17,153 research outputs found
Capacity Region of Finite State Multiple-Access Channel with Delayed State Information at the Transmitters
A single-letter characterization is provided for the capacity region of
finite-state multiple access channels. The channel state is a Markov process,
the transmitters have access to delayed state information, and channel state
information is available at the receiver. The delays of the channel state
information are assumed to be asymmetric at the transmitters. We apply the
result to obtain the capacity region for a finite-state Gaussian MAC, and for a
finite-state multiple-access fading channel. We derive power control strategies
that maximize the capacity region for these channels
On AVCs with Quadratic Constraints
In this work we study an Arbitrarily Varying Channel (AVC) with quadratic
power constraints on the transmitter and a so-called "oblivious" jammer (along
with additional AWGN) under a maximum probability of error criterion, and no
private randomness between the transmitter and the receiver. This is in
contrast to similar AVC models under the average probability of error criterion
considered in [1], and models wherein common randomness is allowed [2] -- these
distinctions are important in some communication scenarios outlined below.
We consider the regime where the jammer's power constraint is smaller than
the transmitter's power constraint (in the other regime it is known no positive
rate is possible). For this regime we show the existence of stochastic codes
(with no common randomness between the transmitter and receiver) that enables
reliable communication at the same rate as when the jammer is replaced with
AWGN with the same power constraint. This matches known information-theoretic
outer bounds. In addition to being a stronger result than that in [1] (enabling
recovery of the results therein), our proof techniques are also somewhat more
direct, and hence may be of independent interest.Comment: A shorter version of this work will be send to ISIT13, Istanbul. 8
pages, 3 figure
Stochastic Stability of Event-triggered Anytime Control
We investigate control of a non-linear process when communication and
processing capabilities are limited. The sensor communicates with a controller
node through an erasure channel which introduces i.i.d. packet dropouts.
Processor availability for control is random and, at times, insufficient to
calculate plant inputs. To make efficient use of communication and processing
resources, the sensor only transmits when the plant state lies outside a
bounded target set. Control calculations are triggered by the received data. If
a plant state measurement is successfully received and while the processor is
available for control, the algorithm recursively calculates a sequence of
tentative plant inputs, which are stored in a buffer for potential future use.
This safeguards for time-steps when the processor is unavailable for control.
We derive sufficient conditions on system parameters for stochastic stability
of the closed loop and illustrate performance gains through numerical studies.Comment: IEEE Transactions on Automatic Control, under revie
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