Dynamic pixel selection in free-space photon-counting optical communication systems for the exploitation of excess channel capacity

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Includes bibliographical references (p. 111-112).Atmospheric turbulence in free-space optical communications turns signal demodulation and decoding into a multimode problem as wavefronts of the transmitting laser beams are warped spatially past the desired form of a diffraction-limited spot at the receiver end of a free-space optical receiver. Adaptive optics, a traditional solution to this problem, is computationally expensive and adds complexity to receiver architecture by requiring tools like wavefront sensors and deformable mirrors. Due to the enabling technology of Geiger-mode avalanche photodiode (GM-APD) arrays, a simple algorithm that only requires information from the GM-APD array to implement the technique of dynamic pixel selection can be realized entirely in software or firmware. Dynamic pixel selection exploits the temporal and spatial information attached to each received photon by filtering out noisy or otherwise undesirable portions of the array in order to exploit any excess channel capacity in the link to allow on-the-fly adjustments of data rates. Preliminary results, specific to the MIT Lincoln Laboratory photon-counting, free-space optical communication system, which utilizes an 8 x 8 GM-APD receiver array, operates at a 1.06pm wavelength with 16-PPM signaling, and supports data rates up to 10 Mbps over 1-5km long paths, will be discussed.by Nivedita Chandrasekaran.M.Eng

Weighted Semi-Supervised Approaches for Predictive Modeling and Truth Discovery

Multi-View Learning (MVL) is a framework which combines data from heteroge- neous sources in an efficient manner in which the different views learn from each other, thereby improving the overall prediction of the task. By not combining the data from different views together, we preserve the underlying statistical property of each view thereby learning from data in their original feature space. Additionally, MVL also mitigates the problem of high dimensionality when data from multiple sources are integrated. We have exploited this property of MVL to predict chemical-target and drug-disease associations. Every chemical or drug can be represented in diverse feature spaces that could be viewed as multiple views. Similarly multi-task learning (MTL) frameworks enables the joint learning of related tasks that improves the overall performances of the tasks than learning them individually. This factor allows us to learn related targets and related diseases together. An empirical study has been carried out to study the combined effects of multi-view multi-task learning (MVMTL) to pre- dict chemical-target interactions and drug-disease associations. The first half of the thesis focuses on two methods that closely resemble MVMTL. We first explain the weighted Multi-View learning (wMVL) framework that systemat- ically learns from heterogeneous data sources by weighting the views in terms of their predictive power. We extend the work to include multi-task learning and formulate the second method called Multi-Task with weighted Multi-View Learning (MTwMVL). The performance of these two methods have been evaluated by cheminformatics data sets. iiWe change gears for the second part of this thesis towards truth discovery (TD). Truth discovery closely resembles a multi-view setting but the two strongly differ in certain aspects. While the underlying assumption in multi-view learning is that the different views have label consistency, truth finding differs in its setup where the main objective is to find the true value of an object given that different sources might conflict with each other and claim different values for that object. The sources could be considered as views and the primary strategy in truth finding is to estimate the reliability of each source and its contribution to the truth. There are many methods that address various challenges and aspects of truth discovery and we have in this thesis looked at TD in a semi-supervised setting. As the third contribution to this dissertation, we adopt a semi-supervised truth dis- covery framework in which we consider the labeled objects and unlabeled objects as two closely related tasks with one task having strong labels while the other task hav- ing weak labels. We show that a small set of ground truth helps in achieving better accuracy than the unsupervised methods

Bidirectional adaptive optics architectures for optical communication through atmospheric turbulence

