275 research outputs found
Capacity Region of the Broadcast Channel with Two Deterministic Channel State Components
This paper establishes the capacity region of a class of broadcast channels
with random state in which each channel component is selected from two possible
functions and each receiver knows its state sequence. This channel model does
not fit into any class of broadcast channels for which the capacity region was
previously known and is useful in studying wireless communication channels when
the fading state is known only at the receivers. The capacity region is shown
to coincide with the UV outer bound and is achieved via Marton coding.Comment: 5 pages, 3 figures. Submitted to ISIT 201
Limits on the Benefits of Energy Storage for Renewable Integration
The high variability of renewable energy resources presents significant
challenges to the operation of the electric power grid. Conventional generators
can be used to mitigate this variability but are costly to operate and produce
carbon emissions. Energy storage provides a more environmentally friendly
alternative, but is costly to deploy in large amounts. This paper studies the
limits on the benefits of energy storage to renewable energy: How effective is
storage at mitigating the adverse effects of renewable energy variability? How
much storage is needed? What are the optimal control policies for operating
storage? To provide answers to these questions, we first formulate the power
flow in a single-bus power system with storage as an infinite horizon
stochastic program. We find the optimal policies for arbitrary net renewable
generation process when the cost function is the average conventional
generation (environmental cost) and when it is the average loss of load
probability (reliability cost). We obtain more refined results by considering
the multi-timescale operation of the power system. We view the power flow in
each timescale as the superposition of a predicted (deterministic) component
and an prediction error (residual) component and formulate the residual power
flow problem as an infinite horizon dynamic program. Assuming that the net
generation prediction error is an IID process, we quantify the asymptotic
benefits of storage. With the additional assumption of Laplace distributed
prediction error, we obtain closed form expressions for the stationary
distribution of storage and conventional generation. Finally, we propose a
two-threshold policy that trades off conventional generation saving with loss
of load probability. We illustrate our results and corroborate the IID and
Laplace assumptions numerically using datasets from CAISO and NREL.Comment: 45 pages, 17 figure
Lecture Notes on Network Information Theory
These lecture notes have been converted to a book titled Network Information
Theory published recently by Cambridge University Press. This book provides a
significantly expanded exposition of the material in the lecture notes as well
as problems and bibliographic notes at the end of each chapter. The authors are
currently preparing a set of slides based on the book that will be posted in
the second half of 2012. More information about the book can be found at
http://www.cambridge.org/9781107008731/. The previous (and obsolete) version of
the lecture notes can be found at http://arxiv.org/abs/1001.3404v4/
Interference Networks with Point-to-Point Codes
The paper establishes the capacity region of the Gaussian interference
channel with many transmitter-receiver pairs constrained to use point-to-point
codes. The capacity region is shown to be strictly larger in general than the
achievable rate regions when treating interference as noise, using successive
interference cancellation decoding, and using joint decoding. The gains in
coverage and achievable rate using the optimal decoder are analyzed in terms of
ensemble averages using stochastic geometry. In a spatial network where the
nodes are distributed according to a Poisson point process and the channel path
loss exponent is , it is shown that the density of users that can be
supported by treating interference as noise can scale no faster than
as the bandwidth grows, while the density of users can scale
linearly with under optimal decoding
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