Researcher:
Mehrnia, Niloofar

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Niloofar

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Mehrnia

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Mehrnia, Niloofar

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2019 - 201932020 - 20224

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Researcher Of Publications: search.filters.isAuthorOfPublication.15a59fd1-e459-4ea7-aee8-ecc95a0f042d

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Now showing 1 - 7 of 7
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    Ray tracing-based maritime channel analysis for millimeter radiowaves
    (Springer, 2019) Ozdemir, Mehmet Kemal; N/A; Mehrnia, Niloofar; PhD Student; Graduate School of Sciences and Engineering; N/A
    In this work, we present and analyze the simulation results of millimeter-wave propagation channel performed over the sea surface for ship to ship scenario. We present a channel characterization study where channel parameters such as path loss, received power, root mean square delay spread, and power delay profile are inspected by taking the ray tracing advantages of the Wireless InSite software. 35 GHz and 94 GHz are the bands of interest, as they have minimum water and oxygen attenuation and their performances in practice would be the best among the other frequency bands. In our study, we investigate the effect of ray spacing, Earth's curvature, and the sea surface roughness on marine channel characteristics. Our results demonstrate that 2-ray analytical model should be only used for some short ranges over the sea surface propagating at high frequencies. Besides, free-space path loss model cannot predict the behavior of channel over the sea surface in high frequencies even for the short ranges. Therefore, a new path loss model is proposed to compensate the defects of existing path loss models by the means of changing the reflection coefficient and modifying the original 2-ray path loss model. This proposed model is able to better follow the simulated or measured propagation loss with less error, when it is compared with Free Space and 2-ray path loss models. Hence, this new model can be used for the path loss calculations at the mentioned frequencies especially for large distances between transmitter and receiver.
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    Power efficient beam-forming algorithm for ultra-reliable low latency millimeter-wave communications
    (Ieee, 2019) N/A; N/A; Department of Electrical and Electronics Engineering; Mehrnia, Niloofar; Ergen, Sinem Çöleri; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 7211
    Achieving ultra low-latency and ultra-high reliable communications at millimeter-waves (mmWaves) is challenging due to the sensitivity of this frequency band to blockage. Different space diversity schemes based on either equal gain or beam-tracking algorithms, are proposed to cope with the significant propagation losses introduced by the blockage at mmWaves. However, equal gain algorithms suffer from the low throughput as they allocate considerable gain to the non-optimal links. On the other hand, beam-tracking algorithms suffer from the link outage as the beam-forming is redone after dropping a large amount of data. In this study we propose a new algorithm based on the prior collection of data to eliminate power consuming beam-tracking techniques while minimum diversity level ensures high received power, ultra-reliability, and low latency.
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    Extreme value theory based rate selection for ultra-reliable communications
    (Institute of Electrical and Electronics Engineers (IEEE), 2022) N/A; Department of Electrical and Electronics Engineering; Mehrnia, Niloofar; Ergen, Sinem Çöleri; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 7211
    Ultra-reliable low latency communication (URLLC) requires the packet error rate to be on the order of 10(-9)-10(-5). Determining the appropriate transmission rate to satisfy this ultra-reliability constraint requires deriving the statistics of the channel in the ultra-reliable region and then incorporating these statistics into the rate selection. In this paper, we propose a framework for determining the rate selection for ultrareliable communications based on the extreme value theory (EVT). We first model the wireless channel at URLLC by estimating the parameters of the generalized Pareto distribution (GPD) best fitting to the tail distribution of the received powers, i.e., the power values below a certain threshold. Then, we determine the maximum transmission rate by incorporating the Pareto distribution into the rate selection function. Finally, we validate the selected rate by computing the resulting error probability. Based on the data collected within the engine compartment of Fiat Linea, we demonstrate the superior performance of the proposed methodology in determining the maximum transmission rate compared to the traditional extrapolation-based approaches.
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    PublicationOpen Access
    Non-stationary wireless channel modeling approach based on extreme value theory for ultra-reliable communications
    (Institute of Electrical and Electronics Engineers (IEEE), 2021) Department of Electrical and Electronics Engineering; Ergen, Sinem Çöleri; Mehrnia, Niloofar; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; 7211; N/A
