Computer-based Monte-Carlo Simulations Research Articles

Mixed RF/FSO SWIPT-Based OSLMD Coded AF Cooperative Communication System: Performance Analysis

In this paper, the performance analysis of simultaneous wireless information and power transfer (SWIPT) using time switching (TS) protocol-based amplify-and-forward (AF) dual-hop mixed radio-frequency/free-space optic (RF/FSO) coded and uncoded communication system (CC and UC) is investigated. Specifically, we look at using the One-Step Majority-Logic Decodable (OSMLD) codes at the source and a majority logic decoding algorithm (MLGD) at the destination, jointly with the use of maximal-ratio combining and SWIPT/TS techniques at the relay. Furthermore, the RF link undergoes Nakagami- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> model, while the second-hop is subject to Máalaga- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mathcal {M}$ </tex-math></inline-formula> atmospheric turbulence with the effect of pointing errors. Closed-form and asymptotic formulations for the average bit error probability (ABEP) are obtained in terms of the system parameters for both CC and UC scenarios in addition of the average channel capacity analysis. Computer-based Monte Carlo simulations were used to numerically validate all of the obtained mathematical formulations. Expectedly, it is shown that significant coding gains are achieved using OSMLD codes in comparison with UC. In addition, above a specific threshold of energy efficiency, the system performance gets steady in the high signal-to-noise-ratio regime. Moreover, the decoding method used in this work has been shown to be suitable for the SWIPT/TS-assisted RF/FSO coded AF cooperative communication system where high performance alongside low computational complexity are required.

Ergodic Capacity Analysis of UAV-Based FSO Links Over Foggy Channels

In this letter, we investigate the ergodic capacity of unmanned aerial vehicle (UAV)-based free space optics (FSO) links over random foggy channel. More specifically, we derive composite probability density function (PDF) and close approximation for the moments of the composite PDF using the statistical model of a UAV-based 3D pointing error and a random foggy channel. With it, we obtain upper bound and asymptotic approximation of the ergodic capacity for the two possible detection techniques of intensity modulation/direct detection (IM/DD) and heterodyne detection at high and low signal-to-noise ratio (SNR) regimes. The numerical results confirm all the presented analytic results via computer-based Monte-Carlo simulations.

Anatomically aided PET image reconstruction using deep neural networks.

The developments of PET/CT and PET/MR scanners provide opportunities for improving PET image quality by using anatomical information. In this paper, we propose a novel co-learning three-dimensional (3D) convolutional neural network (CNN) to extract modality-specific features from PET/CT image pairs and integrate complementary features into an iterative reconstruction framework to improve PET image reconstruction. We used a pretrained deep neural network to represent PET images. The network was trained using low-count PET and CT image pairs as inputs and high-count PET images as labels. This network was then incorporated into a constrained maximum likelihood framework to regularize PET image reconstruction. Two different network structures were investigated for the integration of anatomical information from CT images. One was a multichannel CNN, which treated PET and CT volumes as separate channels of the input. The other one was multibranch CNN, which implemented separate encoders for PET and CT images to extract latent features and fed the combined latent features into a decoder. Using computer-based Monte Carlo simulations and two real patient datasets, the proposed method has been compared with existing methods, including the maximum likelihood expectation maximization (MLEM) reconstruction, a kernel-based reconstruction and a CNN-based deep penalty method with and without anatomical guidance. Reconstructed images showed that the proposed constrained ML reconstruction approach produced higher quality images than the competing methods. The tumors in the lung region have higher contrast in the proposed constrained ML reconstruction than in the CNN-based deep penalty reconstruction. The image quality was further improved by incorporating the anatomical information. Moreover, the liver standard deviation was lower in the proposed approach than all the competing methods at a matched lesion contrast. The supervised co-learning strategy can improve the performance of constrained maximum likelihood reconstruction. Compared with existing techniques, the proposed method produced a better lesion contrast versus background standard deviation trade-off curve, which can potentially improve lesion detection.

