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:
- Stochastic geometry for wireless networks, Martin Haenggi
Prerequisites: Basic probability
Course Contents:
- 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
- Campbell-Mecke
- Slivinak theorem
- Second-order moment measure.
- Ergodicity
- Examples and properties of other point processes
- Cluster pp
- Determinantal
- Matern
- 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