Monte Carlo Based Computer Simulations Research Articles

Multi‐user two‐way relaying in the presence of co‐channel interference

This study investigates the impact of co-channel interference caused by external terminals on multi-user bi-directional amplify-and-forward based wireless relaying network. The investigation considers multi-user pair and a single bi-directional relay terminal and a finite number of co-channel interference in the system model. A lower bound on the end-to-end outage probability is derived for the simultaneous transmission and the opportunistic source-pair selection strategy. According to analytical, asymptotic, and Monte-Carlo based computer simulation results, the opportunistic source-pair selection strategy achieves a near-optimal performance for the inter-cell interference caused by other user-pairs within the system. Results also show that the opportunistic source-pair selection strategy also achieves optimal diversity order, which is equal to N, in high signal-to-noise ratio regimes. Results also show that the co-channel interference degrades the achievable diversity order from N to 0 while also affecting the system coding gain.

LDPCC and OFDM based cooperative communication for wireless sensor networks

This paper investigates the low-density parity-check codes and orthogonal frequency division multiplexing technique effects on the relay assisted sensor networks. The investigation utilizes Rician and Rayleigh fading environments for the performance analysis. The investigation also considers two different types of information exchange processes, which are direct and relay assisted cases. In the relay assisted case, the relay terminal operates in amplify-and-forward and decode-and-forward modes. Monte-Carlo based computer simulations reveal that 10-5 bit error rate value is reached at 16.50 dB for low density parity check coded orthogonal frequency division multiplexing over Rician fading environment in decode-and-forward relay protocol. Similarly, 10-5 bit error rate value is reached at 0.36 dB for the low density parity check coded orthogonal frequency division multiplexing over Rician fading environment in amplify-and-forward relay protocol and finally 10-5 bit error rate value is reached at -5.30 dB for low density parity check coded orthogonal frequency division multiplexing over Rician fading environment without relay protocols.

Secrecy outage performance of multi-hop LEACH networks using power beacon aided cooperative jamming with jammer selection methods

In this paper, we evaluate secrecy performance of cooperative jamming (CJ) aided secure transmission for Multi-hop Low-Energy Adaptive Clustering Hierarchy (M-LEACH) networks, where data transmission between a source and a destination is performed via cluster heads (CHs) of intermediate clusters, and is overheard by an eavesdropper. To protect the source information at each hop, each CH selects one or many cluster nodes to realize the CJ technique. We propose energy harvesting (EH) based jammer selection methods named MAX-EH, MAX-IP and ALL-CJ, where the selected jammer(s) has to harvest wireless energy from a dedicated power beacon to generate jamming noises. In MAX-EH, the cluster node obtained the MAXimum Energy Harvested from the power beacon is chosen. In MAX-IP, the selected jammer is the cluster node providing the MAXimum Interference Power to the eavesdropper. In ALL-CJ, ALL cluster nodes in the clusters take part in the CJ operation. For performance evaluation, we derive expressions of the end-to-end (e2e) secrecy outage probability (SOP) for the proposed methods over Rayleigh fading channels. We then perform Monte-Carlo based computer simulations to verify the theoretical results. The results presented that the proposed methods outperform the RANDom jammer selection (RAND) and the corresponding method WithOut using the CJ technique (WO-CJ).

Joint source‐pair and relay selection for relay‐assisted network

This study investigates the opportunistic joint source-pair and relay selection policy for cooperative networks. The investigation considers multi-user pair and multiple bi-directional amplify-and-forward based relays in the system model. The strategy selects an appropriate user-pair and relay among N candidate user-pairs and R available relays based on the maximum achievable sum-rate of each user pair and related relay terminal. Analytical, asymptotic, and Monte Carlo based computer simulation results reveal that the joint-selection strategy achieves multi-user and cooperative diversity order in high signal-to-noise ratios. The results also show that the opportunistic joint source-pair and relay selection strategy outperforms the max–min based selection policy. Moreover, the system contains a single relay, the joint-selection strategy achieves only a multi-user diversity and performs worse than the system that contains multiple relays. The results also show that the total achievable diversity order equals to the total number of possible paths between user-pairs and relays, which is , while in the multi-user and a single relay model, the diversity order only equals to N. Results also reveal that the proposed selection strategy provides an equal transmission opportunity for each of the user-pairs.

