4,593 research outputs found
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
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
Energy-Efficient Optimization for Wireless Information and Power Transfer in Large-Scale MIMO Systems Employing Energy Beamforming
In this letter, we consider a large-scale multiple-input multiple-output
(MIMO) system where the receiver should harvest energy from the transmitter by
wireless power transfer to support its wireless information transmission. The
energy beamforming in the large-scale MIMO system is utilized to address the
challenging problem of long-distance wireless power transfer. Furthermore,
considering the limitation of the power in such a system, this letter focuses
on the maximization of the energy efficiency of information transmission (bit
per Joule) while satisfying the quality-of-service (QoS) requirement, i.e.
delay constraint, by jointly optimizing transfer duration and transmit power.
By solving the optimization problem, we derive an energy-efficient resource
allocation scheme. Numerical results validate the effectiveness of the proposed
scheme.Comment: 4 pages, 3 figures. IEEE Wireless Communications Letters 201
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