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Green Network Project Contract. Haluk Celebi Manu Dhundi Nourah Alhassoun Sushant Bhardwaj Yasser Mohammed. General Project Description. The project deals with power consumptions femto and pico cells deployed in cellular networks.
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Green Network Project Contract HalukCelebi Manu Dhundi Nourah Alhassoun SushantBhardwaj Yasser Mohammed
General Project Description • The project deals with power consumptions femto and picocells deployed in cellular networks. • The goal is to develop scalable sleep/awake scheduling algorithms, minimize energy consumed by base stations and maintain connectivity
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
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 Xmaxof a base station and define a maximum tolerable delay tmax for each user 3. Plot average delays tavgvs. range of base station Xmax
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
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 femtocells • Sleeping rule: Calculate the probability of a call arrival during the sleep time in anon-overlapping area • Compare the above probability and the blocking probability
Cont. II. Further Simulations: Algorithm 1 • Femtocells 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 tmaxfor 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
II. Further Simulations : Algorithm 2 Algorithm 2: • Schedule sleep/awake periods similar to assigning slots based on TDMA • Femtocells 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 algorithmswill be used
Simulation Tool: MATLAB • Baseline step: generate a program which takes into consideration the followings: • Random positioning of the femtocells • 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
Time Schedule • Weeks 4-6 : Objective I and Simulation • Weeks 7-10 : Objective II • Weeks 11 : Documentation and Presentation