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Energy Efficient Cellular Base Stations based on the Characteristics of Malaysia’s Solar Radiation Exposure


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Energy Efficient Cellular Base Stations based on the Characteristics of Malaysia’s Solar Radiation Exposure

  1. 1.     Ir.  Dr.  Rosdiadee  Nordin   Faculty  of  Engineering  and  Built  Environment   Universi<  Kebangsaan  Malaysia        Energy  Efficient  Cellular  Base  Sta3ons  based  on   the  Characteris3cs  of  Malaysia’s  Solar  Radia3on   Exposure   :     :    hDps://   :    hDp://­‐nordin  
  2. 2. Outline   q   Introduc<on  and  Problem  Background     q   Classifica<ons  of  Energy-­‐Saving  Techniques     q   Case  Study:  Feasibility  Study  of  Green  Wireless  Network  for  Malaysia   q   Future  Direc<ons  &  Challenges  Related  to  Green  Wireless  
  3. 3. IoT   50  Billion   Video  demand     69%   Mobile   Subscribers   9.5  Billion    -­‐          1,000      2,000      3,000      4,000      5,000      6,000      7,000     2005   2006   2007   2008   2009   2010   2011   2012   2013   Mobile-­‐cellular  subscrip3ons  in  (Million)   Introduc3on   Big  Success  of  Mobile  Communica<ons  
  4. 4.   Number  of   subscribers   increased   Mobile  data  traffic   increased   Base  sta3ons     will  be     increased   Z.   J.   Wu,   Y.   Zhang,   M.   Zukerman,   and   E.   Yung   (2015).   Energy-­‐Efficient   Base   Sta3ons   Sleep   Mode   Techniques   in   Green   Cellular   Networks:   A   Survey.   IEEE   Communica,ons  Surveys  &  Tutorials  .   Cont’d   Growth  in  Mobile  Base  Sta<ons     With  5G,  the  number  of  BSs  globally  will  grows  to  reach  approximately  8  million  by  2020.  
  5. 5. In  Malaysia,  Mobile  cellular   subscrip<ons  reached  more   than  42.9  million  in  2014  
  6. 6. Cont’d   57%   20%   15%   6%   2%   Base  sta<on   Mobile  switching   Core  network   Data  center   Retail   E.  Oh,  B.  Krishnamachari,  X.  Liu,  and  Z.  Niu  (2011).  Towards  Dynamic  Energy-­‐Efficient  Opera3on  of  Cellular  Network  Infrastructure.  IEEE  Commun.  Mag.   Ø BSs  are  densely  deployed  and  overlapping   Ø   80%  of  the  BSs  are  quite  lightly  loaded  for  80%   of  the  <me,  but  s<ll  waste  energy   Reducing  the  power   consump3on    of  BSs  is  the  key!  
  7. 7. Ø All  BSs  are  ON  (ac<ve)  all  the  <me  (to  keep  coverage),  although  traffic  is  almost  zero  in  many  areas.     Ø Each  BS  almost  transmits  in  peak  power,  although  peak  traffic  only  lasts  for  a  very  short  <me  in  most  cells   Cont’d   Why  so  many  BSs  under-­‐u3lized?   Migrate  to  Green  Communica3ons   Ø From   World-­‐Wide-­‐Web   to   World-­‐ Wide-­‐Wireless     Ø Definitely   should   not   be   World-­‐ Wide-­‐Wait  and  World-­‐Wide-­‐Waste!   Exis3ng  cellular  is  neither  smart  nor  green  
  8. 8. Ø   The  traffic  loads  during  the  day<me  differs  from  those   during  the  night  for  both  of  the  business  and  residen<al   areas.   Cont’d   Traffic  dynamics  can  provide  opportuni3es  for  energy  saving   Ø Key  challenge:  How  to  guarantee   the  coverage  and  radio  service?   Why  lightly-­‐loaded  BSs  can’t  be  switched  off  (sleep)?  
