233 research outputs found
Detector Randomization and Stochastic Signaling for Minimum Probability of Error Receivers
Cataloged from PDF version of article.Optimal receiver design is studied for a communications
system in which both detector randomization and stochastic
signaling can be performed. First, it is proven that stochastic signaling
without detector randomization cannot achieve a smaller
average probability of error than detector randomization with
deterministic signaling for the same average power constraint
and noise statistics. Then, it is shown that the optimal receiver
design results in a randomization between at most two maximum
a-posteriori probability (MAP) detectors corresponding to two
deterministic signal vectors. Numerical examples are provided
to explain the results
Optimal Randomization of Signal Constellations on Downlink of a Multiuser DS-CDMA System
Cataloged from PDF version of article.In this study, the jointly optimal power control with signal constellation randomization is proposed for the downlink of a multiuser communications system. Unlike a conventional system in which a fixed signal constellation is employed for all the bits of a user (for given channel conditions and noise power), power control with signal constellation randomization involves randomization/time- sharing among different signal constellations for each user. A formulation is obtained for the problem of optimal power control with signal constellation randomization, and it is shown that the optimal solution can be represented by a randomization among (K+1) or fewer distinct signal constellations for each user, where K denotes the number of users. In addition to the original nonconvex formulation, an approximate solution based on convex relaxation is derived. Then, detailed performance analysis is presented when the receivers employ symmetric signaling and sign detectors. Specifically, the maximum asymptotical improvement ratio is shown to be equal to the number of users, and the conditions under which the maximum and minimum asymptotical improvement ratios are achieved are derived. Numerical examples are presented to investigate the theoretical results, and to illustrate performance improvements achieved via the proposed approach. © 2002-2012 IEEE
Optimal stochastic signaling for power-constrained binary communications systems
Cataloged from PDF version of article.Optimal stochastic signaling is studied under second
and fourth moment constraints for the detection of scalar-valued
binary signals in additive noise channels. Sufficient conditions
are obtained to specify when the use of stochastic signals
instead of deterministic ones can or cannot improve the error
performance of a given binary communications system. Also,
statistical characterization of optimal signals is presented, and it
is shown that an optimal stochastic signal can be represented by a
randomization of at most three different signal levels. In addition,
the power constraints achieved by optimal stochastic signals are
specified under various conditions. Furthermore, two approaches
for solving the optimal stochastic signaling problem are proposed;
one based on particle swarm optimization (PSO) and the other
based on convex relaxation of the original optimization problem.
Finally, simulations are performed to investigate the theoretical
results, and extensions of the results to -ary communications
systems and to other criteria than the average probability of
error are discussed
Signal and detector randomization for multiuser and multichannel communication systems
Ankara : The Department of Electrical and Electronics Engineering and the Graduate School of Engineering and Science of Bilkent Univ., 2013.Thesis (Ph. D.) -- Bilkent University, 2013.Includes bibliographical references leaves 111-118.Randomization can be considered as a possible approach to enhance error performance
of communication systems subject to average power constraints. In
the first part of this dissertation, we consider downlink of a multiuser communications
system subject to an average power constraint, where randomization
is employed at the transmitter and receiver sides by modeling signal levels as
random variables (stochastic signals) and employing different sets of detectors
via time-sharing (detector randomization), respectively. In the second part, we
consider single-user systems, where we assume that there exist multiple channels
between the transmitter and receiver with arbitrary noise distributions over each
of them and only one of the channels can be employed for transmission at any
given time. In this case, randomization is performed by choosing the channel
in use according to some probability mass function and employing stochastic
signaling at the transmitter.
First, the jointly optimal power control with signal constellation randomization
is proposed for the downlink of a multiuser communications system. Unlike
a conventional system in which a fixed signal constellation is employed for all the bits of a user (for given channel conditions and noise power), power control with
signal constellation randomization involves randomization/time-sharing among
different signal constellations for each user. A formulation is obtained for the
problem of optimal power control with signal constellation randomization, and
it is shown that the optimal solution can be represented by a randomization of
(K + 1) or fewer distinct signal constellations for each user, where K denotes the
number of users. In addition to the original nonconvex formulation, an approximate
solution based on convex relaxation is derived. Then, detailed performance
analysis is presented when the receivers employ symmetric signaling and sign detectors.
