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

High-dimensional metric combining for non-coherent molecular signal detection

In emerging Internet-of-Nano-Thing (IoNT), information will be embedded and conveyed in the form of molecules through complex and diffusive medias. One main challenge lies in the long-tail nature of the channel response causing inter-symbolinterference (ISI), which deteriorates the detection performance. If the channel is unknown, existing coherent schemes (e.g., the state-of-the-art maximum a posteriori, MAP) have to pursue complex channel estimation and ISI mitigation techniques, which will result in either high computational complexity, or poor estimation accuracy that will hinder the detection performance. In this paper, we develop a novel high-dimensional non-coherent detection scheme for molecular signals. We achieve this in a higher-dimensional metric space by combining different noncoherent metrics that exploit the transient features of the signals. By deducing the theoretical bit error rate (BER) for any constructed high-dimensional non-coherent metric, we prove that, higher dimensionality always achieves a lower BER in the same sample space, at the expense of higher complexity on computing the multivariate posterior densities. The realization of this high-dimensional non-coherent scheme is resorting to the Parzen window technique based probabilistic neural network (Parzen-PNN), given its ability to approximate the multivariate posterior densities by taking the previous detection results into a channel-independent Gaussian Parzen window, thereby avoiding the complex channel estimations. The complexity of the posterior computation is shared by the parallel implementation of the Parzen-PNN. Numerical simulations demonstrate that our proposed scheme can gain 10dB in SNR given a fixed BER as 10-4, in comparison with other state-of-the-art methods

Local convexity inspired low-complexity non-coherent signal detector for nano-scale molecular communications

Molecular communications via diffusion (MCvD) represents a relatively new area of wireless data transfer with especially attractive characteristics for nanoscale applications. Due to the nature of diffusive propagation, one of the key challenges is to mitigate inter-symbol interference (ISI) that results from the long tail of channel response. Traditional coherent detectors rely on accurate channel estimations and incur a high computational complexity. Both of these constraints make coherent detection unrealistic for MCvD systems. In this paper, we propose a low-complexity and noncoherent signal detector, which exploits essentially the local convexity of the diffusive channel response. A threshold estimation mechanism is proposed to detect signals blindly, which can also adapt to channel variations. Compared to other noncoherent detectors, the proposed algorithm is capable of operating at high data rates and suppressing ISI from a large number of previous symbols. Numerical results demonstrate that not only is the ISI effectively suppressed, but the complexity is also reduced by only requiring summation operations. As a result, the proposed noncoherent scheme will provide the necessary potential to low-complexity molecular communications, especially for nanoscale applications with a limited computation and energy budget

Electron-doping evolution of the low-energy spin excitations in the iron arsenide BaFe2−x_{2-x}Nix_{x}As2_{2} superconductors

We use elastic and inelastic neutron scattering to systematically investigate the evolution of the low-energy spin excitations of the iron arsenide superconductor BaFe2-xNixAs2 as a function of nickel doping x. In the undoped state, BaFe2As2 exhibits a tetragonal-to-orthorhombic structural phase transition and simultaneously develops a collinear antiferromagnetic (AF) order below TN = 143 K. Upon electron-doping of x = 0.075 to induce bulk superconductivity with Tc = 12.3 K, the AF ordering temperature reduces to TN = 58 K.We show that the appearance of bulk superconductivity in BaFe1.925Ni0.075As2 coincides with a dispersive neutron spin resonance in the spin excitation spectra, and a reduction in the static ordered moment. For optimally doped BaFe1.9Ni0.1As2 (Tc = 20 K) and overdoped BaFe1.85Ni0.15As2 (Tc = 15 K) superconductors, the static AF long-range order is completely suppressed and the spin excitation spectra are dominated by a resonance and spin-gap at lower energies. We determine the electron-doping dependence of the neutron spin resonance and spin gap energies, and demonstrate that the three-dimensional nature of the resonance survives into the overdoped regime. If spin excitations are important for superconductivity, these results would suggest that the three-dimensional character of the electronic superconducting gaps are prevalent throughout the phase diagram, and may be critical for superconductivity in these materials