  9. 9. Green  Wireless  Cellular  Techniques   Coopera3on  Management     Coopera<ve   base  sta<ons     BSs   switching   On/Off   Cell   zooming   HetNet   Coopera<ve  mobile   operators   Operator   switching   On/Off   Hardware  Solu3ons     Improvements  PA   Renewable   energy   sources   M.   H.   Alsharif,   R.   Nordin,   and   M.   Ismail   (2014).   Classifica3on,   Recent   Advances   and   Research   Challenges   in   Energy   Efficient   Cellular   Networks.   Wireless   Personal  Communica,ons,  77  (2),  1249-­‐1269.     Classifica*ons  of  Energy-­‐Saving  Techniques  
  10. 10. Ø   BSs  Switch  Off/On   Idea   Switching  off  a  specific  number  of  BSs  during  low-­‐traffic,  while  guaranteeing   coverage  and  services  by  the  ac<ve  remaining  BSs   Savings   25-­‐50%   Advantages   Easier  and  less  costly  for  tes<ng  &  implementa<on   Shortcomings     Coverage  issue  and  UE  baDery  life.   Coopera3on  Management  Techniques   The  philosophy  behind  all  the  proposed  methods  is  the  same:  reduce  energy  consump<on  based  on  the   traffic  load.   Cont’d   The  first  research  discussed  this  technique:   L.  Chiaraviglio,  D.  Ciullo,  M.  Meo,  M.  A.  Marsan  (2008).  Energy-­‐Aware  UMTS  Access  Networks.  Proc.  in  the11th  Interna,onal  Symposium  on   Wireless  Personal  Mul,media  Communica,ons  (WPMC’08),  
  11. 11. 37.5%   50.0%   17.0%   40.7%   30.0%   30.0%   40.0%   35.0%   29.0%   0.0%   10.0%   20.0%   30.0%   40.0%   50.0%   60.0%   Chiaraviglio  et   al.,  2008,   (Residen<al)   Chiaraviglio  et   al.,  2008,   (Office)   Chiaraviglio  et   al.,  2008,   (Hierarchical)   Chiaraviglio  et   al.,  2009,   (Uniform)   Chiaraviglio  et   al.,  2009,   (Hierarchical)   Marsan  et  al.,   2009   Xiang  et  al.,   2011   Lorincz  et  al.,   2012   Bousia  et  al.,   2012   BSs  Switch  Off/On  Cont’d   M.  H.  Alsharif,  R.  Nordin,  and  M.  Ismail  (2014).  Classifica3on,  Recent  Advances  and  Research  Challenges  in  Energy  Efficient  Cellular  Networks.  Wireless  Personal   Communica,ons,  77  (2),  1249-­‐1269.     Summary  of  Switch-­‐Off  Previous  Studies  that  have  Inves<gated  the  Possibility  of  Energy  Savings  
  12. 12. Ø   Cell  Zooming   Idea   When  conges<on  occurs  in  a  cell,  the  congested  cell  could  “zoom-­‐in,”  while  neighboring  cells   with  a  smaller  amount  of  traffic  could  “zoom-­‐out”  to  provide  coverage  for  the  UEs.     Savings   Up  to  40%.   Advantages   Large  savings.   Shortcomings     Coverage  issue,  Interference,  and  Compa<bility.   Cont’d   The  first  research  discussed  this  technique:   Z.  Niu,  Y.  Wu,  J.  Gong,  and  Z.  Yang  (2010).  Cell  Zooming  for  Cost-­‐Efficient  Green  Cellular   Networks.  IEEE  Communica<ons  Magazine.     Cell  zooming  opera3ons  in  cellular  networks:     (a) Original  size;     (b) Central  cell  zooms  in  when  load  increases;   (c) Central  cell  zooms  out  when  load  decreases  