Quantitative assessment of Cerenkov luminescence for radioguided brain tumor resection surgery

Cerenkov luminescence imaging (CLI) is a developing imaging modality that detects radiolabeled molecules via visible light emitted during the radioactive decay process. We used a Monte Carlo based computer simulation to quantitatively investigate CLI compared to direct detection of the ionizing radiation itself as an intraoperative imaging tool for assessment of brain tumor margins. Our brain tumor model consisted of a 1 mm spherical tumor remnant embedded up to 5 mm in depth below the surface of normal brain tissue. Tumor to background contrast ranging from 2:1 to 10:1 were considered. We quantified all decay signals (e±, gamma photon, Cerenkov photons) reaching the brain volume surface. CLI proved to be the most sensitive method for detecting the tumor volume in both imaging and non-imaging strategies as assessed by contrast-to-noise ratio and by receiver operating characteristic output of a channelized Hotelling observer.

Formal reliability analysis of oil and gas pipelines

Depending on the operational environment, installation location, and aging of oil and gas pipelines, they are subject to various degradation mechanisms, such as cracking, corrosion, leaking, and thinning of the pipeline walls. Failure of oil and gas pipelines due to these degradation mechanisms can lead to catastrophic events, which, in the worst case, may result in the loss of human lives and huge financial losses. Traditionally, paper-and-pencil proof methods and Monte Carlo based computer simulations are used in the reliability analysis of oil and gas pipelines to identify potential threats and thus avoid unwanted failures. However, paper-and-pencil proof methods are prone to human error, especially when dealing with large systems, while simulation techniques primarily involve sampling-based methods, i.e., not all possible scenarios of the given systems are tested, which compromises the accuracy of the results. As an accurate alternative, we propose to use a higher-order-logic theorem proving for the reliability analysis of oil and gas pipelines. In particular, this paper presents the higher-order-logic formalization of commonly used reliability block diagrams (RBDs), such as series, parallel, series–parallel, and k-out-of- n, and provides an approach to utilize these formalized RBDs to assess the reliability of oil and gas pipelines. For illustration, we present a formal reliability analysis of a pipeline transportation subsystem used between the oil terminals at the Port of Gdynia, Poland, and Dębogórze.

Recursive least square–based fast sparse multipath channel estimation

SummaryIn the next‐generation wireless communication systems, the broadband signal transmission over wireless channel often incurs the frequency‐selective channel fading behavior and also results in the channel sparse structure, which is supported only by few large coefficients. For the stable wireless propagation to be ensured, linear adaptive channel estimation algorithms, eg, recursive least square and least mean square, have been developed. However, these traditional algorithms are unable to exploit the channel sparsity. Actually, channel estimation performance can be further improved by taking advantage of the sparsity. In this paper, 2 recursive least square–based fast adaptive sparse channel estimation algorithm is proposed by introducing sparse constraints, L1‐norm and L0‐norm, respectively. To improve the flexibility of the proposed algorithms, this paper introduces a regularization parameter selection method to adaptively exploit the channel sparsity. Finally, Monte Carlo–based computer simulations are conducted to validate the effectiveness of the proposed algorithms.

RZA-NLMF algorithm-based adaptive sparse sensing for realizing compressive sensing

Nonlinear sparse sensing (NSS) techniques have been adopted for realizing compressive sensing in many applications such as radar imaging. Unlike the NSS, in this paper, we propose an adaptive sparse sensing (ASS) approach using the reweighted zero-attracting normalized least mean fourth (RZA-NLMF) algorithm which depends on several given parameters, i.e., reweighted factor, regularization parameter, and initial step size. First, based on the independent assumption, Cramer-Rao lower bound (CRLB) is derived as for the performance comparisons. In addition, reweighted factor selection method is proposed for achieving robust estimation performance. Finally, to verify the algorithm, Monte Carlo-based computer simulations are given to show that the ASS achieves much better mean square error (MSE) performance than the NSS.

다중 사용자 및 다중 안테나 하향링크 네트워크에서 적응적 사용자 선택 기법

ABSTRACT Multiple antenna technique is attracting attention as a core technology for next-generation mobile communication systems to accommodate explosively increasing mobile data traffic. Especially, recent researches focus on multi-user multiple input multiple output (MU-MIMO) system where base stations are equipped with several tens of transmit antennas and transmit data to multiple terminals (users) simultaneously. To enhance the performance of MU-MIMO systems, we, in this paper, propose an adaptive user selection algorithm which adaptively selects a user set according to varying channel states. According to Monte-Carlo based computer simulations, the performance of proposed scheme is significantly improved compared to the conventional scheme without user selection and approaches that of exhaustive search-based optimal scheme. On the other hand, the proposed scheme can reduce the computational complexity to    compared to the optimal scheme where  denotes the number of total users.

