# Random Thoughts on Stochastic Geometry

## Wishful thinking

Today we are listening in to a conversation between Achill and the Turtle. Achill: I have been conducting research on the performance of wireless links for a while now, and I learnt that analyzing a fixed deterministic channel does not lead to insightful and general results. To capture a variety of channel conditions and obtain … Continue reading Wishful thinking

## Randomness decreases correlation – does it?

Intuition may tell us that increasing the randomness in the system (e.g., by increasing the variance of some random variables relative to their mean) will decrease the correlation between some random quantities of interest. A prominent example is the interference or SIR in a wireless network measured at two locations or in two time slots. … Continue reading Randomness decreases correlation – does it?

## Rayleigh fading and the PPP – part 2

The previous blog highlighted that the Rayleigh fading channel model and the Poisson deployment model are very similar in terms of their tractability and in how realistic they are. It turns out that Rayleigh fading and the PPP are the neutral cases of channel fading and node deployment, respectively, in the following sense: For Rayleigh … Continue reading Rayleigh fading and the PPP – part 2

## Rayleigh fading and the PPP

When stochastic geometry applications in wireless networking were still in their infancy or youth, I was frequently asked “Do you believe in the PPP model?”. I usually answered with a counter-question:“Do you believe in the Rayleigh fading model?”. This “answer” was motivated by the high likelihood that the person askingwas familiar with the idea of … Continue reading Rayleigh fading and the PPP

## Stochastic geometry (is) fun – part 3

This is a true story. Not 100% comic but also showing an interesting point of view.

Reviewer 2:*“This is a well-written paper. But it uses probability theory.”*

## A case for T junctions

It has been established (for example, here) that the standard two-dimensional homogeneous PPP is not an adequate model for vehicular networks, since vehicles are mostly confined to streets. The Poisson line Cox process (PLCP) has naturally emerged as the model of choice. In this process, one-dimensional PPPs are placed on a street system formed by … Continue reading A case for T junctions

## The typical user and her malfunctioning base station

Let us consider a cellular network with Poisson distributed base stations (BSs). We assume that in each Voronoi cell, one user is located uniformly at random (and independently across cells), and, naturally, the user is connected to the nucleus of that cell. This is the user point process of type I defined in this article. … Continue reading The typical user and her malfunctioning base station

## Percentage games

Let us consider a hypothetical situation where the authors of a paper promise the following: “In the next figure, we compare our Quantum Ultra-Enhanced Superior-Throughput Intelligent Objectively-Novel Adaptive Beamformed Low-Latency Emission (QUESTIONABLE) scheme with the Arbitrarily-Massive Antenna Zero-Innovation Neural Grandiloquence (AMAZING) scheme, which is the best previously known scheme. As the figure shows, the QUESTIONABLE … Continue reading Percentage games

## On cell slicing

Network slicing is a warm topic these days. Here we discuss cell slicing, where a polygon is cut in three pieces (sub-polygons) by two lines through its nucleus and a random point, respectively. First, as a sequel to this post, we focus on the 0-cell in the Poisson-Voronoi tessellation, which is the Voronoi cell of … Continue reading On cell slicing

## Stochastic geometry (is) fun – part 2

What do you tell somebody who wants to use the Palm measure but does not condition on a point at the origin?

“You are missing the point.”

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