1,705 research outputs found
Diffusive Molecular Communications with Reactive Signaling
This paper focuses on molecular communication (MC) systems where the
signaling molecules may participate in a reversible bimolecular reaction in the
channel. The motivation for studying these MC systems is that they can realize
the concept of constructive and destructive signal superposition, which leads
to favorable properties such as inter-symbol interference (ISI) reduction and
avoiding environmental contamination due to continuous release of molecules
into the channel. This work first derives the maximum likelihood (ML) detector
for a binary MC system with reactive signaling molecules under the assumption
that the detector has perfect knowledge of the ISI. The performance of this
genie-aided ML detector yields an upper bound on the performance of any
practical detector. In addition, two suboptimal detectors of different
complexity are proposed. The proposed ML detector as well as one of the
suboptimal detectors require the channel response (CR) of the considered MC
system. Moreover, the CR is needed for the performance evaluation of all
proposed detectors. However, analyzing MC with reactive signaling is
challenging since the underlying partial differential equations that describe
the reaction-diffusion mechanism are coupled and non-linear. Therefore, an
algorithm is developed in this paper for efficient computation of the CR to any
arbitrary transmit symbol sequence. The accuracy of this algorithm is validated
via particle-based simulation. Simulation results using the developed CR
algorithm show that the performance of the proposed suboptimal detectors can
approach that of the genie- aided ML detector. Moreover, these results show
that MC systems with reactive signaling have superior performance relative to
those with non-reactive signaling due to the reduction of ISI enabled by the
chemical reactions.Comment: This paper has been submitted to IEEE International Conference on
Communications (ICC) 201
Diffusive Mobile Molecular Communications Over Time-Variant Channels
This letter introduces a formalism for modeling time-variant channels for
diffusive molecular communication systems. In particular, we consider a fluid
environment where one transmitter nano-machine and one receiver nano-machine
are subjected to Brownian motion in addition to the diffusive motion of the
information molecules used for communication. Due to the stochastic movements
of the transmitter and receiver nano-machines, the statistics of the channel
impulse response change over time. We show that the time-variant behaviour of
the channel can be accurately captured by appropriately modifying the diffusion
coefficient of the information molecules. Furthermore, we derive an analytical
expression for evaluation of the expected error probability of a simple
detector for the considered system. The accuracy of the proposed analytical
expression is verified via particle-based simulation of the Brownian motion.Comment: 4 pages, 3 figures, 1 table. Accepted for publication in IEEE
Communications Letters (Author's comment: Manuscript submitted Jan. 19, 2017;
revised Feb. 20, 2017; accepted Feb. 22, 2017
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 modeling for diffusive molecular communication - a tutorial review
Molecular communication (MC) is a new communication engineering paradigm where molecules are employed as information carriers. MC systems are expected to enable new revolutionary applications such as sensing of target substances in biotechnology, smart drug delivery in medicine, and monitoring of oil pipelines or chemical reactors in industrial settings. As for any other kind of communication, simple yet sufficiently accurate channel models are needed for the design, analysis, and efficient operation of MC systems. In this paper, we provide a tutorial review on mathematical channel modeling for diffusive MC systems. The considered end-to-end MC channel models incorporate the effects of the release mechanism, the MC environment, and the reception mechanism on the observed information molecules. Thereby, the various existing models for the different components of an MC system are presented under a common framework and the underlying biological, chemical, and physical phenomena are discussed. Deterministic models characterizing the expected number of molecules observed at the receiver and statistical models characterizing the actual number of observed molecules are developed. In addition, we provide channel models for timevarying MC systems with moving transmitters and receivers, which are relevant for advanced applications such as smart drug delivery with mobile nanomachines. For complex scenarios, where simple MC channel models cannot be obtained from first principles, we investigate simulation-driven and experiment-driven channel models. Finally, we provide a detailed discussion of potential challenges, open research problems, and future directions in channel modeling for diffusive MC systems
Symbol Synchronization for Diffusive Molecular Communication Systems
Symbol synchronization refers to the estimation of the start of a symbol
