WHEN THE SMART GRID MEETS ENERGY-EFFICIENT COMMUNICATIONS: GREEN WIRELESS CELLULAR NETWORKS POWERED BY THE SMART GRID

Transcription

1 WHEN THE SMART GRID MEETS ENERGY-EFFICIENT COMMUNICATIONS: GREEN WIRELESS CELLULAR NETWORKS POWERED BY THE SMART GRID Authors S. Bu, F. R. Yu, Y. Cai, and X. P. Liu IEEE Transactions on Wireless Communications, Aug. 2012

2 Outline 2 1. Introduction 2. System Model 3. Problem Formulation 4. Analysis of the Proposed Two level Game 5. Simulation Results and Discussions 6. Conclusion

3 1. Introduction 3 Green Communications Network Design Objectives: 1. Reduce the amount of energy consumption by the networks BSs 2. Maintain a satisfactory QoS for the users Motivations for Green Radio Communications Energy Consumption Service Provider s Financial Considerations - Half of annual operating expenses are energy costs Environmental Considerations - Currently, 2% of CO2 emissions from telecom.

4 1. Introduction Cont. 4 Solutions for Energy Aware Infrastructure Renewable Energy Sources - Reduce CO2 emissions by using renewable energy - Reliability issues Heterogeneous Cell Sizes - Macro-cells Femto-cells - Balance of different cell sizes is required Dynamic Planning - Exploit traffic load fluctuations - Switch off available resources at light traffic load

5 1. Introduction Cont. 5 Temporal fluctuations in traffic load Resources on-off Switching Radio transceivers of active BSs Entire BS switch-off

6 1. Introduction Cont. 6 Dynamic planning challenges Service Provision Guarantee Increase cell radii - Coverage holes & inter-cell Interference Relaying mechanism - Unreliable for delay sensitive applications Network cooperation - Alternately switch on-off resources CoMP Extend BSs coverage area Ensure service quality for users in off cells

7 1. Introduction Cont. 7 Wireless Cellular Network Powered by the Smart Grid Consider not only energy efficient communications but also the dynamics of the smart grid in designing green wireless cellular networks Novelty Dynamic operation of BSs depends on: traffic, real time electricity price provided by SG, and pollutant level associated with electricity generation Active BSs decide on which retailers to procure electricity from and how much electricity to procure, considering the pollutant level of each retailer and the price offered by the retailer

8 Outline 8 1. Introduction 2. System Model 3. Problem Formulation 4. Analysis of the Proposed Two level Game 5. Simulation Results and Discussions 6. Conclusion

9 2. System Model 9 Cellular network powered by the smart grid Real-time pricing DSM in SG CoMP & service blocking BSs electricity consumption

10 2. System Model Cont. 10 A. Real time pricing DSM: Dynamic pricing: effective DSM strategy to encourage users to consume electricity more wisely Electricity market liberalization: retailers compete with each other and aim to achieve the highest individual profits by adjusting the price offered to users in each region Real time pricing: prices offered by retailers change frequently to reflect variations in the cost of the energy supply

11 2. System Model Cont. 11 B. CoMP Communication: BSs are turned off when traffic is low, real time price is too high, or pollutant level of the electricity retailer is too high CoMP is used among active BSs to guarantee the coverage requirements Assume i BSs in each CoMP cooperation cluster All possible combinations of BSs in the cluster are 2 i,

12 2. System Model Cont. 12 C. Service Blocking: The uplink sum capacity for the cluster is given by Identity matrix Terminal power Channel matrix The number of channel available in cluster is given by BW allocated for each CoMP cluster Effective BW required for service, considers packetlevel QoS (delay, loss)

13 2. System Model Cont. 13 Service blocking probability in each cluster is given by Traffic arrival rate Average service rate Relationship between service blocking probability and a combination set is given by

14 2. System Model Cont. 14 D. BSs Electricity Consumption Model: Active BS energy consumption is given by Backhaul Power Req. BS Transmission Power Signal Processing Power Account for antenna setting, carrier freq. Path loss exponent Inter-site distance Base line signal processing per BS

15 2. System Model Cont. 15 Active BS energy consumption is summarized as

16 Outline Introduction 2. System Model 3. Problem Formulation 4. Analysis of the Proposed Two level Game 5. Simulation Results and Discussions 6. Conclusion

17 3. Problem Formulation 17 Two steps: 1. Each retailer in the smart grid provides the real-time price to the BSs in each cluster 2. Each cluster decides how many BSs turned on, and how much electricity to procure from each retailer Stackelberg Game Leaders Followers Each retailer in the SG SG level Game Cellular network level Game BSs in one cluster

18 3. Problem Formulation Cont. 18 A. Cellular Network Level Game: BSs Obj.: obtain the lowest service blocking probability with least possible costs BSs decide, to maximize a net utility: 1. How many BSs will be active in a cluster? 2. How much electricity is procured from each retailer?

19 3. Problem Formulation Cont. 19 Net utility of all BSs in a cluster: Service blocking utility function Total electricity cost Total pollutant level BSs Optimization Problem:

20 3. Problem Formulation Cont. 20 B. Smart Grid Level Game: Retailer n utility function is given as: Retailer n Optimization Problem:

21 Outline Introduction 2. System Model 3. Problem Formulation 4. Analysis of the Proposed Two level Game 5. Simulation Results and Discussions 6. Conclusion

22 4. Analysis of the Proposed Game 22 Refer to paper for proof of: 1. Existence; and 2. Uniqueness of the Stackelberg equilibrium A. Analysis of Cellular Network Level Game: Find Lagrangian of the cellular network optimization problem Find derivative of the Lagrangian w.r.t. the electricity quantity and equate it to zero

23 4. Analysis of the Proposed Game Cont. 23 B. Analysis of Smart Grid Level Game: Solve for Iteration Step size =

24 Outline Introduction 2. System Model 3. Problem Formulation 4. Analysis of the Proposed Two level Game 5. Simulation Results and Discussions 6. Conclusion

25 25 5. Simulation Results & Discussions

26 26 5. Simulation Results & Discussions Cont.

27 27 5. Simulation Results & Discussions Cont.

28 28 5. Simulation Results & Discussions Cont.

29 Outline Introduction 2. System Model 3. Problem Formulation 4. Analysis of the Proposed Two level Game 5. Simulation Results and Discussions 6. Conclusion

30 6. Conclusion 30 How the cellular network dynamic operation based on traffic arrival rate, electricity real-time price, and pollutant levels of retailers can reduce the operational expenditure and pollution level CoMP is used to extend BSs coverage area and reduce blocking probability for the off-cells Stackelberg game formulation