8,534 research outputs found
Molecular communication in fluid media: The additive inverse Gaussian noise channel
We consider molecular communication, with information conveyed in the time of
release of molecules. The main contribution of this paper is the development of
a theoretical foundation for such a communication system. Specifically, we
develop the additive inverse Gaussian (IG) noise channel model: a channel in
which the information is corrupted by noise with an inverse Gaussian
distribution. We show that such a channel model is appropriate for molecular
communication in fluid media - when propagation between transmitter and
receiver is governed by Brownian motion and when there is positive drift from
transmitter to receiver. Taking advantage of the available literature on the IG
distribution, upper and lower bounds on channel capacity are developed, and a
maximum likelihood receiver is derived. Theory and simulation results are
presented which show that such a channel does not have a single quality measure
analogous to signal-to-noise ratio in the AWGN channel. It is also shown that
the use of multiple molecules leads to reduced error rate in a manner akin to
diversity order in wireless communications. Finally, we discuss some open
problems in molecular communications that arise from the IG system model.Comment: 28 pages, 8 figures. Submitted to IEEE Transactions on Information
Theory. Corrects minor typos in the first versio
Bounds on the Capacity of ASK Molecular Communication Channels with ISI
There are now several works on the use of the additive inverse Gaussian noise
(AIGN) model for the random transit time in molecular communication~(MC)
channels. The randomness invariably causes inter-symbol interference (ISI) in
MC, an issue largely ignored or simplified. In this paper we derive an upper
bound and two lower bounds for MC based on amplitude shift keying (ASK) in
presence of ISI. The Blahut-Arimoto algorithm~(BAA) is modified to find the
input distribution of transmitted symbols to maximize the lower bounds. Our
results show that over wide parameter values the bounds are close.Comment: 7 pages, 4 figures, Accepted in IEEE GLOBECOM 201
Information Rates of ASK-Based Molecular Communication in Fluid Media
This paper studies the capacity of molecular communications in fluid media,
where the information is encoded in the number of transmitted molecules in a
time-slot (amplitude shift keying). The propagation of molecules is governed by
random Brownian motion and the communication is in general subject to
inter-symbol interference (ISI). We first consider the case where ISI is
negligible and analyze the capacity and the capacity per unit cost of the
resulting discrete memoryless molecular channel and the effect of possible
practical constraints, such as limitations on peak and/or average number of
transmitted molecules per transmission. In the case with a constrained peak
molecular emission, we show that as the time-slot duration increases, the input
distribution achieving the capacity per channel use transitions from binary
inputs to a discrete uniform distribution. In this paper, we also analyze the
impact of ISI. Crucially, we account for the correlation that ISI induces
between channel output symbols. We derive an upper bound and two lower bounds
on the capacity in this setting. Using the input distribution obtained by an
extended Blahut-Arimoto algorithm, we maximize the lower bounds. Our results
show that, over a wide range of parameter values, the bounds are close.Comment: 31 pages, 8 figures, Accepted for publication on IEEE Transactions on
Molecular, Biological, and Multi-Scale Communication
Nonlinear limits to the information capacity of optical fiber communications
The exponential growth in the rate at which information can be communicated
through an optical fiber is a key element in the so called information
revolution. However, like all exponential growth laws, there are physical
limits to be considered. The nonlinear nature of the propagation of light in
optical fiber has made these limits difficult to elucidate. Here we obtain
basic insights into the limits to the information capacity of an optical fiber
arising from these nonlinearities. The key simplification lies in relating the
nonlinear channel to a linear channel with multiplicative noise, for which we
are able to obtain analytical results. In fundamental distinction to the linear
additive noise case, the capacity does not grow indefinitely with increasing
signal power, but has a maximal value. The ideas presented here have broader
implications for other nonlinear information channels, such as those involved
in sensory transduction in neurobiology. These have been often examined using
additive noise linear channel models, and as we show here, nonlinearities can
change the picture qualitatively.Comment: 1 figure, 7 pages, submitted to Natur
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