Performance Analysis of Dual-Hop Underwater Wireless Optical Communication Systems Over Mixture Exponential-Generalized Gamma Turbulence Channels

In this work, we present a unified framework for the performance analysis of dual-hop underwater wireless optical communication (UWOC) systems with amplify-and-forward fixed gain relays in the presence of air bubbles and temperature gradients. Operating under either heterodyne detection or intensity modulation with direct detection, the UWOC is modeled by the unified mixture Exponential-Generalized Gamma distribution that we have proposed based on an experiment conducted in an indoor laboratory setup and has been shown to provide an excellent fit with the measured data under the considered lab channel scenarios. More specifically, we derive the cumulative distribution function (CDF) and the probability density function of the end-to-end signal-to-noise ratio (SNR) in exact closed-form in terms of the bivariate Fox's H function. Based on this CDF expression, we present novel results for the fundamental performance metrics such as the outage probability, the average bit-error rate (BER) for various modulation schemes, and the ergodic capacity. Additionally, very tight asymptotic results for the outage probability and the average BER at high SNR are obtained in terms of simple functions. Furthermore, we demonstrate that the dual-hop UWOC system can effectively mitigate the short range and both temperature gradients and air bubbles induced turbulences, as compared to the single UWOC link. All the results are verified via computer-based Monte-Carlo simulations.

Generative adversarial network based regularized image reconstruction for PET

Positron emission tomography (PET) is an ill-posed inverse problem and suffers high noise due to limited number of detected events. Prior information can be used to improve the quality of reconstructed PET images. Deep neural networks have also been applied to regularized image reconstruction. One method is to use a pretrained denoising neural network to represent the PET image and to perform a constrained maximum likelihood estimation. In this work, we propose to use a generative adversarial network (GAN) to further improve the network performance. We also modify the objective function to include a data-matching term on the network input. Experimental studies using computer-based Monte Carlo simulations and real patient datasets demonstrate that the proposed method leads to noticeable improvements over the kernel-based and U-net-based regularization methods in terms of lesion contrast recovery versus background noise trade-offs.

On performance analysis of hybrid FSO/RF systems

In this work, the author investigate the performance of the hybrid free-space optical/radio frequency (FSO/RF) communication systems where RF links are subject to Nakagami-m distribution fading effects. The author derive the statistical characteristics of the hybrid FSO/RF systems in closed-form in terms of Meijer's G-function and the extended generalised bivariate Meijer's G-function. Then, the author rely on these new results to present the performance analysis of the selection combining diversity based on hybrid FSO/RF systems. Also, the author consider a Gamma–Gamma turbulence distribution under the impact of pointing errors and subject to both types of detection techniques (i.e. heterodyne detection and intensity modulation with direct detection (IM/DD)) in the FSO link. Computer-based Monte–Carlo simulations are proved the accuracy of the new analytical results.

On the Maximum and Minimum of Double Generalized Gamma Variates With Applications to the Performance of Free-Space Optical Communication Systems

In this paper, we derive the exact statistical characteristics of the maximum and the minimum of two modified double generalized gamma variates in closed form in terms of Meijer's G-function, Fox's H-function, the extended generalized bivariate Meijer's G-function, and H-function, in addition to simple closed-form asymptotic results in terms of elementary functions. Then, we rely on these new results to present the performance analysis of 1) a dual-branch free-space optical selection combining (FSO SC) diversity and 2) a dual-hop (DH) FSO relay transmission system over double generalized gamma fading channels with the impact of pointing errors. In addition, we provide asymptotic results of the bit error rate (BER) of the two systems at a high signal-to-noise ratio (SNR) regime. Computer-based Monte Carlo simulations verify our new analytical results.