Evaluating the Use of Contractor-Performed Test Results in Highway Construction and Material Acceptance Decisions

AbstractTransportation agencies around the world are using contractor-performed test results in construction and material acceptance and pay decisions. This practice is termed contractor acceptance testing (CAT) in this paper. Although CAT has helped transportation agencies to deal with a shrinking workforce and intensive construction schedules, it has been controversial. This paper provides insights into the technical and conceptual pitfalls of CAT. The technical pitfalls are revealed through Monte Carlo–based computer simulations of pavement specifications that use CAT. These simulations show that the verification process, which relies on the statistical F-test and t-test, is unreliable and can lead to erroneous pay decisions. The conceptual pitfalls are revealed by demonstrating that CAT encourages a quality-control approach that focuses on defect detection and containment, rather than defect prevention. Finally, potential alternatives and improvements to CAT are provided.

Dosimetric characterization of a dedicated breast computed tomography clinical prototype

To investigate the glandular dose magnitudes and characteristics resulting from image acquisition using a dedicated breast computed tomography (BCT) clinical prototype imaging system. The x-ray spectrum and output characteristics of a BCT clinical prototype (Koning Corporation, West Henrietta, NY) were determined using empirical measurements, breast phantoms, and an established spectrum model. The geometry of the BCT system was replicated in a Monte Carlo-based computer simulation using the GEANT4 toolkit and was validated by comparing the simulated results for exposure distribution in a standard 16 cm CT head phantom with those empirically determined using a 10 cm CT pencil ionization chamber and dosimeter. The computer simulation was further validated by replicating the results of a previous BCT dosimetry study. Upon validation, the computer simulation was modified to include breasts of varying sizes and homogeneous compositions spanning those encountered clinically, and the normalized mean glandular dose resulting from BCT was determined. Using the system's measured exposure output determined automatically for breasts of different size and density, the mean glandular dose for these breasts was computed and compared to the glandular dose resulting from mammography. Finally, additional Monte Carlo simulations were performed to study how the glandular dose values vary within the breast tissue during acquisition with both this BCT prototype and a typical craniocaudal (CC) mammographic acquisition. This BCT prototype uses an x-ray spectrum with a first half-value layer of 1.39 mm Al and a mean x-ray energy of 30.3 keV. The normalized mean glandular dose for breasts of varying size and composition during BCT acquisition with this system ranges from 0.278 to 0.582 mGy/mGy air kerma with the reference air kerma measured in air at the center of rotation. Using the measured exposure outputs for the tube currents automatically selected by the system for the breasts of different sizes and densities, the mean glandular dose for a BCT acquisition with this prototype system varies from 5.6 to 17.5 mGy, with the value for a breast of mean size and composition being 17.06 mGy. The glandular dose throughout the breast tissue of this mean breast varies by up to +/- 50% of the mean value. During a typical CC view mammographic acquisition of an equivalent mean breast, which typically results in a mean glandular dose of 2.0-2.5 mGy, the glandular dose throughout the breast tissue varies from approximately 15% to approximately 400% of the mean value. Acquisition of a BCT image with the automated tube output settings for a mean breast with the Koning Corp. clinical prototype results in mean glandular dose values approximately equivalent to three to five two-view mammographic examinations for a similar breast. For all breast sizes and compositions studied, this glandular dose ratio between acquisition with this BCT prototype and two-view mammography ranges from 1.4 to 7.2. In mammography, portions of the mean-sized breast receive a considerably higher dose than the mean value for the whole breast. However, only a small portion of a breast undergoing mammography would receive a glandular dose similar to that from BCT.

