95,847 research outputs found
Non-linear signal detection for molecular communications
Molecular communications convey information via diffusion propagation. The inherent long-tail channel response causes severe inter-symbol interference, which may seriously degrade signal detection performances. Traditional linear signal detection techniques, unfortunately, require both high complexity and a high signal-to-noise (SNR) ratio to operate. In this paper, we proposed a new non-linear signal processing paradigm inspired by the biological systems that achieves low-complexity signal detection even in low SNR regimes. First, we introduce a stochastic resonance inspired non-linear filtering scheme for molecular communications, and show that it significantly improves the output SNR by transforming the noise energy into useful signals. Second, we design a novel non-coherent detector by exploiting the transient features of molecular signaling, which are independent of channel response and involves only lowcomplexity linear summation operations. Numerical simulations show that this new scheme can improve the detection performance remarkably (approx. 7dB gain), even when compared against linearly optimal coherent methods. This is one of the first attempts to demodulate molecular signals from an entirely biological point of view, and the designed non-linear noncoherent paradigm will provide significant potential to the design and future implementation of nano-systems in noisy biological environments
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
Non-coherent detection for ultraviolet communications with inter-symbol interference
Ultraviolet communication (UVC) serves as a promising supplement to share the responsibility for the overloads in conventional wireless communication systems. One challenge for UVC lies in inter-symbol-interference (ISI), which combined with the ambient noise, contaminates the received signals and thereby deteriorates the communication accuracy. Existing coherent signal detection schemes (e.g. maximum likelihood sequence detection, MLSD) require channel state information (CSI) to compensate the channel ISI effect, thereby falling into either a long overhead and large computational complexity, or poor CSI acquisition that further hinders the detection performance. Non-coherent schemes for UVC, although capable of reducing the complexity, cannot provide high detection accuracy in the face of ISI. In this work, we propose a novel non-coherent paradigm via the exploration of the UV signal features that are insensitive to the ISI. By optimally weighting and combining the extracted features to minimize the bit error rate (BER), the optimally-weighted non-coherent detection (OWNCD) is proposed, which converts the signal detection with ISI into a binary detection framework with a heuristic decision threshold. As such, the proposed OWNCD avoids the complex CSI estimation and guarantees the detection accuracy. Compared to the state-of-the-art MLSD in the cases of static and time-varying CSI, the proposed OWNCD can gain âŒ1 dB and 8 dB in signal-to-noise-ratio (SNR) at the 7% overhead FEC limit (BER of 4.5Ă10 â3 , respectively, and can also reduce the computational complexity by 4 order of magnitud
Laser diagnostics and minor species detection in combustion using resonant four-wave mixing
Peer reviewedPostprin
On negative higher-order Kerr effect and filamentation
As a contribution to the ongoing controversy about the role of higher-order
Kerr effect (HOKE) in laser filamentation, we first provide thorough details
about the protocol that has been employed to infer the HOKE indices from the
experiment. Next, we discuss potential sources of artifact in the experimental
measurements of these terms and show that neither the value of the observed
birefringence, nor its inversion, nor the intensity at which it is observed,
appear to be flawed. Furthermore, we argue that, independently on our values,
the principle of including HOKE is straightforward. Due to the different
temporal and spectral dynamics, the respective efficiency of defocusing by the
plasma and by the HOKE is expected to depend substantially on both incident
wavelength and pulse duration. The discussion should therefore focus on
defining the conditions where each filamentation regime dominates.Comment: 22 pages, 11 figures. Submitted to Laser physics as proceedings of
the Laser Physics 2010 conferenc
Optimal Detection for Diffusion-Based Molecular Timing Channels
This work studies optimal detection for communication over diffusion-based
molecular timing (DBMT) channels. The transmitter simultaneously releases
multiple information particles, where the information is encoded in the time of
release. The receiver decodes the transmitted information based on the random
time of arrival of the information particles, which is modeled as an additive
noise channel. For a DBMT channel without flow, this noise follows the L\'evy
distribution. Under this channel model, the maximum-likelihood (ML) detector is
derived and shown to have high computational complexity. It is also shown that
under ML detection, releasing multiple particles improves performance, while
for any additive channel with -stable noise where (such as
the DBMT channel), under linear processing at the receiver, releasing multiple
particles degrades performance relative to releasing a single particle. Hence,
a new low-complexity detector, which is based on the first arrival (FA) among
all the transmitted particles, is proposed. It is shown that for a small number
of released particles, the performance of the FA detector is very close to that
of the ML detector. On the other hand, error exponent analysis shows that the
performance of the two detectors differ when the number of released particles
is large.Comment: 16 pages, 9 figures. Submitted for publicatio
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
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