Asynchronous device detection for cognitive device-to-device communications

Dynamic spectrum sharing will facilitate the interference coordination in device-to-device (D2D) communications. In the absence of network level coordination, the timing synchronization among D2D users will be unavailable, leading to inaccurate channel state estimation and device detection, especially in time-varying fading environments. In this study, we design an asynchronous device detection/discovery framework for cognitive-D2D applications, which acquires timing drifts and dynamical fading channels when directly detecting the existence of a proximity D2D device (e.g. or primary user). To model and analyze this, a new dynamical system model is established, where the unknown timing deviation follows a random process, while the fading channel is governed by a discrete state Markov chain. To cope with the mixed estimation and detection (MED) problem, a novel sequential estimation scheme is proposed, using the conceptions of statistic Bayesian inference and random finite set. By tracking the unknown states (i.e. varying time deviations and fading gains) and suppressing the link uncertainty, the proposed scheme can effectively enhance the detection performance. The general framework, as a complimentary to a network-aided case with the coordinated signaling, provides the foundation for development of flexible D2D communications along with proximity-based spectrum sharing

Bacterial relay for energy efficient molecular communications

In multi-cellular organisms, molecular signaling spans multiple distance scales and is essential to tissue structure and functionality. Molecular communications is increasingly researched and developed as a key subsystem in the Internet-of-Nano-Things paradigm. While short range microscopic diffusion communications is well understood, longer range channels can be inefficient and unreliable. Static and mobile relays have been proposed in both conventional wireless systems and molecular communication contexts. In this paper, our main contribution is to analyze the information delivery energy efficiency of bacteria mobile relays. We discover that these mobile relays offer superior energy efficiency compared with pure diffusion information transfer over long diffusion distances. This paper has widespread implications ranging from understanding biological processes to designing new efficient synthetic biology communication systems

Low-complexity non-coherent signal detection for nano-scale molecular communications

Nano-scale molecular communication is a viable way of exchanging information between nano-machines. In this letter, a low-complexity and non-coherent signal detection technique is proposed to mitigate the intersymbol-interference (ISI) and additive noise. In contrast to existing coherent detection methods of high complexity, the proposed non-coherent signal detector is more practical when the channel conditions are hard to acquire accurately or hidden from the receiver. The proposed scheme employs the concentration difference to detect the ISI corrupted signals and we demonstrate that it can suppress the ISI effectively. The concentration difference is a stable characteristic, irrespective of the diffusion channel conditions. In terms of complexity, by excluding matrix operations or likelihood calculations, the new detection scheme is particularly suitable for nano-scale molecular communication systems with a small energy budget or limited computation resource

Neutron spin resonance as a probe of superconducting gap anisotropy in partially detwinned electron underdoped NaFe0.985_{0.985}Co0.015_{0.015}As

We use inelastic neutron scattering (INS) to study the spin excitations in partially detwinned NaFe$_{0.985}$Co$_{0.015}$As which has coexisting static antiferromagnetic (AF) order and superconductivity ($T_c=15$ K, $T_N=30$ K). In previous INS work on a twinned sample, spin excitations form a dispersive sharp resonance near $E_{r1}=3.25$ meV and a broad dispersionless mode at $E_{r1}=6$ meV at the AF ordering wave vector ${\bf Q}_{\rm AF}={\bf Q}_1=(1,0)$ and its twinned domain ${\bf Q}_2=(0,1)$. For partially detwinned NaFe$_{0.985}$Co$_{0.015}$As with the static AF order mostly occurring at ${\bf Q}_{\rm AF}=(1,0)$, we still find a double resonance at both wave vectors with similar intensity. Since ${\bf Q}_1=(1,0)$ characterizes the explicit breaking of the spin rotational symmetry associated with the AF order, these results indicate that the double resonance cannot be due to the static and fluctuating AF orders, but originate from the superconducting gap anisotropy.Comment: 5 pages, 5 figures; PRB, 2015 (the correct final version is now used