State Leakage and Coordination of Actions: Core of the Receiver's Knowledge

We revisit the problems of state masking and state amplification through the lens of empirical coordination by considering a state-dependent channel in which the encoder has causal and strictly causal state knowledge. We show that the problem of empirical coordination provides a natural framework in which to jointly study the problems of reliable communication, state masking, and state amplification. We characterize the regions of rate-equivocation-coordination trade-offs for several channel models with causal and strictly causal state knowledge. We introduce the notion of `core of the receiver's knowledge' to capture what the decoder can infer about all the signals involved in the model. We exploit this result to solve a channel state estimation zero-sum game in which the encoder prevents the decoder to estimate the channel state accurately.Comment: preliminary draf

Strong Coordination over a Line Network

We study the problem of strong coordination in a three-terminal line network, in which agents use common randomness and communicate over a line network to ensure that their actions follow a prescribed behavior, modeled by a target joint distribution of actions. We provide inner and outer bounds to the coordination capacity region, and show that these bounds are partially optimal. We leverage this characterization to develop insight into the interplay between communication and coordination. Specifically, we show that common randomness helps to achieve optimal communication rates between agents, and that matching the network topology to the behavior structure may reduce inter-agent communication rates.Comment: To be presented at ISIT 2013, Istanbul, Turke

Empirical and Strong Coordination via Soft Covering with Polar Codes

We design polar codes for empirical coordination and strong coordination in two-node networks. Our constructions hinge on the fact that polar codes enable explicit low-complexity schemes for soft covering. We leverage this property to propose explicit and low-complexity coding schemes that achieve the capacity regions of both empirical coordination and strong coordination for sequences of actions taking value in an alphabet of prime cardinality. Our results improve previously known polar coding schemes, which (i) were restricted to uniform distributions and to actions obtained via binary symmetric channels for strong coordination, (ii) required a non-negligible amount of common randomness for empirical coordination, and (iii) assumed that the simulation of discrete memoryless channels could be perfectly implemented. As a by-product of our results, we obtain a polar coding scheme that achieves channel resolvability for an arbitrary discrete memoryless channel whose input alphabet has prime cardinality.Comment: 14 pages, two-column, 5 figures, accepted to IEEE Transactions on Information Theor

Secret key generation from Gaussian sources using lattice hashing

We propose a simple yet complete lattice-based scheme for secret key generation from Gaussian sources in the presence of an eavesdropper, and show that it achieves strong secret key rates up to 1/2 nat from the optimal in the case of "degraded" source models. The novel ingredient of our scheme is a lattice-hashing technique, based on the notions of flatness factor and channel intrinsic randomness. The proposed scheme does not require dithering.Comment: 5 pages, Conference (ISIT 2013

Covert Capacity of Non-Coherent Rayleigh-Fading Channels

The covert capacity is characterized for a non-coherent fast Rayleigh-fading wireless channel, in which a legitimate user wishes to communicate reliably with a legitimate receiver while escaping detection from a warden. It is shown that the covert capacity is achieved with an amplitude-constrained input distribution that consists of a finite number of mass points including one at zero and numerically tractable bounds are provided. It is also conjectured that distributions with two mass points in fixed locations are optimal

Lossy Compression with Near-uniform Encoder Outputs

It is well known that lossless compression of a discrete memoryless source with near-uniform encoder output is possible at a rate above its entropy if and only if the encoder is randomized. This work focuses on deriving conditions for near-uniform encoder output(s) in the Wyner-Ziv and the distributed lossy compression problems. We show that in the Wyner-Ziv problem, near-uniform encoder output and operation close to the WZ-rate limit is simultaneously possible, whereas in the distributed lossy compression problem, jointly near-uniform outputs is achievable in the interior of the distributed lossy compression rate region if the sources share non-trivial G\'{a}cs-K\"{o}rner common information.Comment: Submitted to the 2016 IEEE International Symposium on Information Theory (11 Pages, 3 Figures