776 research outputs found
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
Capacity of Molecular Channels with Imperfect Particle-Intensity Modulation and Detection
This work introduces the particle-intensity channel (PIC) as a model for
molecular communication systems and characterizes the properties of the optimal
input distribution and the capacity limits for this system. In the PIC, the
transmitter encodes information, in symbols of a given duration, based on the
number of particles released, and the receiver detects and decodes the message
based on the number of particles detected during the symbol interval. In this
channel, the transmitter may be unable to control precisely the number of
particles released, and the receiver may not detect all the particles that
arrive. We demonstrate that the optimal input distribution for this channel
always has mass points at zero and the maximum number of particles that can be
released. We then consider diffusive particle transport, derive the capacity
expression when the input distribution is binary, and show conditions under
which the binary input is capacity-achieving. In particular, we demonstrate
that when the transmitter cannot generate particles at a high rate, the optimal
input distribution is binary.Comment: Accepted at IEEE International Symposium on Information Theory (ISIT
Adaptive Molecule Transmission Rate for Diffusion Based Molecular Communication
In this paper, a simple memory limited transmitter for molecular
communication is proposed, in which information is encoded in the diffusion
rate of the molecules. Taking advantage of memory, the proposed transmitter
reduces the ISI problem by properly adjusting its diffusion rate. The error
probability of the proposed scheme is derived and the result is compared with
the lower bound on error probability of the optimum transmitter. It is shown
that the performance of introduced transmitter is near optimal (under certain
simplifications). Simplicity is the key feature of the presented communication
system: the transmitter follows a simple rule, the receiver is a simple
threshold decoder and only one type of molecule is used to convey the
information
A Survey on Modulation Techniques in Molecular Communication via Diffusion
This survey paper focuses on modulation aspects of molecular communication,
an emerging field focused on building biologically-inspired systems that embed
data within chemical signals. The primary challenges in designing these systems
are how to encode and modulate information onto chemical signals, and how to
design a receiver that can detect and decode the information from the corrupted
chemical signal observed at the destination. In this paper, we focus on
modulation design for molecular communication via diffusion systems. In these
systems, chemical signals are transported using diffusion, possibly assisted by
flow, from the transmitter to the receiver. This tutorial presents recent
advancements in modulation and demodulation schemes for molecular communication
via diffusion. We compare five different modulation types: concentration-based,
type-based, timing-based, spatial, and higher-order modulation techniques. The
end-to-end system designs for each modulation scheme are presented. In
addition, the key metrics used in the literature to evaluate the performance of
these techniques are also presented. Finally, we provide a numerical bit error
rate comparison of prominent modulation techniques using analytical models. We
close the tutorial with a discussion of key open issues and future research
directions for design of molecular communication via diffusion systems.Comment: Preprint of the accepted manuscript for publication in IEEE Surveys
and Tutorial
Capacities and Optimal Input Distributions for Particle-Intensity Channels
This work introduces the particle-intensity channel (PIC) as a model for
molecular communication systems and characterizes the capacity limits as well
as properties of the optimal (capacity-achieving) input distributions for such
channels. In the PIC, the transmitter encodes information, in symbols of a
given duration, based on the probability of particle release, and the receiver
detects and decodes the message based on the number of particles detected
during the symbol interval. In this channel, the transmitter may be unable to
control precisely the probability of particle release, and the receiver may not
detect all the particles that arrive. We model this channel using a
generalization of the binomial channel and show that the capacity-achieving
input distribution for this channel always has mass points at probabilities of
particle release of zero and one. To find the capacity-achieving input
distributions, we develop an efficient algorithm we call dynamic assignment
Blahut-Arimoto (DAB). For diffusive particle transport, we also derive the
conditions under which the input with two mass points is capacity-achieving.Comment: arXiv admin note: text overlap with arXiv:1705.0804
The Bit Error Performance and Information Transfer Rate of SPAD Array Optical Receivers
In this paper the photon counting characteristics, the information rate and the bit error performance of single-photon avalanche diode (SPAD) arrays are investigated. It is shown that for sufficiently large arrays, the photocount distribution is well approximated by a Gaussian distribution with dead-time-dependent mean and variance. Because of dead time, the SPAD array channel is subject to counting losses, part of which are due to inter-slot interference (ISI) distortions. Consequently, this channel has memory. The information rate of this channel is assessed. Two auxiliary discrete memoryless channels (DMCs) are proposed which provide upper and lower bounds on the SPAD array information rate. It is shown that in sufficiently large arrays, ISI is negligible and the bounds are tight. Under such conditions, the SPAD array channel is precisely modelled as a memoryless channel. A discrete-time Gaussian channel with input-dependent mean and variance is adopted and the properties of the capacity-achieving input distributions are studied. Using a numerical algorithm, the information rate and the capacity-achieving input distributions, subject to peak and average power constraints are obtained. Furthermore, the bit error performance of a SPAD-based system with on-off keying (OOK) is evaluated for various array sizes, dead times and background count levels
Identification Capacity of the Discrete-Time Poisson Channel
Numerous applications in the field of molecular communications (MC) such as
healthcare systems are often event-driven. The conventional Shannon capacity
may not be the appropriate metric for assessing performance in such cases. We
propose the identification (ID) capacity as an alternative metric.
Particularly, we consider randomized identification (RI) over the discrete-time
Poisson channel (DTPC), which is typically used as a model for MC systems that
utilize molecule-counting receivers. In the ID paradigm, the receiver's focus
is not on decoding the message sent. However, he wants to determine whether a
message of particular significance to him has been sent or not. In contrast to
Shannon transmission codes, the size of ID codes for a Discrete Memoryless
Channel (DMC) grows doubly exponentially fast with the blocklength, if
randomized encoding is used. In this paper, we derive the capacity formula for
RI over the DTPC subject to some peak and average power constraints.
Furthermore, we analyze the case of state-dependent DTPC
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