Modeling heterogeneous network interference

By Robert W. Heath, Marios Kountouris. Information Theory and Applications Workshop, 2012

337 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/b766ec3c3e4df44fd24e7b1a27a4aef22b59f543

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In Aerospace Engineering

In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Power Control for D2D Underlaid Cellular Networks: Modeling, Algorithms, and Analysis (2013, methodology): “(22) Since (22) is complicated and gives little insight, we use th Gamma approximation for the distribution of p0|hk,0|(2)d −α k,0 inspired by [26] as in the following lemma.”
Downlink Cellular Network Analysis With Multi-Slope Path Loss Models (2014, background): “,[2], [19]–[21], and with experimental support seen in [22].”
On Stochastic Geometry Modeling of Cellular Uplink Transmission With Truncated Channel Inversion Power Control (2014, background): “Therefore, power control is not crucial1 for the network operation, and hence, power control is ignored in most of the stochastic geometry models on downlink cellular networks and it is generally assumed that all the BSs in the same tier transmit with equal power [1]–[3], [9]–[14].”
Coverage and Rate Analysis for Millimeter-Wave Cellular Networks (2014, background): “There have been several extensions of the results in [16], such as analyzing a multi-tier network in [1 8] and predicting the site-specific performance in heterogene ous networks in [19].”
Stochastic Geometry for Modeling, Analysis, and Design of Multi-Tier and Cognitive Cellular Wireless Networks: A Survey (2013, methodology): “Since the interference characterization technique used in [24], [73], [74] is limited to channel power gains that can be represented in the form of (9), in [75], the authors proposed the gamma distribution (i.”