19,792 research outputs found
Distance estimation schemes for diffusion based molecular communication systems
Molecule concentration is often used as the information carrier to accomplish diffusion-based molecular communications (DMC) among nano-machines. To achieve the optimal functionality, knowing the distance between the transmitter nano-machine (TN) and the receiver nano-machine (RN) is of high importance. In this paper, two distance estimation schemes are proposed based upon the RN-sensed concentration which changes with regards to the time and distance. The RN estimates the distance by means of measuring either the concentration-peak time or received concentration energy. Simulations are performed to compare the accuracy of each scheme and to discover how the diffusion channel and noise may influence the accuracy. Results show that both schemes will provide a beneficial enhancement to molecular communication systems
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 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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