HANDBOOK ON GREEN INFORMATION AND
COMMUNICATION SYSTEMS
Constrained Green Base Station Deployment with
Resource Allocation in 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
1
Introduction
• Energy Sources
– Renewable Energy
• Repeatedly replenished
• Examples: hydropower, biomass
– Non-renewable Energy:
• Once depleted, no more available
• Examples: coal, natural gas
2
Introduction
• Green Energy
– Eco-friendly renewable energy
– Example: wind, solar
3
Introduction
• Green Wireless Communication Networks
– WLAN mesh network structure
4
Introduction
• Projects
– EARTH
• Energy Aware
Radio and neTwork
tecHnologies
– PERANET
– GREENRADIO
5
Outline
• Introduction
• Literature Review
• System Model
• Problem Formulation
• TCGBP Algorithm
• Numerical Results
• Conclusion & Future Work
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
[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.
7
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.
8
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.
9
Outline
• Introduction
• Literature Review
• System Model
• Problem Formulation
• TCGBP Algorithm
• Numerical Results
• Conclusion & Future Work
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
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
12
Outline
• Introduction
• Literature Review
• System Model
• Problem Formulation
• TCGBP Algorithm
• Numerical Results
• Conclusion & Future Work
13
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
14
Problem Formulation
• Initialization:
• Output:
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
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
17
Outline
• Introduction
• Literature Review
• System Model
• Problem Formulation
• TCGBP Algorithm
• Numerical Results
• Conclusion & Future Work
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
19
TCGBP Algorithm
• First Phase
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
21
TCGBP Algorithm
• Second Phase
22
TCGBP Algorithm
Phase II
Phase I
23
TCGBP Algorithm
24
Outline
• Introduction
• Literature Review
• System Model
• Problem Formulation
• TCGBP Algorithm
• Numerical Results
• Conclusion & Future Work
25
Numerical Results
• Simulation Configurations
Parameter
Value
WLAN mesh networks
100 m × 100 m
Transmission power levels
10 dBm, 15 dBm, 20 dBm
Charging capability
[20, 30] mW per slot
Time duration
1000 slots
Channel bandwidth
40 MHz
Path loss exponent
4
Background noise
-20 dBm
26
Numerical Results
Different numbers of users and traffic demands
27
Numerical Results
Different numbers of candidate locations and charging capabilities
28
Outline
• Introduction
• Literature Review
• System Model
• Problem Formulation
• TCGBP Algorithm
• Numerical Results
• Conclusion & Future Work
29
Conclusion
• Green energy sources
• Formulate an optimal green BS placement
problem
• Propose TCGBP algorithm
– Approach the optimal solution with significantly
reduced time complexity
30
Future Work
• Study the impacts of dynamics in the energy
charging and discharging process
• Analyze the network capacity bounds under
different deployment strategies
31