Search

We revisit the problems of state masking and state amplification through the lens of empirical coordination. Specifically, we characterize the rate-equivocation-coordination trade-offs regions of a state-dependent channel in which the encoder has causal and strictly causal state knowledge. We also extend this characterization to the cases of two-sided state information and noisy channel feedback. Our approach is based on the notion of core of the receiver’s knowledge, which we introduce to capture what the decoder can infer about all the signals involved in the model. Finally, we exploit the aforementioned results to solve a channel state estimation zero-sum game in which the encoder prevents the decoder to estimate the channel state accurately. [ABSTRACT FROM AUTHOR]

In a decentralized and self-configuring network, the communication devices are considered as autonomous decision makers that sense their environment and that implement optimal transmission schemes. It is essential that these autonomous devices cooperate and coordinate their actions, to ensure the reliability of the transmissions and the stability of the network. We study a point-to-point scenario in which the encoder and the decoder implement decentralized policies that are coordinated. The coordination is measured in terms of empirical frequency of symbols of source and channel. The encoder and the decoder perform a coding scheme, such that the empirical distribution of the symbols is close to a target joint probability distribution. We characterize the set of achievable target probability distributions for a point-to-point source-channel model, in which the encoder is non-causal and the decoder is strictly causal, i.e., it returns an action based on the observation of the past channel outputs. The objectives of the encoder and of the decoder are captured by some utility function, evaluated with respect to the set of achievable target probability distributions. In this paper, we investigate the maximization problem of a utility function that is common to both encoder and decoder. We show that the compression and the transmission of information are particular cases of the empirical coordination. [ABSTRACT FROM AUTHOR]

A decentralized network of cognitive and noncognitive transmitters where each transmitter aims at maximizing his energy efficiency is considered. The cognitive transmitters are assumed to be able to sense the transmit power of their noncognitive counterparts and the former have a cost for sensing. The Stackelberg equilibrium analysis of this two-level hierarchical game is conducted, which allows us to better understand the effects of cognition on energy efficiency. In particular, it is proven that the network energy efficiency is maximized when only a given fraction of terminals are cognitive. Then, we study a sensing game where all the transmitters are assumed to take the decision of whether to sense (namely to be cognitive) or not. This game is shown to be a weighted potential game, and its set of equilibria is studied. Playing the sensing game in a first phase (e.g., of a time slot) and then playing the power control game is shown to be more efficient individually for all transmitters than playing a game where a transmitter would jointly optimize whether to sense his power level, showing the existence of a kind of Braess paradox. The derived results are illustrated by numerical results and provide some insights on how to deploy cognitive radios in heterogeneous networks in terms of sensing capabilities. [ABSTRACT FROM PUBLISHER]

We consider a network of two nodes separated by a noisy channel with two-sided state information, in which the input and output signals have to be coordinated with the source and its reconstruction. In the case of non-causal encoding and decoding, we propose a joint source-channel coding scheme and we develop inner and outer bounds for the strong coordination region. While the inner and outer bounds do not match in general, we provide a complete characterization of the strong coordination region in three particular cases: i) when the channel is perfect; ii) when the decoder is lossless; and iii) when the random variables of the channel are independent from the random variables of the source. Through the study of these special cases, we prove that the separation principle does not hold for the joint source-channel strong coordination. Finally, in the absence of state information, we show that polar codes achieve a subset of the best known inner bound for the strong coordination region, therefore offering a constructive alternative to random binning and coding proofs. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a coding strategy devised to increase the throughput in hybrid ARQ (HARQ) transmission over a block fading channel. In our approach, the transmitter jointly encodes a variable number of bits for the each round of HARQ. The parameters (rates) of this joint coding can vary and may be based on the negative acknowledgment provided by the receiver or, on the past (outdated) information about the channel states. These new degrees of freedom allow us to improve the match between the codebook and the channel states experienced by the receiver. The results indicate that gains obtained using the proposed cross-packet coding strategy are particularly notable for the large values of the throughput. In this region, the conventional HARQ fails to offer throughput improvement even if the number of transmission rounds is increased. We implement the proposed cross-packet HARQ using turbo codes, where we show that the theoretically predicted throughput gains materialize in practice; the implementation challenges are also discussed. [ABSTRACT FROM PUBLISHER]