1,242 research outputs found
Performance Analysis and Design of Maximum Ratio Combining in Channel-Aware MIMO Decision Fusion
In this paper we present a theoretical performance analysis of the maximum
ratio combining (MRC) rule for channel-aware decision fusion over
multiple-input multiple-output (MIMO) channels for (conditionally) dependent
and independent local decisions. The system probabilities of false alarm and
detection conditioned on the channel realization are derived in closed form and
an approximated threshold choice is given. Furthermore, the channel-averaged
(CA) performances are evaluated in terms of the CA system probabilities of
false alarm and detection and the area under the receiver operating
characteristic (ROC) through the closed form of the conditional moment
generating function (MGF) of the MRC statistic, along with Gauss-Chebyshev (GC)
quadrature rules. Furthermore, we derive the deflection coefficients in closed
form, which are used for sensor threshold design. Finally, all the results are
confirmed through Monte Carlo simulations.Comment: To appear in IEEE Transactions on Wireless Communication
Rician MIMO Channel- and Jamming-Aware Decision Fusion
In this manuscript we study channel-aware decision fusion (DF) in a wireless
sensor network (WSN) where: (i) the sensors transmit their decisions
simultaneously for spectral efficiency purposes and the DF center (DFC) is
equipped with multiple antennas; (ii) each sensor-DFC channel is described via
a Rician model. As opposed to the existing literature, in order to account for
stringent energy constraints in the WSN, only statistical channel information
is assumed for the non-line-of sight (scattered) fading terms. For such a
scenario, sub-optimal fusion rules are developed in order to deal with the
exponential complexity of the likelihood ratio test (LRT) and impractical
(complete) system knowledge. Furthermore, the considered model is extended to
the case of (partially unknown) jamming-originated interference. Then the
obtained fusion rules are modified with the use of composite hypothesis testing
framework and generalized LRT. Coincidence and statistical equivalence among
them are also investigated under some relevant simplified scenarios. Numerical
results compare the proposed rules and highlight their jammingsuppression
capability.Comment: Accepted in IEEE Transactions on Signal Processing 201
Decision Fusion with Unknown Sensor Detection Probability
In this correspondence we study the problem of channel-aware decision fusion
when the sensor detection probability is not known at the decision fusion
center. Several alternatives proposed in the literature are compared and new
fusion rules (namely 'ideal sensors' and 'locally-optimum detection') are
proposed, showing attractive performance and linear complexity. Simulations are
provided to compare the performance of the aforementioned rules.Comment: To appear in IEEE Signal Processing Letter
Distributed Detection over Fading MACs with Multiple Antennas at the Fusion Center
A distributed detection problem over fading Gaussian multiple-access channels
is considered. Sensors observe a phenomenon and transmit their observations to
a fusion center using the amplify and forward scheme. The fusion center has
multiple antennas with different channel models considered between the sensors
and the fusion center, and different cases of channel state information are
assumed at the sensors. The performance is evaluated in terms of the error
exponent for each of these cases, where the effect of multiple antennas at the
fusion center is studied. It is shown that for zero-mean channels between the
sensors and the fusion center when there is no channel information at the
sensors, arbitrarily large gains in the error exponent can be obtained with
sufficient increase in the number of antennas at the fusion center. In stark
contrast, when there is channel information at the sensors, the gain in error
exponent due to having multiple antennas at the fusion center is shown to be no
more than a factor of (8/pi) for Rayleigh fading channels between the sensors
and the fusion center, independent of the number of antennas at the fusion
center, or correlation among noise samples across sensors. Scaling laws for
such gains are also provided when both sensors and antennas are increased
simultaneously. Simple practical schemes and a numerical method using
semidefinite relaxation techniques are presented that utilize the limited
possible gains available. Simulations are used to establish the accuracy of the
results.Comment: 21 pages, 9 figures, submitted to the IEEE Transactions on Signal
Processin
Communication Theoretic Data Analytics
Widespread use of the Internet and social networks invokes the generation of
big data, which is proving to be useful in a number of applications. To deal
with explosively growing amounts of data, data analytics has emerged as a
critical technology related to computing, signal processing, and information
networking. In this paper, a formalism is considered in which data is modeled
as a generalized social network and communication theory and information theory
are thereby extended to data analytics. First, the creation of an equalizer to
optimize information transfer between two data variables is considered, and
financial data is used to demonstrate the advantages. Then, an information
coupling approach based on information geometry is applied for dimensionality
reduction, with a pattern recognition example to illustrate the effectiveness.
These initial trials suggest the potential of communication theoretic data
analytics for a wide range of applications.Comment: Published in IEEE Journal on Selected Areas in Communications, Jan.
201
Interference Alignment for Cognitive Radio Communications and Networks: A Survey
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe
Energy Harvesting Wireless Communications: A Review of Recent Advances
This article summarizes recent contributions in the broad area of energy
harvesting wireless communications. In particular, we provide the current state
of the art for wireless networks composed of energy harvesting nodes, starting
from the information-theoretic performance limits to transmission scheduling
policies and resource allocation, medium access and networking issues. The
emerging related area of energy transfer for self-sustaining energy harvesting
wireless networks is considered in detail covering both energy cooperation
aspects and simultaneous energy and information transfer. Various potential
models with energy harvesting nodes at different network scales are reviewed as
well as models for energy consumption at the nodes.Comment: To appear in the IEEE Journal of Selected Areas in Communications
(Special Issue: Wireless Communications Powered by Energy Harvesting and
Wireless Energy Transfer
- …