (MISO)
communication system is considered when both the transmitter (TX) and the
receiver (RX) have energy harvesting (EH) capabilities. The RX is interested in
feeding back the channel state information (CSI) to the TX to help improve the
transmission rate. The objective is to maximize the throughput by a deadline,
subject to the EH constraints at the TX and the RX. The throughput metric
considered is an upper bound on the ergodic rate of the MISO channel with
beamforming and limited feedback. Feedback bit allocation and transmission
policies that maximize the upper bound on the ergodic rate are obtained. Tools
from majorization theory are used to simplify the formulated optimization
problems. Optimal policies obtained for the modified problem outperform the
naive scheme in which no intelligent management of energy is performed.Comment: 11 page
Physical Layer Service Integration in 5G: Potentials and Challenges
High transmission rate and secure communication have been identified as the
key targets that need to be effectively addressed by fifth generation (5G)
wireless systems. In this context, the concept of physical-layer security
becomes attractive, as it can establish perfect security using only the
characteristics of wireless medium. Nonetheless, to further increase the
spectral efficiency, an emerging concept, termed physical-layer service
integration (PHY-SI), has been recognized as an effective means. Its basic idea
is to combine multiple coexisting services, i.e., multicast/broadcast service
and confidential service, into one integral service for one-time transmission
at the transmitter side. This article first provides a tutorial on typical
PHY-SI models. Furthermore, we propose some state-of-the-art solutions to
improve the overall performance of PHY-SI in certain important communication
scenarios. In particular, we highlight the extension of several concepts
borrowed from conventional single-service communications, such as artificial
noise (AN), eigenmode transmission etc., to the scenario of PHY-SI. These
techniques are shown to be effective in the design of reliable and robust
PHY-SI schemes. Finally, several potential research directions are identified
for future work.Comment: 12 pages, 7 figure
Dynamic Resource Allocation for Multiple-Antenna Wireless Power Transfer
We consider a point-to-point multiple-input-single-output (MISO) system where
a receiver harvests energy from a wireless power transmitter to power itself
for various applications. The transmitter performs energy beamforming by using
an instantaneous channel state information (CSI). The CSI is estimated at the
receiver by training via a preamble, and fed back to the transmitter. The
channel estimate is more accurate when longer preamble is used, but less time
is left for wireless power transfer before the channel changes. To maximize the
harvested energy, in this paper, we address the key challenge of balancing the
time resource used for channel estimation and wireless power transfer (WPT),
and also investigate the allocation of energy resource used for wireless power
transfer. First, we consider the general scenario where the preamble length is
allowed to vary dynamically. Taking into account the effects of imperfect CSI,
the optimal preamble length is obtained online by solving a dynamic programming
(DP) problem. The solution is shown to be a threshold-type policy that depends
only on the channel estimate power. Next, we consider the scenario in which the
preamble length is fixed. The optimal preamble length is optimized offline.
Furthermore, we derive the optimal power allocation schemes for both scenarios.
For the scenario of dynamic-length preamble, the power is allocated according
to both the optimal preamble length and the channel estimate power; while for
the scenario of fixed-length preamble, the power is allocated according to only
the channel estimate power. The analysis results are validated by numerical
simulations. Encouragingly, with optimal power allocation, the harvested energy
by using optimized fixed-length preamble is almost the same as the harvested
energy by employing dynamic-length preamble, hence allowing a low-complexity
WPT system to be implemented in practice.Comment: 30 pages, 6 figures, Submitted to the IEEE Transactions on Signal
Processin
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