15,640 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
Diffusive MIMO Molecular Communications: Channel Estimation, Equalization and Detection
In diffusion-based communication, as for molecular systems, the achievable
data rate is low due to the stochastic nature of diffusion which exhibits a
severe inter-symbol-interference (ISI). Multiple-Input Multiple-Output (MIMO)
multiplexing improves the data rate at the expense of an inter-link
interference (ILI). This paper investigates training-based channel estimation
schemes for diffusive MIMO (D-MIMO) systems and corresponding equalization
methods. Maximum likelihood and least-squares estimators of mean channel are
derived, and the training sequence is designed to minimize the mean square
error (MSE). Numerical validations in terms of MSE are compared with Cramer-Rao
bound derived herein. Equalization is based on decision feedback equalizer
(DFE) structure as this is effective in mitigating diffusive ISI/ILI.
Zero-forcing, minimum MSE and least-squares criteria have been paired to DFE,
and their performances are evaluated in terms of bit error probability. Since
D-MIMO systems are severely affected by the ILI because of short transmitters
inter-distance, D-MIMO time interleaving is exploited as countermeasure to
mitigate the ILI with remarkable performance improvements. The feasibility of a
block-type communication including training and data equalization is explored
for D-MIMO, and system-level performances are numerically derived.Comment: Accepted paper at IEEE transaction on Communicatio
Channel Estimation for Diffusive MIMO Molecular Communications
In diffusion-based communication, as for molecular systems, the achievable
data rate is very low due to the slow nature of diffusion and the existence of
severe inter-symbol interference (ISI). Multiple-input multiple-output (MIMO)
technique can be used to improve the data rate. Knowledge of channel impulse
response (CIR) is essential for equalization and detection in MIMO systems.
This paper presents a training-based CIR estimation for diffusive MIMO (D-MIMO)
channels. Maximum likelihood and least-squares estimators are derived, and the
training sequences are designed to minimize the corresponding Cram\'er-Rao
bound. Sub-optimal estimators are compared to Cram\'er-Rao bound to validate
their performance.Comment: 5 pages, 5 figures, EuCNC 201
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
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Proliferation tracing with single-cell mass cytometry optimizes generation of stem cell memory-like T cells.
Selective differentiation of naive T cells into multipotent T cells is of great interest clinically for the generation of cell-based cancer immunotherapies. Cellular differentiation depends crucially on division state and time. Here we adapt a dye dilution assay for tracking cell proliferative history through mass cytometry and uncouple division, time and regulatory protein expression in single naive human T cells during their activation and expansion in a complex ex vivo milieu. Using 23 markers, we defined groups of proteins controlled predominantly by division state or time and found that undivided cells account for the majority of phenotypic diversity. We next built a map of cell state changes during naive T-cell expansion. By examining cell signaling on this map, we rationally selected ibrutinib, a BTK and ITK inhibitor, and administered it before T cell activation to direct differentiation toward a T stem cell memory (TSCM)-like phenotype. This method for tracing cell fate across division states and time can be broadly applied for directing cellular differentiation
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