16,560 research outputs found
Multiaccess Channels with State Known to One Encoder: Another Case of Degraded Message Sets
We consider a two-user state-dependent multiaccess channel in which only one
of the encoders is informed, non-causally, of the channel states. Two
independent messages are transmitted: a common message transmitted by both the
informed and uninformed encoders, and an individual message transmitted by only
the uninformed encoder. We derive inner and outer bounds on the capacity region
of this model in the discrete memoryless case as well as the Gaussian case.
Further, we show that the bounds for the Gaussian case are tight in some
special cases.Comment: 5 pages, Proc. of IEEE International Symposium on Information theory,
ISIT 2009, Seoul, Kore
Advances in Calibration and Imaging Techniques in Radio Interferometry
This paper summarizes some of the major calibration and image reconstruction
techniques used in radio interferometry and describes them in a common
mathematical framework. The use of this framework has a number of benefits,
ranging from clarification of the fundamentals, use of standard numerical
optimization techniques, and generalization or specialization to new
algorithms
Degraded Broadcast Diamond Channels with Non-Causal State Information at the Source
A state-dependent degraded broadcast diamond channel is studied where the
source-to-relays cut is modeled with two noiseless, finite-capacity digital
links with a degraded broadcasting structure, while the relays-to-destination
cut is a general multiple access channel controlled by a random state. It is
assumed that the source has non-causal channel state information and the relays
have no state information. Under this model, first, the capacity is
characterized for the case where the destination has state information, i.e.,
has access to the state sequence. It is demonstrated that in this case, a joint
message and state transmission scheme via binning is optimal. Next, the case
where the destination does not have state information, i.e., the case with
state information at the source only, is considered. For this scenario, lower
and upper bounds on the capacity are derived for the general discrete
memoryless model. Achievable rates are then computed for the case in which the
relays-to-destination cut is affected by an additive Gaussian state. Numerical
results are provided that illuminate the performance advantages that can be
accrued by leveraging non-causal state information at the source.Comment: Submitted to IEEE Transactions on Information Theory, Feb. 201
- …