EE6151: Advanced Topics in Networks

Instructor: RadhaKrishna Ganti

Slot: E

Contact Information:

• Phone:   2257-4467
• Email:  rganti [at] ee . iitm . ac . in
• Office: ESB 208D

 Course Description: This course will provide a basic introduction to stochastic geometry and its application to the analysis of wireless networks. The initial part of the course will be  point processes and in particular, spatial Poisson point process. The second part of the course will be about applications to Wireless networks.

Time  permitting, we will also look at Erdos Reyni graphs and develop martingale tools for their analysis.

The course is only for graduate students and will involve lot of paper reading and presentations.

Reference Textbooks:

1. Stochastic geometry for wireless networks, Martin Haenggi

Prerequisites: Basic probability

Course Contents:

• Introduction
• Foundations

• Definition and probability spaces
• Product densities and moment measures
• Examples
• Stationarity
• Sums over PP
• Products over PP

• Spatial Poisson point process

• Properties and characterization
• PGFL

• Palm distribution

• Campbell-Mecke
• Slivinak theorem
• Second-order moment measure.
• Ergodicity

• Examples and properties of other point processes

• Cluster pp
• Determinantal
• Matern

• Interference modelling

• Mean and moments
• Laplace transform
• Spatio-temporal correlation

• Outage probability in spatial PPP (ad hoc)

• Single antenna
• Multiple antenna
• General fading distributions
• Power control

• Modelling of cellular networks

• Uplink, downlink, Mimo, Mu-mimo, FFR, Mobility

• Modelling of Heterogeneous networks

• Connectivity models
• Coverage
• Mobility

• Erdos Reyni graphs.