  13. 13. Ø   HetNet   Idea   Macrocells  are  deployed  to  provide  overall  coverage,  while  small  cells  (e.g.,  micro,  pico,  femto)   are  ac<vated  if  the  demand  increases.   Savings   Up  to  70%   Advantages   Largest  reported  savings.   Shortcomings     Interference,  Resource  Management,  and  Complexity.   Cont’d   The  first  research  discussed  this  technique:   H.  Claussen,  L.  T.  W.  HO,  F.  Pivit  (2008).  Effects  of  joint  macrocell  and  residen3al  picocell   deployment.  Proc.  in  the  19th  Annual  IEEE  Interna<onal  Symposium  on  Personal,  Indoor   and  Mobile  Radio  Communica<ons  (PIMRC'08)   E-UTRAN Macro Cell A   E-UTRAN Pico/Micro Cell B   Ø  Two   E-­‐UTRAN   cells   (Cell   A,   Cell   B)   with   separate   frequency  bands  cover  the  same  geographical  area.     Ø  Cell  B  has  a  smaller  size  (Pico  Cell  or  Micro  Cell)  than   Cell  A  (Macro  Cell)  and  is  covered  totally  by  Cell  A   Ø   Cell  A  is  deployed  to  provide  con<nuous  coverage  of   the  area,  while  Cell  B  increases  the  capacity  of  the   special  sub-­‐areas,  such  as  hot  spots.       Ø  Cell   B   deac<va<on   in   case   that   light   traffic.   Cell   B   ac<va<on  when  the  traffic  resumes  to  a  high  level.  
  14. 14. Ø   Coopera3ve  Mobile  Operators   Idea   Switch  off  one  or  more  BSs  when  the  traffic  load  is  low,  managing  coverage  with  a   subset  of  remaining  ac<ve  BSs  through  either  the  same  operator  network  or  another   operator,  with  both  networks  covering  the  same  geographical  area.     Savings   Depends  on  the  number  of  operators.   Advantages   A  good  exploita<on  of  the  network.   Shortcomings     Complexity  &  compa<bility,  resource  management,  QoS  &  human  factor(?)   Cont’d   The  first  research  discussed  this  technique:   M.   A.   Marsan,   M.   Meo   (2010).   Energy   efficient   wireless   Internet   access   with   coopera3ve  cellular  networks.  Computer  Networks.  
  15. 15. Renewable  Energy  System  Cont’d   M.  H.  Alsharif,  R.  Nordin,  and  M.  Ismail  (2016).  Green  wireless  network  op3misa3on  strategies  within  smart  grid  environments  for  Long  Term  Evolu3on  (LTE)   cellular  networks  in  Malaysia.  Renewable  Energy,  85,  157-­‐170.    
  16. 16. The  concept  of  using  diesel  generator  (DG)  to  power  rural  BS  has  become  much  less  viable  for   the  mobile  operators  for  the  following  reasons:     •  Fuel,  opera<ng,  and  maintenance  costs.   •  Environmental  impacts:    air  pollu<on,  emitng  harmful  components  such  as  CO2,  SO2.   •  Technical  issues:  The  efficiency  of  the  system  is  low  (30%)   Net  costs  of  opera<ng  a  diesel  generator   51%   20%   15%   14%   Mobile  Sector   Fixed  Narrowband   Telecom  Devices   Fixed  Broadband   51%  of  the  ICT   industry!     Forecast  Carbon  Footprint   Contribu<on  by  Telecom  for   2020.     Total=  179  MtCO2   Mo3va3ons  Towards  Renewable  Energy   M.  H.  Alsharif,  R.  Nordin,  and  M.  Ismail  (2015).  Energy  Op3miza3on  of  Hybrid  Off-­‐Grid  System  for  Remote  Telecommunica3on  Base  Sta3on  Deployment  in   Malaysia.  EURASIP  Journal  on  Wireless  Communica,ons  and  Networking,  2015:64.    
