2,534 research outputs found
Physical-layer Network Coding: A Random Coding Error Exponent Perspective
In this work, we derive the random coding error exponent for the uplink phase
of a two-way relay system where physical layer network coding (PNC) is
employed. The error exponent is derived for the practical (yet sub-optimum) XOR
channel decoding setting. We show that the random coding error exponent under
optimum (i.e., maximum likelihood) PNC channel decoding can be achieved even
under the sub-optimal XOR channel decoding. The derived achievability bounds
provide us with valuable insight and can be used as a benchmark for the
performance of practical channel-coded PNC systems employing low complexity
decoders when finite-length codewords are used.Comment: Submitted to IEEE International Symposium on Information Theory
(ISIT), 201
Compute-and-Forward Relay Networks with Asynchronous, Mobile, and Delay-Sensitive Users
We consider a wireless network consisting of multiple source nodes, a set of relays
and a destination node. Suppose the sources transmit their messages simultaneously
to the relays and the destination aims to decode all the messages. At the physical layer,
a conventional approach would be for the relay to decode the individual message
one at a time while treating rest of the messages as interference. Compute-and-forward
is a novel strategy which attempts to turn the situation around by treating
the interference as a constructive phenomenon. In compute-and-forward, each relay
attempts to directly compute a combination of the transmitted messages and then
forwards it to the destination. Upon receiving the combinations of messages from the
relays, the destination can recover all the messages by solving the received equations.
When identical lattice codes are employed at the sources, error correction to integer
combination of messages is a viable option by exploiting the algebraic structure of
lattice codes. Therefore, compute-and-forward with lattice codes enables the relay
to manage interference and perform error correction concurrently. It is shown that
compute-and-forward exhibits substantial improvement in the achievable rate compared
with other state-of-the-art schemes for medium to high signal-to-noise ratio
regime.
Despite several results that show the excellent performance of compute-and-forward,
there are still important challenges to overcome before we can utilize compute-and-
forward in practice. Some important challenges include the assumptions of \perfect
timing synchronization "and \quasi-static fading", since these assumptions rarely
hold in realistic wireless channels. So far, there are no conclusive answers to whether
compute-and-forward can still provide substantial gains even when these assumptions
are removed. When lattice codewords are misaligned and mixed up, decoding integer
combination of messages is not straightforward since the linearity of lattice codes is
generally not invariant to time shift. When channel exhibits time selectivity, it brings
challenges to compute-and-forward since the linearity of lattice codes does not suit
the time varying nature of the channel. Another challenge comes from the emerging
technologies for future 5G communication, e.g., autonomous driving and virtual
reality, where low-latency communication with high reliability is necessary. In this
regard, powerful short channel codes with reasonable encoding/decoding complexity
are indispensable. Although there are fruitful results on designing short channel
codes for point-to-point communication, studies on short code design specifically for
compute-and-forward are rarely found.
The objective of this dissertation is threefold. First, we study compute-and-forward
with timing-asynchronous users. Second, we consider the problem of compute-and-
forward over block-fading channels. Finally, the problem of compute-and-forward
for low-latency communication is studied. Throughout the dissertation, the research
methods and proposed remedies will center around the design of lattice codes in order
to facilitate the use of compute-and-forward in the presence of these challenges
CoCalc as a Learning Tool for Neural Network Simulation in the Special Course "Foundations of Mathematic Informatics"
The role of neural network modeling in the learning content of the special
course "Foundations of Mathematical Informatics" was discussed. The course was
developed for the students of technical universities - future IT-specialists
and directed to breaking the gap between theoretic computer science and it's
applied applications: software, system and computing engineering. CoCalc was
justified as a learning tool of mathematical informatics in general and neural
network modeling in particular. The elements of technique of using CoCalc at
studying topic "Neural network and pattern recognition" of the special course
"Foundations of Mathematic Informatics" are shown. The program code was
presented in a CoffeeScript language, which implements the basic components of
artificial neural network: neurons, synaptic connections, functions of
activations (tangential, sigmoid, stepped) and their derivatives, methods of
calculating the network's weights, etc. The features of the Kolmogorov-Arnold
representation theorem application were discussed for determination the
architecture of multilayer neural networks. The implementation of the
disjunctive logical element and approximation of an arbitrary function using a
three-layer neural network were given as an examples. According to the
simulation results, a conclusion was made as for the limits of the use of
constructed networks, in which they retain their adequacy. The framework topics
of individual research of the artificial neural networks is proposed.Comment: 16 pages, 3 figures, Proceedings of the 13th International Conference
on ICT in Education, Research and Industrial Applications. Integration,
Harmonization and Knowledge Transfer (ICTERI, 2018
Differential Distributed Space-Time Coding with Imperfect Synchronization in Frequency-Selective Channels
Differential distributed space-time coding (D-DSTC) is a cooperative
transmission technique that can improve diversity in wireless relay networks in
the absence of channel information. Conventionally, it is assumed that channels
are flat-fading and relays are perfectly synchronized at the symbol level.
However, due to the delay spread in broadband systems and the distributed
nature of relay networks, these assumptions may be violated. Hence,
inter-symbol interference (ISI) may appear. This paper proposes a new
differential encoding and decoding process for D-DSTC systems with multiple
relays over slow frequency-selective fading channels with imperfect
synchronization. The proposed method overcomes the ISI caused by
frequency-selectivity and is robust against synchronization errors while not
requiring any channel information at the relays and destination. Moreover, the
maximum possible diversity with a decoding complexity similar to that of the
conventional D-DSTC is attained. Simulation results are provided to show the
performance of the proposed method in various scenarios.Comment: to appear in IEEE Transaction on Wireless Communications, 201
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