Performance Analysis of Free-Space Optical Links Over Málaga ($\mathcal{M} $) Turbulence Channels With Pointing Errors

In this work, we present a unified performance analysis of a free-space optical (FSO) link that accounts for pointing errors and both types of detection techniques [i.e., intensity modulation/direct detection (IM/DD) and heterodyne detection]. More specifically, we present unified exact closed-form expressions for the cumulative distribution function, the probability density function, the moment generating function, and the moments of the end-to-end signal-to-noise ratio (SNR) of a single link FSO transmission system, all in terms of the Meijer's G function except for the moments that is in terms of simple elementary functions. We then capitalize on these unified results to offer unified exact closed-form expressions for various performance metrics of FSO link transmission systems, such as the outage probability, the scintillation index (SI), the average error rate for binary and $M$-ary modulation schemes, and the ergodic capacity (except for IM/DD technique, where we present closed-form lower bound results), all in terms of Meijer's G functions except for the SI that is in terms of simple elementary functions. Additionally, we derive the asymptotic results for all the expressions derived earlier in terms of Meijer's G function in the high SNR regime in terms of simple elementary functions via an asymptotic expansion of the Meijer's G function. We also derive new asymptotic expressions for the ergodic capacity in the low as well as high SNR regimes in terms of simple elementary functions via utilizing moments. All the presented results are verified via computer-based Monte-Carlo simulations.

Multihop Relaying Over IM/DD FSO Systems With Pointing Errors

In this paper, the end-to-end performance of a multihop free-space optical system with amplify-and-forward channel-state-information-assisted or fixed-gain relays using intensity modulation with direct detection technique over Gamma–Gamma turbulence fading with pointing error impairments is studied. More specifically, novel closed-form results for the probability density function and the cumulative distribution function of the end-to-end signal-to-noise ratio (SNR) are derived in terms of the Fox's H function. Based on these formulas, closed form bounds for the outage probability, the average bit-error rate of on–off keying modulation scheme, the moments, and the ergodic capacity are presented. Furthermore, using the moments-based approach, tight asymptotic approximations at high- and low-average SNR regimes are derived for the ergodic capacity in terms of simple elementary functions. The obtained results indicate that the overall system performance degrades with an increase of the number of hops. The effects of the atmospheric turbulence conditions and the pointing error are also quantified. All the analytical results are verified via computer-based Monte-Carlo simulations.

Theoretical Analysis of Penalized Maximum-Likelihood Patlak Parametric Image Reconstruction in Dynamic PET for Lesion Detection.

Detecting cancerous lesions is a major clinical application of emission tomography. In a previous work, we studied penalized maximum-likelihood (PML) image reconstruction for lesion detection in static PET. Here we extend our theoretical analysis of static PET reconstruction to dynamic PET. We study both the conventional indirect reconstruction and direct reconstruction for Patlak parametric image estimation. In indirect reconstruction, Patlak parametric images are generated by first reconstructing a sequence of dynamic PET images, and then performing Patlak analysis on the time activity curves (TACs) pixel-by-pixel. In direct reconstruction, Patlak parametric images are estimated directly from raw sinogram data by incorporating the Patlak model into the image reconstruction procedure. PML reconstruction is used in both the indirect and direct reconstruction methods. We use a channelized Hotelling observer (CHO) to assess lesion detectability in Patlak parametric images. Simplified expressions for evaluating the lesion detectability have been derived and applied to the selection of the regularization parameter value to maximize detection performance. The proposed method is validated using computer-based Monte Carlo simulations. Good agreements between the theoretical predictions and the Monte Carlo results are observed. Both theoretical predictions and Monte Carlo simulation results show the benefit of the indirect and direct methods under optimized regularization parameters in dynamic PET reconstruction for lesion detection, when compared with the conventional static PET reconstruction.

