29,611 research outputs found
Optimal Receiver Design for Diffusive Molecular Communication With Flow and Additive Noise
In this paper, we perform receiver design for a diffusive molecular
communication environment. Our model includes flow in any direction, sources of
information molecules in addition to the transmitter, and enzymes in the
propagation environment to mitigate intersymbol interference. We characterize
the mutual information between receiver observations to show how often
independent observations can be made. We derive the maximum likelihood sequence
detector to provide a lower bound on the bit error probability. We propose the
family of weighted sum detectors for more practical implementation and derive
their expected bit error probability. Under certain conditions, the performance
of the optimal weighted sum detector is shown to be equivalent to a matched
filter. Receiver simulation results show the tradeoff in detector complexity
versus achievable bit error probability, and that a slow flow in any direction
can improve the performance of a weighted sum detector.Comment: 14 pages, 7 figures, 1 appendix. To appear in IEEE Transactions on
NanoBioscience (submitted July 31, 2013, revised June 18, 2014, accepted July
7, 2014
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
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