This work introduces capacity limits for molecular timing (MT) channels, where information is modulated on the release timing of small information particles, and decoded from the time of arrival at the receiver. It is shown that the random time of arrival can be represented as an additive noise channel, and for the diffusion-based MT (DBMT) channel, this noise is distributed according to the Lévy distribution. Lower and upper bounds on the capacity of the DBMT channel are derived for the case where the delay associated with the propagation of information particles in the channel is finite. These bounds are also shown to be tight.

Abstract-We study reliable transmission of arbitrarily correlated sources over multiple-access relay channels (MARCs) and multiple-access broadcast relay channels (MABRCs). In MARCs only the destination is interested in reconstructing the sources, while in MABRCs both the relay and the destination want to reconstruct them. In addition to arbitrary correlation among the source signals at the users, both the relay and the destination have side information correlated with the source signals. Our objective is to determine whether a given pair of sources can be losslessly transmitted to the destination for a given number of channel symbols per source sample, defined as the sourcechannel rate. Sufficient conditions for reliable communication based on operational separation, as well as necessary conditions on the achievable source-channel rates are characterized. Since operational separation is generally not optimal for MARCs and MABRCs, sufficient conditions for reliable communication using joint source-channel coding schemes based on a combination of the correlation preserving mapping technique with SlepianWolf source coding are also derived. For correlated sources transmitted over fading Gaussian MARCs and MABRCs, we present conditions under which separation (i.e., separate and stand-alone source and channel codes) is optimal. This is the first time optimality of separation is proved for MARCs and MABRCs.

We study communications under slowly varying channels, and consider three cases of knowledge of the channel impulse response (CIR): full knowledge, no knowledge, and partial knowledge of the CIR. By partial knowledge, we refer to knowing only either the CIR magnitudes or the CIR phases. It is known that obtaining the exact joint maximum‐likelihood estimate (MLE) of the CFO and the SFO requires a two‐dimensional search. Here, we present a new estimation method which uses the Taylor expansion of the MLE cost function, combined with the best linear unbiased estimator, to obtain a method which does not require such a search. The computational complexity of the new method is evaluated. Numerical simulations demonstrate that the new method approaches the corresponding Cramér‐Rao bound for a wide range of signal‐to‐noise ratios, and has superior performance compared to all other existing methods for approximating the solution for the joint MLE, while maintaining a low computational complexity. Copyright © 2015 John Wiley & Sons, Ltd.

Epilepsy is one of the most common neurological disorders affecting about 1% of the world population. For patients with focal seizures that cannot be treated with antiepileptic drugs, the common treatment is a surgical procedure for removal of the seizure onset zone (SOZ). In this work we introduce an algorithm for automatic localization of the seizure onset zone (SOZ) in epileptic patients based on electrocorticography (ECoG) recordings. The proposed algorithm builds upon the hypothesis that the abnormal excessive (or synchronous) neuronal activity in the brain leading to seizures starts in the SOZ and then spreads to other areas in the brain. Thus, when this abnormal activity starts, signals recorded at electrodes close to the SOZ should have a relatively large causal influence on the rest of the recorded signals. The SOZ localization is executed in two steps. First, the algorithm represents the set of electrodes using a directed graph in which nodes correspond to recording electrodes and the edges’ weights quantify the pair-wise causal influence between the recorded signals. Then, the algorithm infers the SOZ from the estimated graph using a variant of the PageRank algorithm followed by a novel post-processing phase. Inference results for 19 patients show a close match between the SOZ inferred by the proposed approach and the SOZ estimated by expert neurologists (success rate of 17 out of 19).

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Reliable transmission of arbitrarily correlated sources over multiple-access relay channels (MARCs) and multiple-access broadcast relay channels (MABRCs) is considered. In MARCs, only the destination is interested in a reconstruction of the sources, while in MABRCs, both the relay and the destination want to reconstruct the sources. We allow an arbitrary correlation among the sources at the transmitters, and let both the relay and the destination have side information that are correlated with the sources. Two joint source-channel coding schemes are presented and the corresponding sets of sufficient conditions for reliable communication are derived. The proposed schemes use a combination of the correlation preserving mapping (CPM) technique with Slepian-Wolf (SW) source coding: the first scheme uses CPM for encoding information to the relay and SW source coding for encoding information to the destination; while the second scheme uses SW source coding for encoding information to the relay and CPM for encoding information to the destination. I. INTRODUCTIONThe multiple-access relay channel (MARC) models a network in which several users communicate with a single destination, with the help of a relay [1]. Examples of such a network include sensor and ad-hoc networks in which an intermediate relay node is introduced to assist the communication from the source terminals to the destination. The MARC is a fundamental multi-terminal channel model that generalizes both the multiple-access channel (MAC) and the relay channel models, and has received a lot of attention in the recent years. If the relay terminal is also required to decode the source messages, the model is called the multiple-access broadcast relay channel (MABRC).While in [1],[2] MARCs with independent sources at the terminals are considered, in [3], [4] we allow arbitrary correlation among the sources to be transmitted to the destination in a lossless fashion. We also let the relay and the destination have side information that are correlated with the two sources. In [3] we address the problem of determining whether a pair of sources can be losslessly transmitted to the destination with a given number of channel uses per source sample, using statistically independent source code and channel code.In [5] Shannon showed that a source can be reliably transmitted over a memoryless point-to-point (PtP) channel, if and only if its entropy is less than the channel capacity. Hence,

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Abstract-We study linear encoding for a pair of correlated Gaussian sources transmitted over a two-user Gaussian broadcast channel in the presence of unit-delay noiseless feedback, abbreviated as the GBCF. Each pair of source samples is transmitted using a linear transmission scheme in a finite number of channel uses. We investigate three linear transmission schemes: A scheme based on the Ozarow-Leung (OL) code, a scheme based on the linear quadratic Gaussian (LQG) code of Ardestanizadeh et al., and a novel scheme derived in this work using a dynamic programming (DP) approach. For the OL and LQG schemes we present lower and upper bounds on the minimal number of channel uses needed to achieve a target mean-square error (MSE) pair. For the LQG scheme in the symmetric setting, we identify the optimal scaling of the sources, which results in a significant improvement of its finite horizon performance, and, in addition, characterize the (exact) minimal number of channel uses required to achieve a target MSE. Finally, for the symmetric setting, we show that for any fixed and finite number of channel uses, the DP scheme achieves an MSE lower than the MSE achieved by either the LQG or the OL schemes.