On the Performance of Free-Space Optical Communication Systems Over Double Generalized Gamma Channel

Starting with the double generalized Gamma (GG) model to describe turbulence-induced fading in free-space optical (FSO) systems, we propose a new unified model that accounts for the impact of pointing errors and type of receiver detector. More specifically, we present unified closed-form expressions for the cumulative distribution function, the probability density function, the moment generating function, and the moments of the end-to-end signal-to-noise ratio (SNR) of a single link FSO transmission system in terms of the Meijer's G-function. We then use these unified expressions to evaluate performance measures such as the bit error rate, the outage probability, and the ergodic capacity of: 1) a single FSO link operating over double GG fading model; and 2) asymmetric RF-FSO dual-hop relay transmission system with fixed gain relay. Using an asymptotic expansion of the Meijer's G-function at high SNR, we express all the expressions, derived earlier, in terms of elementary functions. All our analytical results are verified using computer based-Monte Carlo simulations.

Ergodic Capacity Analysis of Free-Space Optical Links With Nonzero Boresight Pointing Errors

A unified capacity analysis of a free-space optical (FSO) link that accounts for nonzero boresight pointing errors and both types of detection techniques (i.e. intensity modulation/direct detection as well as heterodyne detection) is addressed in this work. More specifically, an exact closed-form expression for the moments of the end-to-end signal-to-noise ratio (SNR) of a single link FSO transmission system is presented in terms of well-known elementary functions. Capitalizing on these new moments expressions, we present approximate and simple closed-form results for the ergodic capacity at high and low SNR regimes. All the presented results are verified via computer-based Monte-Carlo simulations.

Development of a surrogate model for elemental analysis using a natural gamma ray spectroscopy tool

A systematic computational method for obtaining accurate elemental standards efficiently for varying borehole conditions was developed based on Monte Carlo simulations, surrogate modeling, and data assimilation. Elemental standards are essential for spectral unfolding in formation evaluation applications commonly used for nuclear well logging tools. Typically, elemental standards are obtained by standardized measurements, but these experiments are expensive and lack the flexibility to address different logging conditions. In contrast, computer-based Monte Carlo simulations provide an accurate and more flexible approach to obtaining elemental standards for formation evaluation.The presented computational method recognizes that in contrast to typical neutron–photon simulations, where the source is typically artificial and well characterized (Galford, 2009), an accurate knowledge of the source is essential for matching the obtained Monte Carlo elemental standards with their experimental counterparts. Therefore, source distributions are adjusted to minimize the L2 difference of the Monte Carlo computed and experimental standards. Subsequently, an accurate surrogate model is developed accounting for different casing and cement thicknesses, and tool positions within the borehole.The adjusted source distributions are then utilized to generate and validate spectra for varying borehole conditions: tool position, casing and cement thickness. The effect of these conditions on the spectra are investigated and discussed in this work.Given that Monte Carlo modeling provides much lower cost and more flexibility, employing Monte Carlo could enhance the processing of nuclear tool logging data computed standards.

On the Performance of Multihop Heterodyne FSO Systems With Pointing Errors

This paper reports the end-to-end performance analysis of a multihop free-space optical system with amplify-and-forward (AF) channel-state-information (CSI)-assisted or fixed-gain relays using heterodyne detection over Gamma–Gamma turbulence fading with pointing error impairments. In particular, we derive new closed-form results for the average bit error rate (BER) of a variety of binary modulation schemes and the ergodic capacity in terms of the Meijer's G function. We then offer new accurate asymptotic results for the average BER and the ergodic capacity at high SNR values in terms of simple elementary functions. For the capacity, novel asymptotic results at low and high average SNR regimes are also obtained via an alternative moments-based approach. All analytical results are verified via computer-based Monte-Carlo simulations.