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.Cataloged from PDF version of thesis.Includes bibliographical references (pages 223-231).Free-space optical (FSO) classical communication links can provide high data rates vital for successfully serving the world's exponentially growing demand for bandwidth, while FSO quantum key distribution (QKD) links allow information-theoretic rather than computational secure communication between two parties. Unlike fiber-optic classical communication and QKD links, FSO links can do so with minimal up-front investments in infrastructure. Setting aside absorption and scattering losses along the propagation path, optical links with a terrestrial terminal will still experience the deleterious effects of clear-weather turbulence, namely beam spread, beam wander, angle-of-arrival spread, and scintillation, which leads to low end-to-end power transfer from the transmitter to receiver. Decreases in the power transfer result in lower communication rates and may result in no secure-key rate for the loss-sensitive QKD communication protocols. Adaptive optics holds the best promise for mitigating, if not completely compensating for, these turbulence-induced degradations. Nevertheless, despite adaptive optics being a richly developed field, theoretical studies of adaptive optics systems have not fully exploited the reciprocal nature of propagation through atmospheric turbulence. It is known that applying ideal, full-wave adaptive optics at both the transmitter and receiver of a free-space optical link can guarantee scintillation-free power transmission when operation is deep in the near-field power transfer regime. Buoyed by the advent of enabling technologies like scalable Mach-Zehnder interferometer arrays and coherent receiver arrays, this thesis: (1) introduces both a full-wave and phase-only bidirectional adaptive optics (BDAO) protocol; (2) assesses the ergodic performances of FSO classical and QKD communication links utilizing these BDAO systems using both theoretical performance bounds as well as turbulence simulation results; and (3) provides an initial study of the noise and time-dynamics the BDAO protocol can tolerate while still achieving near-optimal classical communication or QKD rates.by Nivedita Chandrasekaran.Ph. D

Photon information efficient communication through atmospheric turbulence

High photon-efficiency (many bits/photon) optical communication is possible with pulse-position modulation and direct detection, and high spectral efficiency (many bits/sec-Hz) optical communication is possible with quadrature-amplitude modulation and coherent detection. These high efficiencies, however, cannot be achieved simultaneously unless multiple spatial modes are employed. Previous work for the vacuum-propagation channel has shown that achieving 10 bits/photon and 5 bits/sec-Hz is impossible with coherent detection, and it requires 189 low diffraction-loss spatial modes at the ultimate Holevo limit, and 4500 such modes at the Shannon limit for on-off keying with direct detection. For terrestrial propagation paths, however, the effects of atmospheric turbulence must be factored into the photon and spectral efficiency assessments. This paper accomplishes that goal by presenting upper and lower bounds on the turbulent channel’s ergodic Holevo capacity for M-mode systems whose transmitters use either focused-beam, Hermite-Gaussian (HG), or Laguerre-Gaussian (LG) modes, and whose receivers do M-mode detection either with or without adaptive optics. The bounds show that use of adaptive optics will not be necessary for achieving high photon efficiency and high spectral efficiency through atmospheric turbulence, although receivers which do not use adaptive optics will need to cope with considerable crosstalk between the spatial patterns produced in their entrance pupils by the M-mode transmitter. The bounds also show the exact theoretical equivalence of the HG and LG mode sets for this application, generalizing a result previously established for the vacuum-propagation channel. Finally, our results show that the FB modes outperform the HG and LG modes in operation with and without adaptive optics.National Science Foundation (U.S.). Integrative Graduate Education and Research Traineeship (Interdisciplinary Quantum Information Science and Engineering)United States. Defense Advanced Research Projects Agency. Information in a Photon (InPho) Program (DARPA/CMO Contract HR0011-10-C-1059

