293,105 research outputs found
The Capacity of Channels with Feedback
We introduce a general framework for treating channels with memory and
feedback. First, we generalize Massey's concept of directed information and use
it to characterize the feedback capacity of general channels. Second, we
present coding results for Markov channels. This requires determining
appropriate sufficient statistics at the encoder and decoder. Third, a dynamic
programming framework for computing the capacity of Markov channels is
presented. Fourth, it is shown that the average cost optimality equation (ACOE)
can be viewed as an implicit single-letter characterization of the capacity.
Fifth, scenarios with simple sufficient statistics are described
Capacity of a POST Channel with and without Feedback
We consider finite state channels where the state of the channel is its
previous output. We refer to these as POST (Previous Output is the STate)
channels. We first focus on POST() channels. These channels have binary
inputs and outputs, where the state determines if the channel behaves as a
or an channel, both with parameter . %with parameter We
show that the non feedback capacity of the POST() channel equals its
feedback capacity, despite the memory of the channel. The proof of this
surprising result is based on showing that the induced output distribution,
when maximizing the directed information in the presence of feedback, can also
be achieved by an input distribution that does not utilize of the feedback. We
show that this is a sufficient condition for the feedback capacity to equal the
non feedback capacity for any finite state channel. We show that the result
carries over from the POST() channel to a binary POST channel where the
previous output determines whether the current channel will be binary with
parameters or . Finally, we show that, in general, feedback may
increase the capacity of a POST channel
On the Capacity of Symmetric Gaussian Interference Channels with Feedback
In this paper, we propose a new coding scheme for symmetric Gaussian
interference channels with feedback based on the ideas of time-varying coding
schemes. The proposed scheme improves the Suh-Tse and Kramer inner bounds of
the channel capacity for the cases of weak and not very strong interference.
This improvement is more significant when the signal-to-noise ratio (SNR) is
not very high. It is shown theoretically and numerically that our coding scheme
can outperform the Kramer code. In addition, the generalized degrees-of-freedom
of our proposed coding scheme is equal to the Suh-Tse scheme in the strong
interference case. The numerical results show that our coding scheme can attain
better performance than the Suh-Tse coding scheme for all channel parameters.
Furthermore, the simplicity of the encoding/decoding algorithms is another
strong point of our proposed coding scheme compared with the Suh-Tse coding
scheme. More importantly, our results show that an optimal coding scheme for
the symmetric Gaussian interference channels with feedback can be achieved by
using only marginal posterior distributions under a better cooperation strategy
between transmitters.Comment: To appear in Proc. of IEEE International Symposium on Information
Theory (ISIT), Hong Kong, June 14-19, 201
Identification via Quantum Channels in the Presence of Prior Correlation and Feedback
Continuing our earlier work (quant-ph/0401060), we give two alternative
proofs of the result that a noiseless qubit channel has identification capacity
2: the first is direct by a "maximal code with random extension" argument, the
second is by showing that 1 bit of entanglement (which can be generated by
transmitting 1 qubit) and negligible (quantum) communication has identification
capacity 2.
This generalises a random hashing construction of Ahlswede and Dueck: that 1
shared random bit together with negligible communication has identification
capacity 1.
We then apply these results to prove capacity formulas for various quantum
feedback channels: passive classical feedback for quantum-classical channels, a
feedback model for classical-quantum channels, and "coherent feedback" for
general channels.Comment: 19 pages. Requires Rinton-P9x6.cls. v2 has some minor errors/typoes
corrected and the claims of remark 22 toned down (proofs are not so easy
after all). v3 has references to simultaneous ID coding removed: there were
necessary changes in quant-ph/0401060. v4 (final form) has minor correction
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