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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.

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Presentation on theme: "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."— Presentation transcript:

1 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 University of Waterloo 2 School of Engineering and Applied Science Princeton University HANDBOOK ON GREEN INFORMATION AND COMMUNICATION SYSTEMS Chapter 16

2 1 Introduction Literature Review System Model Problem Formulation TCGBP Algorithm Numerical Results Conclusion & Future Work Outline

3 Introduction Energy Sources –Renewable Energy Repeatedly replenished Examples: wind, solar –Non-renewable Energy: Once depleted, no more available Examples: coal, natural gas 2

4 Introduction Green Wireless Communication Networks – WLAN mesh network structure 3

5 4 Introduction Literature Review System Model Problem Formulation TCGBP Algorithm Numerical Results Conclusion & Future Work Outline

6 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 5 [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 [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 [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 , 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 , pp. 1–8.

7 Literature Review Minimal Device Deployment –Continuous Case Direct search [5] Quasi-Newton methods –Discrete Case [6] Sustainability [7] Outage free 6 [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 [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 , 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 , pp. 1–6.

8 Literature Review Resource Allocation –Scheme Design [8] Traffic scheduling [9] Admission control and routing [10] Power control 7 [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 , 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 [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

9 8 Introduction Literature Review System Model Problem Formulation TCGBP Algorithm Numerical Results Conclusion & Future Work Outline

10 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 9

11 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 10

12 11 Introduction Literature Review System Model Problem Formulation TCGBP Algorithm Numerical Results Conclusion & Future Work Outline

13 Problem Formulation 12 The number of deployed BSs Full coverage & Each user is associated with only one BS Achieved throughput Traffic demand Harvested energy Consumed energy

14 Problem Formulation Initialization: Output: 13

15 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 14

16 Problem Formulation Algorithm Design Strategy –NP-hard No solution in polynomial time –Design an effective heuristic algorithm Achieve good performance Reduce the time complexity 15

17 16 Introduction Literature Review System Model Problem Formulation TCGBP Algorithm Numerical Results Conclusion & Future Work Outline

18 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 17

19 TCGBP Algorithm First Phase 18

20 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 19

21 TCGBP Algorithm Second Phase 20

22 TCGBP Algorithm 21 Phase II Phase I

23 TCGBP Algorithm 22

24 23 Introduction Literature Review System Model Problem Formulation TCGBP Algorithm Numerical Results Conclusion & Future Work Outline

25 Numerical Results Simulation Configurations 24 ParameterValue WLAN mesh networks100 m × 100 m Transmission power levels10 dBm, 15 dBm, 20 dBm Charging capability[20, 30] mW per slot Time duration1000 slots Channel bandwidth40 MHz Path loss exponent4 Background noise-20 dBm

26 Numerical Results Different numbers of users and traffic demands 25

27 Numerical Results Different numbers of candidate locations and charging capabilities 26

28 27 Introduction Literature Review System Model Problem Formulation TCGBP Algorithm Numerical Results Conclusion & Future Work Outline

29 Conclusion Green energy sources Formulate an optimal green BS placement problem Propose TCGBP algorithm –Approach the optimal solution with significantly reduced time complexity 28

30 Future Work Study the impacts of dynamics in the energy charging and discharging process Analyze the network capacity bounds under different deployment strategies 29

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