Body mass index contributes to sympathovagal imbalance in prehypertensives

Abstract Background The present study was conducted to assess the nature of sympathovagal imbalance (SVI) in prehypertensives by short-term analysis of heart rate variability (HRV) to understand the alteration in autonomic modulation and the contribution of BMI to SVI in the genesis of prehypertension. Methods Body mass index (BMI), basal heart rate (BHR), blood pressure (BP), rate pressure product (RPP) and HRV indices such as total power (TP), low-frequency power (LF), normalized LF (LFnu), high-frequency power (HF), normalized HF (HFnu), LF-HF ratio, mean heart rate (mean RR), square root of the mean squared differences of successive normal to normal intervals (RMSSD), standard deviation of normal to normal RR interval (SDNN), the number of interval differences of successive NN intervals greater than 50 ms (NN50) and the proportion derived by dividing NN50 by the total number of NN intervals (pNN50) were assessed in three groups of subjects: normotensives having normal BMI (Group 1), prehypertensives having normal BMI (Group 2) and prehypertensives having higher BMI (Group 3). SVI was assessed from LF-HF ratio and correlated with BMI, BHR, BP and RPP in all the groups by Pearson correlation. The contribution of BMI to SVI was assessed by multiple regression analysis. Results LF and LFnu were significantly increased and HF and HFnu were significantly decreased in prehypertensive subjects in comparison to normotensive subjects and the magnitude of these changes was more prominent in subjects with higher BMI compared to that of normal BMI. LF-HF ratio, the sensitive indicator of sympathovagal balance had significant correlation with BMI (P = 0.000) and diastolic blood pressure (DBP) (P = 0.002) in prehypertensives. BMI was found to be an independent contributing factor to SVI (P = 0.001) in prehypertensives. Conclusions It was concluded that autonomic imbalance in prehypertensives manifested in the form of increased sympathetic activity and vagal inhibition. In prehypertensives with higher BMI, vagal withdrawal was predominant than sympathetic overactivity. Magnitude of SVI (alteration in LF-HF ratio) was linked to changes in BMI and DBP. BMI had an independent influence on LF-HF ratio. It was advised that life-style modifications such as yoga and exercise would enable achieve the sympathovagal balance and blood pressure homeostasis in prehypertensives.</p

Sympathovagal imbalance contributes to prehypertension status and cardiovascular risks attributed by insulin resistance, inflammation, dyslipidemia and oxidative stress in first degree relatives of type 2 diabetics.

BackgroundThough cardiovascular (CV) risks are reported in first-degree relatives (FDR) of type 2 diabetics, the pathophysiological mechanisms contributing to these risks are not known. We investigated the association of sympathovagal imbalance (SVI) with CV risks in these subjects.Subjects and methodsBody mass index (BMI), basal heart rate (BHR), blood pressure (BP), rate-pressure product (RPP), spectral indices of heart rate variability (HRV), autonomic function tests, insulin resistance (HOMA-IR), lipid profile, inflammatory markers, oxidative stress (OS) marker, rennin, thyroid profile and serum electrolytes were measured and analyzed in subjects of study group (FDR of type 2 diabetics, n = 72) and control group (subjects with no family history of diabetes, n = 104).ResultsBMI, BP, BHR, HOMA-IR, lipid profile, inflammatory and OS markers, renin, LF-HF (ratio of low-frequency to high-frequency power of HRV, a sensitive marker of SVI) were significantly increased (pConclusionSVI in FDR of type 2 diabetics occurs due to sympathetic activation and vagal withdrawal. The SVI contributes to prehypertension status and CV risks caused by insulin resistance, dyslipidemia, inflammation and oxidative stress in FDR of type 2 diabetics

Bivariate logistic regression analysis of RPP (as dependent variable) with LF-HF ratio of heart rate variability (as independent variable) in control group and study group subjects after adjusting for BMI.

<p>p<0.05 considered significant; OR : odds ratio; RPP: rate pressure product; LF-HF: Ratio of low-frequency to high-frequency power of heart rate variability; C.I. : confidence interval.</p

Multiple regression analysis of LF-HF (as dependent variable) with various parameters (as independent variables) in study group subjects.

<p>P values<0.05 considered significant. BMI: Body mass index; HOMA-IR: homeostatic model assessment of insulin resistance; AI: Atherogenic index; IL6: Interleukin 6; hsCRP: high-sensitive C reactive protein; TNFα: Tumor necrosis factorα; TBARS: Thiobarbituric acid reactive substance; PHTN status: Prehypertension status.</p