Specifically, the maximum asymptotical improvement ratio is shown to
be equal to the number of users, and the conditions under which the maximum
and minimum asymptotical improvement ratios are achieved are derived. In
the literature, it is known that employing different detectors with corresponding
deterministic signals via time-sharing may enhance error performance of communications
systems subject to average power constraints. Motivated by this
result, as a second approach, we study optimal detector randomization for the
downlink of a multiuser communications system. A formulation is provided to
obtain optimal signal amplitudes, detectors, and detector randomization factors.
It is shown that the solution of this joint optimization problem can be calculated
in two steps, resulting in significant reduction in computational complexity. It is
proved that the optimal solution is achieved via randomization among at most
min{K, Nd} detector sets, where K is the number of users and Nd is the number
of detectors at each receiver. Lower and upper bounds are derived on the performance
of optimal detector randomization, and it is proved that the optimal
detector randomization approach can reduce the worst-case average probability
of error of the optimal approach that employs a single detector for each user by
up to K times. Various sufficient conditions are obtained for the improvability
and nonimprovability via detector randomization. In the special case of equal crosscorrelations and noise powers, a simple solution is developed for the optimal
detector randomization problem, and necessary and sufficient conditions are
presented for the uniqueness of that solution.
Next, a single-user M−ary communication system is considered in which the
transmitter and the receiver are connected via multiple additive (possibly nonGaussian)
noise channels, any one of which can be utilized for a given symbol
transmission. Contrary to deterministic signaling (i.e., employing a fixed constellation),
a stochastic signaling approach is adopted by treating the signal values
transmitted for each information symbol over each channel as random variables.
In particular, the joint optimization of the channel switching (i.e., time-sharing
among different channels) strategy, stochastic signals, and decision rules at the receiver
is performed in order to minimize the average probability of error under an
average transmit power constraint. It is proved that the solution to this problem
involves either one of the following: (i) deterministic signaling over a single channel,
(ii) randomizing (time-sharing) between two different signal constellations
over a single channel, or (iii) switching (time-sharing) between two channels with
deterministic signaling over each channel. For all cases, the optimal strategies
are shown to employ corresponding maximum a posteriori probability (MAP)
decision rules at the receiver.Tutay, Mehmet EminPh.D
Stochastic signaling in the presence of channel state information uncertainty
Cataloged from PDF version of article.In this paper, stochastic signaling is studied for power-constrained scalar valued binary communications systems in the presence of uncertainties in channel state information (CSI). First, stochastic signaling based on the available imperfect channel coefficient at the transmitter is analyzed, and it is shown that optimal signals can be represented by a randomization between at most two distinct signal levels for each symbol. Then, performance of stochastic signaling and conventional deterministic signaling is compared for this scenario, and sufficient conditions are derived for improvability and nonimprovability of deterministic signaling via stochastic signaling in the presence of CSI uncertainty. Furthermore, under CSI uncertainty, two different stochastic signaling strategies, namely, robust stochastic signaling and stochastic signaling with averaging, are proposed. For the robust stochastic signaling problem, sufficient conditions are derived for reducing the problem to a simpler form. It is shown that the optimal signal for each symbol can be expressed as a randomization between at most two distinct signal values for stochastic signaling with averaging, as well as for robust stochastic signaling under certain conditions. Finally, two numerical examples are presented to explore the theoretical results. (C) 2012 Elsevier Inc. All rights reserve
Stochastic signal design on the downlink of a multiuser communications system
Stochastic signal design is studied for the downlink of a multiuser communications system. First, a formulation is proposed for the joint design of optimal stochastic signals. Then, an approximate formulation, which can get arbitrarily close to the optimal solution, is obtained based on convex relaxation. In addition, when the receivers employ symmetric signaling and sign detectors, it is shown that the maximum asymptotical improvement ratio is equal to the number of users, and the conditions under which that maximum asymptotical improvement ratio is achieved are presented. Numerical examples are provided to explain the theoretical results. © 2012 IEEE
Optimal channel switching in the presence of stochastic signaling