    A proper channel modeling methodology that characterizes the statistics of extreme events is key in the design of a system at an ultra-reliable regime of operation. The strict constraint of ultra-reliability corresponds to the packet error rate (PER) in the range of 10(-9)-10(-5) within the acceptable latency on the order of milliseconds. Extreme value theory (EVT) is a robust framework for modeling the statistical behavior of extreme events in the channel data. In this paper, we propose a methodology based on EVT to model the extreme events of a non-stationary wireless channel for the ultra-reliable regime of operation. This methodology includes techniques for splitting the channel data sequence into multiple groups concerning the environmental factors causing non-stationarity, and fitting the lower tail distribution of the received power in each group to the generalized Pareto distribution (GPD). The proposed approach also consists of optimally determining the time-varying threshold over which the tail statistics are derived as a function of time, and assessing the validity of the derived Pareto model. Finally, the proposed approach chooses the best model with minimum complexity that represents the time variation behavior of the non-stationary channel data sequence. Based on the data collected within the engine compartment of Fiat Linea under various engine vibrations and driving scenarios, we demonstrate the capability of the proposed methodology in providing the best fit to the extremes of the non-stationary data. The proposed approach significantly outperforms the channel modeling approach using the stationary channel assumption in characterizing the extreme events.
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    PublicationOpen Access
    Incorporation of confidence interval into rate selection based on the extreme value theory for ultra-reliable communications
    (Institute of Electrical and Electronics Engineers (IEEE), 2022) Department of Electrical and Electronics Engineering; Ergen, Sinem Çöleri; Mehrnia, Niloofar; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 7211; N/A
    Proper determination of the transmission rate in ultra-reliable low latency communication (URLLC) needs to incorporate a confidence interval (CI) for the estimated parameters due to the large amount of data required for their accurate estimation. In this paper, we propose a framework based on the extreme value theory (EVT) for determining the transmission rate along with its corresponding CI for an ultra-reliable communication system. This framework consists of characterizing the statistics of extreme events by fitting the generalized Pareto distribution (GPD) to the channel tail, deriving the GPD parameters and their associated CIs, and obtaining the transmission rate within a confidence interval. Based on the data collected within the engine compartment of Fiat Linea, we demonstrate the accuracy of the estimated rate obtained through the EVT-based framework considering the confidence interval for the GPD parameters. Additionally, we show that proper estimation of the transmission rate based on the proposed framework requires a lower number of samples compared to the traditional extrapolation-based approaches.
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    PublicationOpen Access
    Power efficient beam-forming algorithm for ultra-reliable low latency millimeter-wave communications
    (Institute of Electrical and Electronics Engineers (IEEE), 2019) Department of Electrical and Electronics Engineering; Ergen, Sinem Çöleri; Mehrnia, Niloofar; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; 7211; N/A
    Achieving ultra low-latency and ultra-high reliable communications at millimeter-waves (mmWaves) is challenging due to the sensitivity of this frequency band to blockage. Different space diversity schemes based on either equal gain or beam-tracking algorithms, are proposed to cope with the significant propagation losses introduced by the blockage at mmWaves. However, equal gain algorithms suffer from the low throughput as they allocate considerable gain to the non-optimal links. On the other hand, beam-tracking algorithms suffer from the link outage as the beam-forming is redone after dropping a large amount of data. In this study we propose a new algorithm based on the prior collection of data to eliminate power consuming beam-tracking techniques while minimum diversity level ensures high received power, ultra-reliability, and low latency.
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    PublicationOpen Access
    Wireless channel modeling based on extreme value theory for ultra-reliable communications
    (Institute of Electrical and Electronics Engineers (IEEE), 2022) Department of Electrical and Electronics Engineering; Ergen, Sinem Çöleri; Mehrnia, Niloofar; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; Graduate School of Sciences and Engineering; 7211; N/A
    A key building block in the design of ultra-reliable communication systems is a wireless channel model that captures the statistics of rare events occurring due to the significant fading. In this paper, we propose a novel methodology based on extreme value theory (EVT) to statistically model the behavior of extreme events in a wireless channel for ultra-reliable communication. This methodology includes techniques for fitting the lower tail distribution of the received power to the generalized Pareto distribution (GPD), determining the optimum threshold over which the tail statistics are derived, ascertaining the optimum stopping condition on the number of samples required to estimate the tail statistics by using GPD, and finally, assessing the validity of the derived Pareto model. Based on the data collected within the engine compartment of Fiat Linea under various engine vibrations and driving scenarios, we demonstrate that the proposed methodology provides the best fit to the collected data, significantly outperforming the conventional extrapolation-based methods. Moreover, the usage of the EVT in the proposed method decreases the required number of samples for estimating the tail statistics significantly.