219 research outputs found
Capacity of a Class of State-Dependent Orthogonal Relay Channels
The class of orthogonal relay channels in which the orthogonal channels
connecting the source terminal to the relay and the destination, and the relay
to the destination, depend on a state sequence, is considered. It is assumed
that the state sequence is fully known at the destination while it is not known
at the source or the relay. The capacity of this class of relay channels is
characterized, and shown to be achieved by the partial
decode-compress-and-forward (pDCF) scheme. Then the capacity of certain binary
and Gaussian state-dependent orthogonal relay channels are studied in detail,
and it is shown that the compress-and-forward (CF) and
partial-decode-and-forward (pDF) schemes are suboptimal in general. To the best
of our knowledge, this is the first single relay channel model for which the
capacity is achieved by pDCF, while pDF and CF schemes are both suboptimal.
Furthermore, it is shown that the capacity of the considered class of
state-dependent orthogonal relay channels is in general below the cut-set
bound. The conditions under which pDF or CF suffices to meet the cut-set bound,
and hence, achieve the capacity, are also derived.Comment: This paper has been accepted by IEEE Transactions on Information
Theor
Distortion Exponent in MIMO Fading Channels with Time-Varying Source Side Information
Transmission of a Gaussian source over a time-varying multiple-input
multiple-output (MIMO) channel is studied under strict delay constraints.
Availability of a correlated side information at the receiver is assumed, whose
quality, i.e., correlation with the source signal, also varies over time. A
block-fading model is considered for the states of the time-varying channel and
the time-varying side information; and perfect state information at the
receiver is assumed, while the transmitter knows only the statistics. The high
SNR performance, characterized by the \textit{distortion exponent}, is studied
for this joint source-channel coding problem. An upper bound is derived and
compared with lowers based on list decoding, hybrid digital-analog
transmission, as well as multi-layer schemes which transmit successive
refinements of the source, relying on progressive and superposed transmission
with list decoding. The optimal distortion exponent is characterized for the
single-input multiple-output (SIMO) and multiple-input single-output (MISO)
scenarios by showing that the distortion exponent achieved by multi-layer
superpositon encoding with joint decoding meets the proposed upper bound. In
the MIMO scenario, the optimal distortion exponent is characterized in the low
bandwidth ratio regime, and it is shown that the multi-layer superposition
encoding performs very close to the upper bound in the high bandwidth expansion
regime.Comment: Submitted to IEEE Transactions on Information Theor
Joint Source-Channel Coding with Time-Varying Channel and Side-Information
Transmission of a Gaussian source over a time-varying Gaussian channel is
studied in the presence of time-varying correlated side information at the
receiver. A block fading model is considered for both the channel and the side
information, whose states are assumed to be known only at the receiver. The
optimality of separate source and channel coding in terms of average end-to-end
distortion is shown when the channel is static while the side information state
follows a discrete or a continuous and quasiconcave distribution. When both the
channel and side information states are time-varying, separate source and
channel coding is suboptimal in general. A partially informed encoder lower
bound is studied by providing the channel state information to the encoder.
Several achievable transmission schemes are proposed based on uncoded
transmission, separate source and channel coding, joint decoding as well as
hybrid digital-analog transmission. Uncoded transmission is shown to be optimal
for a class of continuous and quasiconcave side information state
distributions, while the channel gain may have an arbitrary distribution. To
the best of our knowledge, this is the first example in which the uncoded
transmission achieves the optimal performance thanks to the time-varying nature
of the states, while it is suboptimal in the static version of the same
problem. Then, the optimal \emph{distortion exponent}, that quantifies the
exponential decay rate of the expected distortion in the high SNR regime, is
characterized for Nakagami distributed channel and side information states, and
it is shown to be achieved by hybrid digital-analog and joint decoding schemes
in certain cases, illustrating the suboptimality of pure digital or analog
transmission in general.Comment: Submitted to IEEE Transactions on Information Theor
A Learning Theoretic Approach to Energy Harvesting Communication System Optimization
A point-to-point wireless communication system in which the transmitter is
equipped with an energy harvesting device and a rechargeable battery, is
studied. Both the energy and the data arrivals at the transmitter are modeled
as Markov processes. Delay-limited communication is considered assuming that
the underlying channel is block fading with memory, and the instantaneous
channel state information is available at both the transmitter and the
receiver. The expected total transmitted data during the transmitter's
activation time is maximized under three different sets of assumptions
regarding the information available at the transmitter about the underlying
stochastic processes. A learning theoretic approach is introduced, which does
not assume any a priori information on the Markov processes governing the