History-Dependent Catastrophes Regulate Axonal Microtubule Behavior

In Chinese hamster ovary cells, microtubules originate at the microtubule organizing center (MTOC) and grow persistently toward the cell edge, where they undergo catastrophe. In axons, microtubule dynamics must be regulated differently because microtubules grow parallel to the plasma membrane and there is no MTOC. GFP-tagged microtubule plus end tracking proteins (+TIPs) mark the ends of growing neuronal microtubules. Their fluorescent "comet-like" pattern reflects turnover of +TIP binding sites. Using GFP-tagged +TIPs and fluorescence-based segmentation and tracking tools, we show that axonal microtubules grow with a constant average velocity and that they undergo catastrophes at random positions, yet in a programmed fashion. Using protein depletion approaches, we find that the +TIPs CLIP-115 and CLIP-170 affect average microtubule growth rate and growth distance in neurons but not the duration of a microtubule growth event. In N1E-115 neuroblastoma cells, we find that EB1, the core +TIP, regulates microtubule growth rate, growth distance, and duration, consistent with in vitro data. Combined, our data suggest that CLIPs influence the axonal microtubule/tubulin ratio, whereas EB1 stimulates microtubule growth and structural transitions at microtubule ends, thereby regulating microtubule catastrophes and the turnover of +TIP binding sites.

A Neuromorphic Single-Electron Circuit for Noise-Shaping Pulse-Density Modulation

We propose a bio-inspired circuit performing pulse-density modulation with single-electron devices. The proposed circuit consists of three single-electron neuronal units, receiving the same input and are connected to a common output. The output is inhibitorily fedback to the three neuronal circuits through a capacitive coupling. The circuit performance was evaluated through Monte-Carlo based computer simulations. We demonstrated that the proposed circuit possesses noise-shaping characteristics, where signal and noises are separated into low and high frequency bands respectively. This significantly improved the signal-tonoise ratio (SNR) by 4.34 dB in the coupled network, as compared to the uncoupled one. The noise-shaping properties are as a result of i) the inhibitory feedback between the output and the neuronal circuits, and ii) static noises (originating from device fabrication mismatches) and dynamic noises (as a result of thermally induced random tunneling events) introduced into the network.

Uncertainty analysis of whole-field phase-differences retrieved from ESPI fringe patterns by using the Fourier transform method (FTM)

We have evaluated the uncertainty associated with the whole-field phase-differences retrieved by using the Fourier transform method (FTM), from a fringe pattern generated by electronic speckle pattern interferometry (ESPI). The phase-differences were induced by applying load to an elastic sample. The FTM involved the Fourier transform application to the fringe pattern, the isolation of the term carrying the phase information by applying a band-pass filter in the spatial frequency domain, and then the inverse Fourier transform application. Since the fringes in the analyzed pattern were adequately open, the FTM outcomes were presumed to be mainly affected by errors in the determination of both the width and the location of the applied filter mask. The influence of these error sources was assessed by using a Monte Carlo-based computer simulation. It implied evaluating the phase-differences a large number of times under the influence of the involved error sources. We found that the phase uncertainty depends strongly on the width of the applied filter mask; the influence of the other error sources considered into the uncertainty propagation was significantly smaller.

Uncertainty evaluation of out-of-plane displacements measured by electronic speckle-pattern interferometry (ESPI)

Electronic speckle-pattern interferometry (ESPI) is a whole-field optical technique used to generate phase fringe patterns modulo 2π that allow the measurement of the displacement fields induced on a specimen by mechanical deformation. We measured by ESPI the out-of-plane displacements induced on a specimen subjected to uniaxial tensile load. Our displacement measurements were influenced by optical noise and external vibration as well as by errors in the phase measuring technique and in the determination of the interferometer sensitivity. In this paper, the influences of these errors are characterized and compared with other systematic effects through an uncertainty analysis. We evaluated the uncertainty of the sensitivity vector components of the interferometer as well as the uncertainties associated with our measurements of the phase and the displacement. According to international recommendations, we carried out the uncertainty evaluations by using Monte Carlo based computer simulations. We found that the out-of-plane displacement uncertainty depends strongly on eventual alignment errors in the optical set-up.

Carrier dynamics studies through free-carrier absorption: a Monte Carlo study for silicon

Monte Carlo based computer simulations normally used for transport studies in semiconductors are extended and used to study free-carrier absorption of subbandgap radiation in semiconductors. The approach is applied to n-type silicon where we find very good agreement with experimental results and calculations based on quantum electrodynamics. The computer simulation method also allows us to study free-carrier absorption in semiconductors with a dc bias. We solve the classical transport equation to show that the absorption coefficient in the presence of a dc bias can be used to obtain information on the carrier temperature, momentum relaxation time, as well as energy relaxation time. Monte Carlo studies show this to be the case. Thus, we show that important carrier dynamics properties can be obtained from long-wavelength free-carrier absorption studies done on samples with a dc bias.