interval and is needed for reliable detection. In this paper, we develop a
symbol synchronization framework for molecular communication (MC) systems where
we consider some practical challenges which have not been addressed in the
literature yet. In particular, we take into account that in MC systems, the
transmitter may not be equipped with an internal clock and may not be able to
emit molecules with a fixed release frequency. Such restrictions hold for
practical nanotransmitters, e.g. modified cells, where the lengths of the
symbol intervals may vary due to the inherent randomness in the availability of
food and energy for molecule generation, the process for molecule production,
and the release process. To address this issue, we propose to employ two types
of molecules, one for synchronization and one for data transmission. We derive
the optimal maximum likelihood (ML) symbol synchronization scheme as a
performance upper bound. Since ML synchronization entails high complexity, we
also propose two low-complexity synchronization schemes, namely a peak
observation-based scheme and a threshold-trigger scheme, which are suitable for
MC systems with limited computational capabilities. Our simulation results
reveal the effectiveness of the proposed synchronization~schemes and suggest
that the end-to-end performance of MC systems significantly depends on the
accuracy of symbol synchronization.Comment: This paper has been accepted for presentation at IEEE International
Conference on Communications (ICC) 201
Channel Modeling for Diffusive Molecular Communication - A Tutorial Review
Molecular communication (MC) is a new communication engineering paradigm
where molecules are employed as information carriers. MC systems are expected
to enable new revolutionary applications such as sensing of target substances
in biotechnology, smart drug delivery in medicine, and monitoring of oil
pipelines or chemical reactors in industrial settings. As for any other kind of
communication, simple yet sufficiently accurate channel models are needed for
the design, analysis, and efficient operation of MC systems. In this paper, we
provide a tutorial review on mathematical channel modeling for diffusive MC
systems. The considered end-to-end MC channel models incorporate the effects of
the release mechanism, the MC environment, and the reception mechanism on the
observed information molecules. Thereby, the various existing models for the
different components of an MC system are presented under a common framework and
the underlying biological, chemical, and physical phenomena are discussed.
Deterministic models characterizing the expected number of molecules observed
at the receiver and statistical models characterizing the actual number of
observed molecules are developed. In addition, we provide channel models for
time-varying MC systems with moving transmitters and receivers, which are
relevant for advanced applications such as smart drug delivery with mobile
nanomachines. For complex scenarios, where simple MC channel models cannot be
obtained from first principles, we investigate simulation-driven and
experimentally-driven channel models. Finally, we provide a detailed discussion
of potential challenges, open research problems, and future directions in
channel modeling for diffusive MC systems.Comment: 40 pages; 23 figures, 2 tables; this paper is submitted to the
Proceedings of IEE
Channel Estimation for Diffusive Molecular Communications
In molecular communication (MC) systems, the \textit{expected} number of
molecules observed at the receiver over time after the instantaneous release of
molecules by the transmitter is referred to as the channel impulse response
(CIR). Knowledge of the CIR is needed for the design of detection and
equalization schemes. In this paper, we present a training-based CIR estimation
framework for MC systems which aims at estimating the CIR based on the
\textit{observed} number of molecules at the receiver due to emission of a
\textit{sequence} of known numbers of molecules by the transmitter. Thereby, we
distinguish two scenarios depending on whether or not statistical channel
knowledge is available. In particular, we derive maximum likelihood (ML) and
least sum of square errors (LSSE) estimators which do not require any knowledge
of the channel statistics. For the case, when statistical channel knowledge is
available, the corresponding maximum a posteriori (MAP) and linear minimum mean
square error (LMMSE) estimators are provided. As performance bound, we derive
the classical Cramer Rao (CR) lower bound, valid for any unbiased estimator,
which does not exploit statistical channel knowledge, and the Bayesian CR lower
bound, valid for any unbiased estimator, which exploits statistical channel
knowledge. Finally, we propose optimal and suboptimal training sequence designs
for the considered MC system. Simulation results confirm the analysis and
compare the performance of the proposed estimation techniques with the
respective CR lower bounds.Comment: to be appeared in IEEE Transactions on Communications. arXiv admin
note: text overlap with arXiv:1510.0861
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