communication system. In addition, online and offline optimization problems are
studied for the same setting. Full statistical knowledge and causal information
on the realizations of the underlying stochastic processes are assumed in the
online optimization problem, while the offline optimization problem assumes
non-causal knowledge of the realizations in advance. Comparing the optimal
solutions in all three frameworks, the performance loss due to the lack of the
transmitter's information regarding the behaviors of the underlying Markov
processes is quantified
On Joint Source-Channel Coding for Correlated Sources Over Multiple-Access Relay Channels
We study the transmission of correlated sources over discrete memoryless (DM)
multiple-access-relay channels (MARCs), in which both the relay and the
destination have access to side information arbitrarily correlated with the
sources. As the optimal transmission scheme is an open problem, in this work we
propose a new joint source-channel coding scheme based on a novel combination
of the correlation preserving mapping (CPM) technique with Slepian-Wolf (SW)
source coding, and obtain the corresponding sufficient conditions. The proposed
coding scheme is based on the decode-and-forward strategy, and utilizes CPM for
encoding information simultaneously to the relay and the destination, whereas
the cooperation information from the relay is encoded via SW source coding. It
is shown that there are cases in which the new scheme strictly outperforms the
schemes available in the literature. This is the first instance of a
source-channel code that uses CPM for encoding information to two different
nodes (relay and destination). In addition to sufficient conditions, we present
three different sets of single-letter necessary conditions for reliable
transmission of correlated sources over DM MARCs. The newly derived conditions
are shown to be at least as tight as the previously known necessary conditions.Comment: Accepted to TI
Source-Channel Coding for the Multiple-Access Relay Channel
This work considers reliable transmission of general correlated sources over
the multiple-access relay channel (MARC) and the multiple-access broadcast
relay channel (MABRC). In MARCs only the destination is interested in a
reconstruction of the sources, while in MABRCs both the relay and the
destination want to reconstruct the sources. We assume that both the relay and
the destination have correlated side information. We find sufficient conditions
for reliable communication based on operational separation, as well as
necessary conditions on the achievable source-channel rate. For correlated
sources transmitted over fading Gaussian MARCs and MABRCs we find conditions
under which informational separation is optimal.Comment: Presented in ISWCS 2011, Aachen, German
Source-Channel Coding Theorems for the Multiple-Access Relay Channel
We study reliable transmission of arbitrarily correlated sources over
multiple-access relay channels (MARCs) and multiple-access broadcast relay
channels (MABRCs). In MARCs only the destination is interested in
reconstructing the sources, while in MABRCs both the relay and the destination
want to reconstruct them. In addition to arbitrary correlation among the source
signals at the users, both the relay and the destination have side information
correlated with the source signals. Our objective is to determine whether a
given pair of sources can be losslessly transmitted to the destination for a
given number of channel symbols per source sample, defined as the
source-channel rate. Sufficient conditions for reliable communication based on
operational separation, as well as necessary conditions on the achievable
source-channel rates are characterized. Since operational separation is
generally not optimal for MARCs and MABRCs, sufficient conditions for reliable
communication using joint source-channel coding schemes based on a combination
of the correlation preserving mapping technique with Slepian-Wolf source coding
are also derived. For correlated sources transmitted over fading Gaussian MARCs
and MABRCs, we present conditions under which separation (i.e., separate and
stand-alone source and channel codes) is optimal. This is the first time
optimality of separation is proved for MARCs and MABRCs.Comment: Accepted to IEEE Transaction on Information Theor
Constraining Nelson-Barr Models with Generalized CP Transformations through Decoupling Analysis
This thesis aims to study a novel solution to the Strong CP Problem. As no experimental signals of an axion have been found yet, the Nelson-Barr mechanism is gaining more and more popularity. After a review of the Standard Model and the Strong CP Problem, a model is introduced which combines the Nelson-Barr mechanism with a non-conventional CP transformation of order 4. A slightly improved calculation of the 2-loop contribution to θ is presented and the decoupling limits of the model are discussed. While the abso- lute scales of the model evade prediction, a combination of the energy scales and Yukawa couplings is found that can be constrained. Fitting the model via Markov Chain Monte Carlo algorithm to experimental results supports these findings. For the fit, a focus on CP violating observables in the quark and meson sector is chosen. While the solution to the Strong CP problem might lie at energies far above the experimentally accessible scales, our results show a novel way to still constrain at least specific combinations of these high- energy scales. In the future, these results can work as a starting point to help constrain new creative model building ideas
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
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