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

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Presentation on theme: "Green Network Project Contract Haluk Celebi Manu Dhundi Nourah Alhassoun Sushant Bhardwaj Yasser Mohammed."— Presentation transcript:

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 ρ BS : density of base stations (base station per m 2 ) ρ MU : density of mobile users Network topology is random R max : Max transmit distance (in meters) t max : 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 1.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 X max of a base station and define a maximum tolerable delay t max for each user 3. Plot average delays t avg vs. range of base station X max

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

6 II. Further Simulations : Algorithm 1 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 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


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