  17. 17. Burkina  Faso     Kenya   Angola     Arab  gulf  region   Lebanon       Nepal   India   Bangladesh   Turkey   Sri  Lanka     …  and  …       Malaysia!     Brazil   Italy   Prac*cal  Solar  Powered  Base  Sta*on   Implementa*on
  18. 18. Solar  power  system  in  remote  areas  of  Burkina  Faso     Provided  by  ZTE,  2009         hDp://<cles/200907/t20090710_173704.html  Reference:     Requirements:  power  system  is  required  to  provide  power  for  BTS   and  microwave  equipment;  the  total  power  consump<on  is  550W.       System  Design:       1.  Photovoltaic  module:  30  pieces  of  165W  monocrystalline  cells;     2.  BaDery:  Two  groups  of  2V/1000Ah  Gel  OPzV;     3.  Charge  controller:  48V/150A  controller.       In   this   project,   22   solar-­‐powered   BTSs   are   deployed.   They   have   a   rela<vely   small   capacity,   which   is   in   the   range   of   400-­‐900W.   Solar   power   system   makes   diesel   re-­‐fuelling   and   maintenance   work   unnecessary,  which  can  save  about  US$150,000  for  operator  every   year.  
  19. 19. Loca3on:   Solar   powered   base   sta<on   at   the   Italian   city   of   L'Aquila   implemented   by   Ericsson   and  Telecom  Italia.       System  Design:  The  Eco  Smart  solu<on  features   an   ellip<cal   support   structure   coated   with   flexible   solar   panels   ‘wrapping’   the   tower   structure.       1.  Solar  PV  Panels.   2.  BaDeries   3.  Solar  charge  controllers   4.  DC  power  rec<fiers   Italy,  2009   Reference:   hDp://www.cellular-­‐  
  20. 20. Solar  base  sta3ons  by  Alfa  mobile  operator  in  Lebanon,  2013   Loca3on:   five   remotes   sites,   namely   in   Hourata,   Challita,   Aakoura,   Ouyoun   Laqlouq,   and   Mehmarch,   which   are   implemented   by   ECOsys   company   that   specialist   in   solar   energy  solu<on.     System  Design:     1.  Solar  PV  Panels  from  Kyocera.   2.  BaDeries  from  EnerSys   3.  Solar  charge  controllers  from  Steca,  controlling  the  en<re   energy  flow  while  ensuring  op<mal  baDery  maintenance.   4.  DC  power  rec<fiers  from  Eaton,  designed  for  high  power   density  and  opera<ng  efficiency.           Reference:   hDp://  
  21. 21. Arab  gulf  region,  2015   Loca3on:   300   solar-­‐powered   base   sta<ons   has   deployed   in   Arab   gulf   region   implemented   by   Eltek.   In   addi<on,   200   sites   will  be  deployed  in  2015  and  2016.     System  Design:     1.  PV   panels   (Photovoltaic   Panels),   strong   and   resistant   PV   moun<ngs   2.  BaDeries   3.  Solar  controllers  &  rec<fiers     The   solu<on   design   is   based   on   full   reliability   on   solar   and   backup   baDeries,   knowing   that   on   few   sites,   unstable   u<lity   and  generators  are  available  for  addi<onal  backup.  The  baDery   autonomy  is  very  high  and  the  solu<on  can  provide  con<nuous   energy  for  5  days.   It  is  worth  men<oning,  Eltek  has  provided  solar  powered  telecom  installa<ons  across  the  African  con<nent,  in   countries  such  as  Angola,  Chad,  Kenya,  Lesotho,  Mauritania,  Morocco,  Mozambique,  Somalia,  Somaliland,  South   Africa,  Zambia  and  Zimbabwe.   Reference:   hDp://  
