Introduction to Meta Distribution
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Meta Distribution sentence examples within fine grained information
This work studies the meta distribution in a partial-NOMA network to obtain fine-grained information about the network performance.
This work studies the meta distribution in a partial-NOMA network to obtain fine-grained information about the network performance.
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In order to obtain fine-grained information on the coverage performance, the meta distribution (MD) of signal-to-interference-to-noise ratio (SINR) is adopted for network performance evaluation, which provides the probability that certain percentage of satellite-relays-user links are able to reach a target SINR threshold.
In order to obtain fine-grained information on the coverage performance, the meta distribution (MD) of signal-to-interference-to-noise ratio (SINR) is adopted for network performance evaluation, which provides the probability that certain percentage of satellite-relays-user links are able to reach a target SINR threshold.
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Meta Distribution sentence examples within interference plus noise
By combining stochastic geometry with queueing theory, two fundamental measures are analyzed, namely the transmission success probability and the meta distribution of signal-to-interference-plus-noise ratio (SINR).
By combining stochastic geometry with queueing theory, two fundamental measures are analyzed, namely the transmission success probability and the meta distribution of signal-to-interference-plus-noise ratio (SINR).
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This work studies the signal-to-interference-plus-noise ratio (SINR) meta distribution (MD) in cellular networks with a focus on the Poisson model.
This work studies the signal-to-interference-plus-noise ratio (SINR) meta distribution (MD) in cellular networks with a focus on the Poisson model.
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Meta Distribution sentence examples within downlink non orthogonal
In this letter, the Meta distributions (MDs) of the secrecy rate in downlink non-orthogonal multiple access (NOMA) systems with randomly located eavesdroppers are investigated.
In this letter, the Meta distributions (MDs) of the secrecy rate in downlink non-orthogonal multiple access (NOMA) systems with randomly located eavesdroppers are investigated.
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We study the meta distribution (MD) of the coverage probability (CP) in downlink non-orthogonal-multiple-access (NOMA) networks.
We study the meta distribution (MD) of the coverage probability (CP) in downlink non-orthogonal-multiple-access (NOMA) networks.
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Meta Distribution sentence examples within non orthogonal multiple
This paper presents the meta distribution analysis of the downlink two-user non-orthogonal multiple access (NOMA) in cellular networks.
This paper presents the meta distribution analysis of the downlink two-user non-orthogonal multiple access (NOMA) in cellular networks.
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Meta Distribution sentence examples within Sinr Meta Distribution
Under a general Nakagami fading model, we derive the upper bounds for the $b$ -moments of the conditional signal-to-interference-noise ratio (SINR) distributions for the two modes given the network realization, and further calculate the upper bounds of SINR meta distributions (MDs).
Under a general Nakagami fading model, we derive the upper bounds for the $b$ -moments of the conditional signal-to-interference-noise ratio (SINR) distributions for the two modes given the network realization, and further calculate the upper bounds of SINR meta distributions (MDs).
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We derive a tractable expression for the SINR meta distribution, and verify its accuracy via simulations.
We derive a tractable expression for the SINR meta distribution, and verify its accuracy via simulations.
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10.1109/VTC2021-Spring51267.2021.9448956
We use the concept of meta distribution (MD) of the signal-to-interference ratio (SIR) to gain a complete understanding of the per-link reliability and describe the performance of two scheduling methods for data aggregation of machine type communication (MTC): random resource scheduling (RRS) and channel-aware resource scheduling (CRS).
We use the concept of meta distribution (MD) of the signal-to-interference ratio (SIR) to gain a complete understanding of the per-link reliability and describe the performance of two scheduling methods for data aggregation of machine type communication (MTC): random resource scheduling (RRS) and channel-aware resource scheduling (CRS).
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10.1109/LCOMM.2020.3041221
In contrast to the conventional performance analysis based on the coverage probability, the distribution of the conditional coverage probability (CCP), which is called signal-to-interference ratio (SIR) meta distribution, is investigated by considering the random location of the nodes as well as the underlying channel.
In contrast to the conventional performance analysis based on the coverage probability, the distribution of the conditional coverage probability (CCP), which is called signal-to-interference ratio (SIR) meta distribution, is investigated by considering the random location of the nodes as well as the underlying channel.
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10.1109/PIMRC50174.2021.9569467
Therefore, we derive the meta distribution, which is calculated directly from the moment result of the CP, and validate its correctness by Monte Carlo simulations.
