Stochastic Geometry for Wireless Networks

By Martin Haenggi. 2012

2,198 citations recorded by the source corpus.

Subfields: Applied Mathematics, Discrete Mathematics and Combinatorics, Electrical and Electronic Engineering

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Citations in the corpus

Scheduling Policies for Federated Learning in Wireless Networks (2019, methodology): “As such, by applying Slivnyak’s theorem to the stationary PPP of APs, it is sufﬁcient to evaluate the SINR of a typical AP at the origin [33], [34].”
Low Power Wide Area Network Analysis: Can LoRa Scale? (2016, methodology): “Namely, we leverage tools from Stochastic Geometry [8] to address two independent linkoutage conditions, one concerned with SNR, and the other with co-spreading factor interference.”
Wireless Information and Power Transfer in Cooperative Networks With Spatially Random Relays (2014, background): “…three different strategies to use the available relays are studied, and we demonstrate that a more sophisticated relay selection strategy can ensure better reception reliability, albeit with a price of more system overhead to realize the required channel state information (CSI) assumption.”
A Survey on Scalable LoRaWAN for Massive IoT: Recent Advances, Potentials, and Challenges (2022, methodology): “This is also known as GWs densification, which has been studied considering the LoRa communication channel models [161], [162] while designing realistic coverage probability derived from stochastic geometry tools [151].”
Nonorthogonal Multiple Access in Large-Scale Underlay Cognitive Radio Networks (2016, methodology): “A bounded path-loss model is used to ensure that the path loss is always larger than 1 even for small distances [2], [9].”
Modeling and Analysis of Cellular Networks Using Stochastic Geometry: A Tutorial (2016, background): “On the other hand, if the PP is stationary but spatial ergodicity does not hold, then the expectation is done w.r.t. the Palm distribution of the PP [142] and the result is location independent.”
A General MIMO Framework for NOMA Downlink and Uplink Transmission Based on Signal Alignment (2015, methodology): “As a result, the expectation of Q1 with respect to Im′ can be expressed as follows [24], [27]:”
Tractable Resource Management With Uplink Decoupled Millimeter-Wave Overlay in Ultra-Dense Cellular Networks (2015, methodology): “Appying the nearest BS distance distribution [46],”
Millimeter Wave Cellular Networks: A MAC Layer Perspective (2015, methodology): “We consider a typical UE at the origin and evaluate the performance metric from its perspective, thanks to Slivnyak’s Theorem [25, Theorem 8.1] applied to the Poisson point processes.”
Modeling and Analyzing Millimeter Wave Cellular Systems (2016, background): “One promising approach to compute the uplink interference distribution is to extend the approach in [143] that models uplink interferers as a non-homogeneous PPP in Sub-6GHz heterogeneous networks.”
Unmanned Aerial Vehicle With Underlaid Device-to-Device Communications: Performance and Tradeoffs (2015, background): “In this network, the users are divided into two groups: downlink users located uniformly in the cell with density λdu (number of users per m2), and D2D users whose distribution follows a homogeneous Poisson point process (PPP) B [22] with density λd (number of D2D pairs per m2).”
Downlink Cellular Network Analysis With Multi-Slope Path Loss Models (2014, background): “By the mapping theorem [37], it is easy to show that for any homogeneous PPP Φ ⊂ R with intensity λ, f(Φ) is also a homogeneous PPP on R with intensity λ/a.”
User-Centric Mobility Management in Ultra-Dense Cellular Networks under Spatio-Temporal Dynamics (2016, background): “The last step comes from the mapping theorem [11].”
URLLC-eMBB Slicing to Support VR Multimodal Perceptions over Wireless Cellular Systems (2018, methodology): “Applying the probability generating functional (PGFL) of a stationary PPP Φo [19], we obtain the integral expression”
Downlink Coverage Analysis for a Finite 3-D Wireless Network of Unmanned Aerial Vehicles (2017, background): “The outage probability for this reference receiver is then derived assuming that it is served by a reference transmitter located at a ﬁxed distance (not a part of the BPP).”
On Stochastic Geometry Modeling of Cellular Uplink Transmission With Truncated Channel Inversion Power Control (2014, methodology): “According to Slivnyak’s theorem [4], the analysis holds for a generic BS located at a generic location.”
Stochastic Geometry for Modeling, Analysis, and Design of Multi-Tier and Cognitive Cellular Wireless Networks: A Survey (2013, background): “In this article, we will not go into the details of how to derive the LT, CF, or MGF for the aggregate interference associated with the PP of interest as they are well explained in the literature [11], [13], [14], [25], [27].”
Ultra-Dense Networks: A Survey (2016, methodology): “In this section, we focus on two of the most commonly used modelling techniques, namely, stochastic geometry [44] and game theory [45].”
Stochastic Geometric Coverage Analysis in mmWave Cellular Networks With Realistic Channel and Antenna Radiation Models (2018, methodology): “It is additionally because I i and of I N i are mutually independent owing to the Markov property for the PPPs Φi and Φ N i [29].”