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HANDBOOK ON GREEN INFORMATION AND COMMUNICATION SYSTEMS Chapter 16. Base Station Deployment and Resource Allocation in Sustainable Wireless Networks. 1 Zhongming Zheng, 1 Shibo He, 2 Lin X. Cai, and 1 Xuemin (Sherman) Shen 1 Department of Electrical and Computer Engineering
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HANDBOOK ON GREEN INFORMATION AND COMMUNICATION SYSTEMS Chapter 16 Base Station Deployment and Resource Allocation in Sustainable Wireless Networks 1Zhongming Zheng, 1Shibo He, 2Lin X. Cai, and 1Xuemin (Sherman) Shen 1Department of Electrical and Computer Engineering University of Waterloo 2School of Engineering and Applied Science Princeton University
Outline • Introduction • Literature Review • System Model • Problem Formulation • TCGBP Algorithm • Numerical Results • Conclusion & Future Work
Introduction • Energy Sources • Renewable Energy • Repeatedly replenished • Examples: wind, solar • Non-renewable Energy: • Once depleted, no more available • Examples: coal, natural gas
Introduction • Green Wireless Communication Networks • WLAN mesh network structure
Outline • Introduction • Literature Review • System Model • Problem Formulation • TCGBP Algorithm • Numerical Results • Conclusion & Future Work
Literature Review • Device Design • PV systems • [1] Probabilistic methods • [2] Simulation model • Energy charging and discharging models • [3] Battery/energy buffer • [4] Power consumption model of BSs [1] H. A. M. Maghraby, M. H. Shwehdi, and G. K. Al-Bassam, “Probabilistic assessment of photovoltaic (pv) generation systems,” Power Systems, IEEE Transactions on, vol. 17, no. 1, pp. 205–208, Feb. 2002. [2] E. Lorenzo and L. Navarte, “On the usefulness of stand-alone pv sizing methods,” Progress in Photovoltaics: Research and Applications, vol. 8, no. 4, pp. 391–409, Aug. 2000. [3] L. X. Cai, Y. Liu, H. T. Luan, X. Shen, J. W. Mark, and H. V. Poor, “Adaptive resource management in sustainable energy powered wireless mesh networks,” in IEEE Globecom, Houston, TX, USA, Dec. 5-9 2011, pp. 1–5. [4] O. Arnold, F. Richter, G. Fettweis, and O. Blume, “Power consumption modeling of different base station types in heterogeneous cellular networks,” in Future Network & Mobile Summit, Florence, IT, Jun. 16-18 2010, pp. 1–8.
Literature Review • Minimal Device Deployment • Continuous Case • Direct search • [5] Quasi-Newton methods • Discrete Case • [6] Sustainability • [7] Outage free [5] G. L. Z. Wei and L. Qi, “New quasi-newton methods for unconstrained optimization problems,” Applied Mathematics and Computation, vol. 175, no. 2, pp. 1156–1188, Apr. 2006. [6] Z. Zheng, L. X. Cai, M. Dong, X. Shen, and H. V. Poor, “Constrained energyaware ap placement with rate adaptation in wlan mesh networks,” in IEEE GLOBECOM, Houston, TX, USA, Dec. 5-9 2011, pp. 1–5. [7] S. A. Shariatmadari, A. A. Sayegh, and T. D. Todd, “Energy aware basestation placement in solar powered sensor networks,” in IEEE WCNC, Sydney, AUS, Apr. 18-21 2010, pp. 1–6.
Literature Review • Resource Allocation • Scheme Design • [8] Traffic scheduling • [9] Admission control and routing • [10] Power control [8] A. A. Hammad, G. H. Badawy, T. D. Todd, A. A. Sayegh, and D. Zhao, “Traffic scheduling for energy sustainable vehicular infrastructure,” in IEEE GLOBECOM, Miami, FL, USA, Dec. 6-10 2010, pp. 1–6. [9] L. Lin, N. B. Shroff, and R. Srikant, “Asymptotically optimal energy-aware routing for multihop wireless networks with renewable energy sources,” Networking, IEEE/ACM Transactions on, vol. 15, no. 5, pp. 1021–1034, Oct. 2007. [10] A. Farbod and T. D. Todd, “Resource allocation and outage control for solarpowered wlan mesh networks,” Mobile Computing, IEEE Transactions on, vol. 6, no. 8, pp. 960–970, Aug. 2007.
Outline • Introduction • Literature Review • System Model • Problem Formulation • TCGBP Algorithm • Numerical Results • Conclusion & Future Work
System Model • Given a set of BSs, users and candidate locations • All users are associated with a BS • BSs are powered by renewable energy • BSs and users may have different power levels of charging and transmission • In a WLAN, BS and its associated users use the same transmission power
System Model • No inter-WLAN interference with orthogonal channels assigned to BSs for inter-WLAN communication • BSs can only be placed at a given set of candidate locations • BSs at different candidate locations have different charging capabilities
Outline • Introduction • Literature Review • System Model • Problem Formulation • TCGBP Algorithm • Numerical Results • Conclusion & Future Work
Problem Formulation The number of deployed BSs Full coverage & Each user is associated with only one BS Achieved throughput ≥ Traffic demand Harvested energy ≥ Consumed energy
Problem Formulation • Initialization: • Output:
Problem Formulation • Problem Analysis • Minimal BS placement problem with power allocation • NP-hard problem • Sub-problems are NP-hard • Optimal placement of BSs with a fixed power • Power allocation of BSs
Problem Formulation • Algorithm Design Strategy • NP-hard → No solution in polynomial time • Design an effective heuristic algorithm • Achieve good performance • Reduce the time complexity
Outline • Introduction • Literature Review • System Model • Problem Formulation • TCGBP Algorithm • Numerical Results • Conclusion & Future Work
TCGBP Algorithm • First Phase • Partition the whole network region into several VPs (Voronoi Polygons) • Place one BS in each candidate location • Connect users to the BS in the same VP region
TCGBP Algorithm • First Phase
TCGBP Algorithm • Second Phase • Connect BSs and users in neighboring VP regions until constraints can not be held • Return the result when all users are connected
TCGBP Algorithm • Second Phase
TCGBP Algorithm Phase II Phase I
Outline • Introduction • Literature Review • System Model • Problem Formulation • TCGBP Algorithm • Numerical Results • Conclusion & Future Work
Numerical Results • Simulation Configurations
Numerical Results Different numbers of users and traffic demands
Numerical Results Different numbers of candidate locations and charging capabilities
Outline • Introduction • Literature Review • System Model • Problem Formulation • TCGBP Algorithm • Numerical Results • Conclusion & Future Work
Conclusion • Green energy sources • Formulate an optimal green BS placement problem • Propose TCGBP algorithm • Approach the optimal solution with significantly reduced time complexity
Future Work • Study the impacts of dynamics in the energy charging and discharging process • Analyze the network capacity bounds under different deployment strategies