Regularization design in penalized maximum-likelihood image reconstruction for lesion detection in 3D PET

Detecting cancerous lesions is a major clinical application in emission tomography. In previous work, we have studied penalized maximum-likelihood (PML) image reconstruction for the detection task and proposed a method to design a shift-invariant quadratic penalty function to maximize detectability of a lesion at a known location in a two dimensional image. Here we extend the regularization design to maximize detectability of lesions at unknown locations in fully 3D PET. We used a multiview channelized Hotelling observer (mvCHO) to assess the lesion detectability in 3D images to mimic the condition where a human observer examines three orthogonal views of a 3D image for lesion detection. We derived simplified theoretical expressions that allow fast prediction of the detectability of a 3D lesion. The theoretical results were used to design the regularization in PML reconstruction to improve lesion detectability. We conducted computer-based Monte Carlo simulations to compare the optimized penalty with the conventional penalty for detecting lesions of various sizes. Only true coincidence events were simulated. Lesion detectability was also assessed by two human observers, whose performances agree well with that of the mvCHO. Both the numerical observer and human observer results showed a statistically significant improvement in lesion detection by using the proposed penalty function compared to using the conventional penalty function.

On Hybrid Cooperation in Underlay Cognitive Radio Networks

Cooperative communication is a promising strategy to enhance the performance of a communication network as it helps to improve the coverage area and the outage performance. However, such enhancement comes at the expense of increased resource utilization, which is undesirable; more so in the case of opportunistic wireless systems such as cognitive radio networks. In order to balance the performance gains from cooperative communication against the possible over-utilization of resources, we propose and analyze an adaptive-cooperation technique for underlay cognitive radio networks, termed as hybrid-cooperation. Under the proposed cooperation scheme, secondary users in a cognitive radio network cooperate adaptively to enhance the spectral efficiency and the error performance of the network. The bit error rate, the spectral efficiency and the outage performance of the network under the proposed hybrid cooperation scheme with amplify-and-forward relaying are analyzed in this paper, and compared against conventional cooperation technique. Findings of the analytical performance analyses are further validated numerically through selected computer-based Monte-Carlo simulations. The proposed scheme is found to achieve significantly better performance in terms of the spectral efficiency and the bit error rate, compared to the conventional amplify-and-forward cooperation scheme.

Penalized maximum-likelihood image reconstruction for lesion detection

Detecting cancerous lesions is one major application in emission tomography. In this paper, we study penalized maximum-likelihood image reconstruction for this important clinical task. Compared to analytical reconstruction methods, statistical approaches can improve the image quality by accurately modelling the photon detection process and measurement noise in imaging systems. To explore the full potential of penalized maximum-likelihood image reconstruction for lesion detection, we derived simplified theoretical expressions that allow fast evaluation of the detectability of a random lesion. The theoretical results are used to design the regularization parameters to improve lesion detectability. We conducted computer-based Monte Carlo simulations to compare the proposed penalty function, conventional penalty function, and a penalty function for isotropic point spread function. The lesion detectability is measured by a channelized Hotelling observer. The results show that the proposed penalty function outperforms the other penalty functions for lesion detection. The relative improvement is dependent on the size of the lesion. However, we found that the penalty function optimized for a 5 mm lesion still outperforms the other two penalty functions for detecting a 14 mm lesion. Therefore, it is feasible to use the penalty function designed for small lesions in image reconstruction, because detection of large lesions is relatively easy.

Nonradiative Excitation Energy Transfer in Hydrophobically Modified Amphiphilic Block Copolymer Micelles. Theoretical Model and Monte Carlo Simulations,

A general approach for analyzing the direct nonradiative excitation transfer from donors to traps (NRET) in systems of specifically tagged polymeric micelles is presented. We assume that the micelles are formed by a hydrophobic/hydrophilic diblock copolymer in a strongly polar selective solvent. The micelle-forming chain is tagged by a donor between blocks and by a strongly hydrophobic trap at the end of the hydrophilic shell-forming block. When micelles are formed the donors are trapped at the core/shell interface and the hydrophobic traps try to avoid the polar medium and return back into the shell. Formation of compact chain conformations or loops is entropically unfavorable and the spatial distribution of traps in the shell is a result of the enthalpy-to-entropy interplay. Several physically reasonable but simplified models for the distributions of traps in the shell have been studied in detail. Representative results of computer-based Monte Carlo simulations of the time-resolved donor fluorescence de...