Optimal channel switching and detector design is studied for M-ary communication systems in the presence of stochastic signaling, which facilitates randomization of signal values transmitted for each information symbol. Considering the presence of multiple additive noise channels (which can have non-Gaussian distributions in general) between a transmitter and a receiver, the joint optimization of the channel switching (timesharing) strategy, stochastic signals, and detectors is performed in order to achieve the minimum average probability of error. It is proved that the optimal solution to this problem corresponds to either (i) switching between at most two channels with deterministic signaling over each channel, or (ii) time-sharing between at most two different signals over a single channel (i.e., stochastic signaling over a single channel). For both cases, the optimal solutions are shown to employ corresponding maximum a posteriori probability (MAP) detectors at the receiver. Numerical results are presented to investigate the proposed approach. © 2013 IEEE
Stochastic signaling for power constrained communication systems
Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Science of Bilkent University, 2011.Thesis (Master's) -- Bilkent University, 2011.Includes bibliographical references leaves 93-97.In this thesis, optimal stochastic signaling problem is studied for power constrained
communications systems. In the first part, optimal stochastic signaling
problem is investigated for binary communications systems under second and
fourth moment constraints for any given detector structure and noise probability
distribution. It is shown that an optimal signal can be represented by randomization
among at most three signal levels for each symbol. Next, stochastic signaling
problem is studied in the presence of an average power constraint instead of second
and fourth moment constraints. It is shown that an optimal signal can be
represented by randomization between at most two signal levels for each symbol
in this case. For both scenarios, sufficient conditions are obtained to determine
the improvability and nonimprovability of conventional deterministic signaling
via stochastic signaling. In the second part of the thesis, the joint design of
optimal signals and optimal detector is studied for binary communications systems
under average power constraints in the presence of additive non-Gaussian
noise. It is shown that the optimal solution involves randomization between at
most two signal levels and the use of the corresponding maximum a posteriori
probability (MAP) detector. In the last part of the thesis, stochastic signaling
is investigated for power-constrained scalar valued binary communications systems
in the presence of uncertainties in channel state information (CSI). First,
stochastic signaling is performed based on the available imperfect channel coef-
ficient at the transmitter to examine the effects of imperfect CSI. The sufficient
conditions are derived for improvability and nonimprovability of deterministic
signaling via stochastic signaling in the presence of CSI uncertainty. Then, two
different stochastic signaling strategies, namely, robust stochastic signaling and
stochastic signaling with averaging, are proposed for designing stochastic signals
under CSI uncertainty. For the robust stochastic signaling problem, sufficient
conditions are derived to obtain an equivalent form which is simpler to solve.
In addition, it is shown that optimal signals for each symbol can be written as
randomization between at most two signal levels for stochastic signaling using
imperfect channel coefficient and stochastic signaling with averaging as well as
for robust stochastic signaling under certain conditions. The solutions of the
optimal stochastic signaling problems are obtained by using global optimization
techniques, specifically, Particle Swarm Optimization (PSO), and by employing
convex relaxation approaches. Numerical examples are presented to illustrate
the theoretical results at the end of each part.Göken, ÇağrıM.S
Optimal channel switching in multiuser systems under average capacity constraints
In this paper, the optimal channel switching problem is studied for average capacity maximization in the presence of multiple receivers in the communication system. First, the optimal channel switching problem is proposed for average capacity maximization of the communication between the transmitter and the secondary receiver while fulfilling the minimum average capacity requirement of the primary receiver and considering the average and peak power constraints. Then, an alternative equivalent optimization problem is provided and it is shown that the solution of this optimization problem satisfies the constraints with equality. Based on the alternative optimization problem, it is obtained that the optimal channel switching strategy employs at most three communication links in the presence of multiple available channels in the system. In addition, the optimal strategies are specified in terms of the number of channels employed by the transmitter to communicate with the primary and secondary receivers. Finally, numerical examples are provided in order to verify the theoretical investigations. © 2017 Elsevier Inc
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