1. Green Network Project Contract
Haluk Celebi
Manu Dhundi
Nourah Alhassoun
Sushant Bhardwaj
Yasser Mohammed

2. General Project Description
The project deals with power consumptions femto and pico cells deployed in cellular networks.
The goal is to develop scalable sleep/awake scheduling algorithms, minimize energy consumed by base stations and maintain connectivity

3. Assumptions & Input Parameters
ρBS: density of base stations (base station per m2)
ρMU : density of mobile users
Network topology is random
Rmax: Max transmit distance (in meters)
tmax: maximum delay a mobile user (MU) can tolerate (in milliseconds)
Capacity of base station: maximum number MUs that BS can serve simultaneously
Cells can adjust their transmit distance
Blocking probability

4. Objectives: I. Initial Simulations
Define an on/off algorithm:
A base station is turned off for a fixed percentage of the total period
Poisson process (memory less feature) for turning base stations on/off
2. Define threshold distance Xmax of a base station and define a maximum tolerable delay tmax for each user
3. Plot average delays tavg vs. range of base station Xmax

5. Cont. I. Initial Simulations
4. Calculate the percentage of energy saved i) plot % of energy saved vs. tavg ii) plot % of energy saved vs. Xmax iii) plot % of energy saved/tavg vs. on/off algorithms 5. Plot the blocking rate vs. Xmax

6. II. Further Simulations : Algorithm 1
Sleep awake scheduling: Calculate the arrival rate and the probability of no arrival within the sleep time Sleep awake scheduling
Find the overlapping areas with active neighboring femto cells
Sleeping rule: Calculate the probability of a call arrival during the sleep time in a non-overlapping area
Compare the above probability and the blocking probability

7. Cont. II. Further Simulations: Algorithm 1
Femto cells advertise its sleep time to neighboring active femto cells so that overlapping areas will be reachable
When a user attempts to connect from non-overlapping area during period T:
The user waits tmax for the sleeping cell to become active
If user is not able to connect within tmax , an emergency signal is sent & the nearest active base station increases its transmission distance

8. II. Further Simulations : Algorithm 2
Schedule sleep/awake periods similar to assigning slots based on TDMA
Femto cells operate with transmission range R, but they can increase their transmission rage to 2R
The goal to assign sleep/awake slots such that there is always active femto cell within radius 2R
Assume each femto cell can communicate with neighboring cells
If a user is not able to connect any base station within R, an emergency signal is sent & the nearest active base station doubles its transmission distance
A similar algorithm to distributed TDMA scheduling algorithms will be used

9. Simulation Tool: MATLAB
Baseline step: generate a program which takes into consideration the followings:
Random positioning of the femto cells
The location of the mobile users
The max transmission distance of the base stations
The max delay time The base station positioning
Mobile users can be generated randomly in MATLAB using plot functions
Different active and sleeping base stations
Power usage calculation of the entire system depending on the number of transmissions that take place
Plot the desired graphs and find the optimal time delay and transmit distance from this simulation
The next phase of the project: a similar set up with the sleep- awake scheduling of the base stations is being altered to find power saving mechanisms

10. Time Schedule Weeks 4-6 : Objective I and Simulation
Weeks 7-10 : Objective II
Weeks 11 : Documentation and Presentation

11. Q & A