28,258 research outputs found
Limited-Feedback-Based Channel-Aware Power Allocation for Linear Distributed Estimation
This paper investigates the problem of distributed best linear unbiased
estimation (BLUE) of a random parameter at the fusion center (FC) of a wireless
sensor network (WSN). In particular, the application of limited-feedback
strategies for the optimal power allocation in distributed estimation is
studied. In order to find the BLUE estimator of the unknown parameter, the FC
combines spatially distributed, linearly processed, noisy observations of local
sensors received through orthogonal channels corrupted by fading and additive
Gaussian noise. Most optimal power-allocation schemes proposed in the
literature require the feedback of the exact instantaneous channel state
information from the FC to local sensors. This paper proposes a
limited-feedback strategy in which the FC designs an optimal codebook
containing the optimal power-allocation vectors, in an iterative offline
process, based on the generalized Lloyd algorithm with modified distortion
functions. Upon observing a realization of the channel vector, the FC finds the
closest codeword to its corresponding optimal power-allocation vector and
broadcasts the index of the codeword. Each sensor will then transmit its analog
observations using its optimal quantized amplification gain. This approach
eliminates the requirement for infinite-rate digital feedback links and is
scalable, especially in large WSNs.Comment: 5 Pages, 3 Figures, 1 Algorithm, Forty Seventh Annual Asilomar
Conference on Signals, Systems, and Computers (ASILOMAR 2013
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
Power Allocation for Distributed BLUE Estimation with Full and Limited Feedback of CSI
This paper investigates the problem of adaptive power allocation for
distributed best linear unbiased estimation (BLUE) of a random parameter at the
fusion center (FC) of a wireless sensor network (WSN). An optimal
power-allocation scheme is proposed that minimizes the -norm of the vector
of local transmit powers, given a maximum variance for the BLUE estimator. This
scheme results in the increased lifetime of the WSN compared to similar
approaches that are based on the minimization of the sum of the local transmit
powers. The limitation of the proposed optimal power-allocation scheme is that
it requires the feedback of the instantaneous channel state information (CSI)
from the FC to local sensors, which is not practical in most applications of
large-scale WSNs. In this paper, a limited-feedback strategy is proposed that
eliminates this requirement by designing an optimal codebook for the FC using
the generalized Lloyd algorithm with modified distortion metrics. Each sensor
amplifies its analog noisy observation using a quantized version of its optimal
amplification gain, which is received by the FC and used to estimate the
unknown parameter.Comment: 6 pages, 3 figures, to appear at the IEEE Military Communications
Conference (MILCOM) 201
Receive Combining vs. Multi-Stream Multiplexing in Downlink Systems with Multi-Antenna Users
In downlink multi-antenna systems with many users, the multiplexing gain is
strictly limited by the number of transmit antennas and the use of these
antennas. Assuming that the total number of receive antennas at the
multi-antenna users is much larger than , the maximal multiplexing gain can
be achieved with many different transmission/reception strategies. For example,
the excess number of receive antennas can be utilized to schedule users with
effective channels that are near-orthogonal, for multi-stream multiplexing to
users with well-conditioned channels, and/or to enable interference-aware
receive combining. In this paper, we try to answer the question if the data
streams should be divided among few users (many streams per user) or many users
(few streams per user, enabling receive combining). Analytic results are
derived to show how user selection, spatial correlation, heterogeneous user
conditions, and imperfect channel acquisition (quantization or estimation
errors) affect the performance when sending the maximal number of streams or
one stream per scheduled user---the two extremes in data stream allocation.
While contradicting observations on this topic have been reported in prior
works, we show that selecting many users and allocating one stream per user
(i.e., exploiting receive combining) is the best candidate under realistic
conditions. This is explained by the provably stronger resilience towards
spatial correlation and the larger benefit from multi-user diversity. This
fundamental result has positive implications for the design of downlink systems
as it reduces the hardware requirements at the user devices and simplifies the
throughput optimization.Comment: Published in IEEE Transactions on Signal Processing, 16 pages, 11
figures. The results can be reproduced using the following Matlab code:
https://github.com/emilbjornson/one-or-multiple-stream
Estimation in Phase-Shift and Forward Wireless Sensor Networks
We consider a network of single-antenna sensors that observe an unknown
deterministic parameter. Each sensor applies a phase shift to the observation
and the sensors simultaneously transmit the result to a multi-antenna fusion
center (FC). Based on its knowledge of the wireless channel to the sensors, the
FC calculates values for the phase factors that minimize the variance of the
parameter estimate, and feeds this information back to the sensors. The use of
a phase-shift-only transmission scheme provides a simplified analog
implementation at the sensor, and also leads to a simpler algorithm design and
performance analysis. We propose two algorithms for this problem, a numerical
solution based on a relaxed semidefinite programming problem, and a closed-form
solution based on the analytic constant modulus algorithm. Both approaches are
shown to provide performance close to the theoretical bound. We derive
asymptotic performance analyses for cases involving large numbers of sensors or
large numbers of FC antennas, and we also study the impact of phase errors at
the sensor transmitters. Finally, we consider the sensor selection problem, in
which only a subset of the sensors is chosen to send their observations to the
FC.Comment: 28 pages, 5 figures, accepted by IEEE Transactions on Signal
Processing, Apr. 201
Wireless Power Charging Control in Multiuser Broadband Networks
Recent advances in wireless power transfer (WPT) technology provide a
cost-effective solution to charge wireless devices remotely without disruption
to the use. In this paper, we propose an efficient wireless charging control
method for exploiting the frequency diversity in multiuser broadband wireless
networks, to reduce energy outage and keep the system operating in an efficient
and sustainable state. In particular, we first analyze the impact of charging
control method to the operating lifetime of a WPT-enabled broadband system.
Based on the analysis, we then propose a multi-criteria charging control policy
that optimizes the transmit power allocation over frequency by jointly
considering the channel state information (CSI) and the battery state
information (BSI) of wireless devices. For practical implementation, the
proposed scheme is realized by a novel limited CSI estimation mechanism
embedded with partial BSI, which significantly reduces the energy cost of CSI
and BSI feedback. Simulation results show that the proposed method could
significantly increase the network lifetime under stringent transmit power
constraint. Reciprocally, it also consumes lower transmit power to achieve
near-perpetual network operation than other single-criterion based charging
control methods.Comment: This paper had been accepted by IEEE ICC 2015, Workshop on Green
Communications and Networks with Energy Harvesting, Smart Grids, and
Renewable Energie
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