Huawei Service Presentation by PItEY5iY

VIEWS: 10 PAGES: 34

									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] Trafficscheduling
             •   [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

								
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