704 research outputs found
Dirty Paper Arbitrarily Varying Channel with a State-Aware Adversary
In this paper, we take an arbitrarily varying channel (AVC) approach to
examine the problem of writing on a dirty paper in the presence of an
adversary. We consider an additive white Gaussian noise (AWGN) channel with an
additive white Gaussian state, where the state is known non-causally to the
encoder and the adversary, but not the decoder. We determine the randomized
coding capacity of this AVC under the maximal probability of error criterion.
Interestingly, it is shown that the jamming adversary disregards the state
knowledge to choose a white Gaussian channel input which is independent of the
state
Correlated Jamming in a Joint Source Channel Communication System
We study correlated jamming in joint source-channel communication systems. An
i.i.d. source is to be communicated over a memoryless channel in the presence
of a correlated jammer with non-causal knowledge of user transmission. This
user-jammer interaction is modeled as a zero sum game. A set of conditions on
the source and the channel is provided for the existence of a Nash equilibrium
for this game, where the user strategy is uncoded transmission and the jammer
strategy is i.i.d jamming. This generalizes a well-known example of uncoded
communication of a Gaussian sources over Gaussian channels with additive
jamming. Another example, of a Binary Symmetric source over a Binary Symmetric
channel with jamming, is provided as a validation of this result
How to Securely Compute the Modulo-Two Sum of Binary Sources
In secure multiparty computation, mutually distrusting users in a network
want to collaborate to compute functions of data which is distributed among the
users. The users should not learn any additional information about the data of
others than what they may infer from their own data and the functions they are
computing. Previous works have mostly considered the worst case context (i.e.,
without assuming any distribution for the data); Lee and Abbe (2014) is a
notable exception. Here, we study the average case (i.e., we work with a
distribution on the data) where correctness and privacy is only desired
asymptotically.
For concreteness and simplicity, we consider a secure version of the function
computation problem of K\"orner and Marton (1979) where two users observe a
doubly symmetric binary source with parameter p and the third user wants to
compute the XOR. We show that the amount of communication and randomness
resources required depends on the level of correctness desired. When zero-error
and perfect privacy are required, the results of Data et al. (2014) show that
it can be achieved if and only if a total rate of 1 bit is communicated between
every pair of users and private randomness at the rate of 1 is used up. In
contrast, we show here that, if we only want the probability of error to vanish
asymptotically in block length, it can be achieved by a lower rate (binary
entropy of p) for all the links and for private randomness; this also
guarantees perfect privacy. We also show that no smaller rates are possible
even if privacy is only required asymptotically.Comment: 6 pages, 1 figure, extended version of submission to IEEE Information
Theory Workshop, 201
The Oblivious Transfer Capacity of the Wiretapped Binary Erasure Channel
We consider oblivious transfer between Alice and Bob in the presence of an
eavesdropper Eve when there is a broadcast channel from Alice to Bob and Eve.
In addition to the secrecy constraints of Alice and Bob, Eve should not learn
the private data of Alice and Bob. When the broadcast channel consists of two
independent binary erasure channels, we derive the oblivious transfer capacity
for both 2-privacy (where the eavesdropper may collude with either party) and
1-privacy (where there are no collusions).Comment: This is an extended version of the paper "The Oblivious Transfer
Capacity of the Wiretapped Binary Erasure Channel" to be presented at ISIT
201
Rigid Body Motion Estimation based on the Lagrange-d'Alembert Principle
Stable estimation of rigid body pose and velocities from noisy measurements,
without any knowledge of the dynamics model, is treated using the
Lagrange-d'Alembert principle from variational mechanics. With body-fixed
optical and inertial sensor measurements, a Lagrangian is obtained as the
difference between a kinetic energy-like term that is quadratic in velocity
estimation error and the sum of two artificial potential functions; one
obtained from a generalization of Wahba's function for attitude estimation and
another which is quadratic in the position estimate error. An additional
dissipation term that is linear in the velocity estimation error is introduced,
and the Lagrange-d'Alembert principle is applied to the Lagrangian with this
dissipation. This estimation scheme is discretized using discrete variational
mechanics. The presented pose estimator requires optical measurements of at
least three inertially fixed landmarks or beacons in order to estimate
instantaneous pose. The discrete estimation scheme can also estimate velocities
from such optical measurements. In the presence of bounded measurement noise in
the vector measurements, numerical simulations show that the estimated states
converge to a bounded neighborhood of the actual states.Comment: My earlier submitted manuscript (arXiv:1508.07671), is an extended
version of this work, containing detailed proofs and more elaborated
numerical simulations, currently under review in Automatica. This paper will
be cited in the extended journal version (arXiv:1508.07671) upon publicatio
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