Therefore, we derive the meta distribution, which is calculated directly from the moment result of the CP, and validate its correctness by Monte Carlo simulations.
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10.1109/TII.2020.3003474
In this article, we focus on the analysis of the coverage probability and the meta distribution of the signal-to-interference ratio (SIR) for a LoRaWAN uplink with fractional power control (FPC).
In this article, we focus on the analysis of the coverage probability and the meta distribution of the signal-to-interference ratio (SIR) for a LoRaWAN uplink with fractional power control (FPC).
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10.1109/LCOMM.2021.3069662
Meta distributions (MDs) have emerged as a powerful tool in the analysis of wireless networks.
Meta distributions (MDs) have emerged as a powerful tool in the analysis of wireless networks.
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10.1109/twc.2021.3089553
That holds for even a simple average-based performance metric—the success probability, which is a special case of the fine-grained metric, the meta distribution (MD) of the signal-to-interference ratio (SIR).
That holds for even a simple average-based performance metric—the success probability, which is a special case of the fine-grained metric, the meta distribution (MD) of the signal-to-interference ratio (SIR).
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10.1109/LWC.2021.3074399
The meta distribution (MD) of the signal to interference ratio (SIR) extends stochastic geometry analysis from spatial averages to reveals find-grained information about the network performance.
The meta distribution (MD) of the signal to interference ratio (SIR) extends stochastic geometry analysis from spatial averages to reveals find-grained information about the network performance.
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10.1109/TCOMM.2018.2890247
In this paper, we apply the signal-to-interference ratio (SIR) meta distribution framework for a refined SIR performance analysis of HCNs, focusing on <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>-tier heterogeneous cellular networks based on the homogeneous independent Poisson point process (PPP) model, with range expansion bias (offloading bias) in each tier.
In this paper, we apply the signal-to-interference ratio (SIR) meta distribution framework for a refined SIR performance analysis of HCNs, focusing on <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>-tier heterogeneous cellular networks based on the homogeneous independent Poisson point process (PPP) model, with range expansion bias (offloading bias) in each tier.
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10.1109/TCOMM.2019.2940659
The meta distribution of the signal-to-interference-ratio (SIR) is an important performance indicator for wireless networks because, for ergodic point processes, it describes the fraction of scheduled links that achieve certain reliability, conditionally on the point process.
The meta distribution of the signal-to-interference-ratio (SIR) is an important performance indicator for wireless networks because, for ergodic point processes, it describes the fraction of scheduled links that achieve certain reliability, conditionally on the point process.
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10.1109/ICC.2019.8761082
This paper characterizes the meta distribution of the downlink signal-to-interference ratio (SIR) attained at a typical Internet-of-Things (IoT) device in a dual-hop IoT network.
This paper characterizes the meta distribution of the downlink signal-to-interference ratio (SIR) attained at a typical Internet-of-Things (IoT) device in a dual-hop IoT network.
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10.1109/LWC.2019.2912614
The meta distribution (MD) of the signal-to-interference ratio (SIR) provides fine-grained reliability performance in wireless networks modeled by point processes.
The meta distribution (MD) of the signal-to-interference ratio (SIR) provides fine-grained reliability performance in wireless networks modeled by point processes.
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10.1109/GLOBECOM38437.2019.9013286
With the pcf in hand, we provide the tightest known approximation of the point process of interfering BSs as seen by the typical user of Type I process, which is used to derive remarkably tight expressions for the moments of the downlink signal-to-interference- ratio (SIR) meta distribution for the typical cell.
With the pcf in hand, we provide the tightest known approximation of the point process of interfering BSs as seen by the typical user of Type I process, which is used to derive remarkably tight expressions for the moments of the downlink signal-to-interference- ratio (SIR) meta distribution for the typical cell.
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10.1109/JSAC.2018.2872373
This paper considers a WEIT-enabled device-to-device (D2D) network with the ambient RF transmitters distributed according to a Poisson point process and focuses on the meta distribution of the transferred energy, which is the distribution of the conditional energy outage probability given the locations of the RF transmitters, to show what fraction of devices in the network satisfy the target energy outage constraint if the required transmission energy is given.
This paper considers a WEIT-enabled device-to-device (D2D) network with the ambient RF transmitters distributed according to a Poisson point process and focuses on the meta distribution of the transferred energy, which is the distribution of the conditional energy outage probability given the locations of the RF transmitters, to show what fraction of devices in the network satisfy the target energy outage constraint if the required transmission energy is given.
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