  22. 22. hDp://<cles/200907/t20090710_173704.html     hDp://   hDp://<cles/200406/ t20040611_161343.html     Nepal     Burkina  Faso       Arab  gulf  region   hDp://     Turkey   hDp://www.cellular-­‐     Italia   hDp://www.cellular-­‐     Sri  Lanka   hDp://www.cellular-­‐     Angola   hDp://­‐power-­‐solu<ons-­‐communica<ons     Lebanon     hDp://    
  23. 23. Prac3cal  case  in  Malaysia   Solar  BS  project  implementa<on  by:     Solar  Energy  Research  Ins<tute(SERI)   Universi<  Kebangsaan  Malaysia  (UKM)  
  24. 24. •  In   Malaysia,   total   energy   consump<on   by   Celcom   for   2014   was   820,775  GJ.  In  addi<on,  GHG  Emission  168,544  Tonnes  CO2   •  Following   are   some   of   the   key   ini<a<ves   that   are   undertaken   to   reduce  energy  consump<ons  by  Celcom  operator,   Ø  Solar  Hybrid  systems  on  the  sites  where  grid  power  is  unavailable.   Ø  Posi<oning   telecom   equipment   outdoor   to   minimise   power   consump<on   and  space  requirement.   Ø  Free  cooling  units  to  minimise  air-­‐condi<oning  requirements  on  sites.   Ø  Automa<c   TRX   shutdown   in   the   hours   when   there   is   no   traffic   detected   (non-­‐busy  hours)    
  25. 25. Case  Study:  Feasibility  Study  of  Green   Wireless  Network  for  Malaysia     Case  Study     Part  1:  Energy  op<miza<on  of  off-­‐grid  system  for  remote  LTE-­‐BS   Part  2:  Coopera<on  management  among  solar  powered  LTE-­‐BSs  for   sub-­‐urban  areas    
  26. 26. Cont’d   0   1   2   3   4   5   6   7   Jan   Feb   Mar   Apr   May   Jun   Jul   Aug   Sep   Oct   Nov   Dec   Daily  Radia3on  (kWhm2d)   Sabah   Perlis   Kedah   0   0.1   0.2   0.3   0.4   0.5   0.6   0.7   0.8   0.9   1   0   1   2   3   4   5   6   Jan   Feb   Mar   Apr   May   Jun   Jul   Aug   Sep   Oct   Nov   Dec   Clearness  Index   Daily  Radia3on  (kWhm2d)   Daily  Radia<on   Clearness  Index   Poten3al  of  Solar  in  Malaysia   M.  H.  Alsharif,  R.  Nordin,  and  M.  Ismail  (2016).  Green  wireless  network  op3misa3on  strategies  within  smart  grid  environments  for  Long  Term  Evolu3on  (LTE)   cellular  networks  in  Malaysia/.  Renewable  Energy,  85,  157-­‐170.    
  27. 27.  BS  Subsystem   Item   Nota3on   Unit   Macro   PA   Max  transmit  (rms)  power,  Pmax   W   39.8   Max  transmit  (rms)  power   dBm   46.0   PA  efficiency,  µ   %   38.8   Total  PA  (PPA)=     W   102.6   TRX   PTX   W   5.7   PRX   W   5.2   Total  RF  (PRF)   W   10.9   BB   Radio  (inner  Rx/Tx)   W   5.4   Turbo  code  (outer  Rx/Tx)   W   4.4   Processor   W   5.0   Total  BB  (PBB)   W   14.8   DC-­‐DC  loss,  σDC   %   6.0   Cooling  loss,  σcool   %   9.0   AC-­‐DC  (main  supply)  loss,  σMS   %   7.0   Total  per  TRX  =     W   160.8   Number  of  sectors   #   3   Number  of  antennas   #   2   Total  number  of  NTRX  chains,  Pin=  NTRX  ×  Total  per  TRX   W   964.9   µ maxP ( )( )( )MScoolDC BBRFPA PPP σσσ −−− ++ 111 Power  consump3on  of  the  LTE-­‐BS  hardware  elements     G  Auer,  O  Blume,  V  Giannini,  I  Godor,  M  A  Imran,    Y  Jading,  E  Katranaras,  M  Olsson,   D   Sabella,     P   Skillermark,   W   Wajda,   Energy   efficiency   analysis   of   the   reference   systems,   areas   of   improvements   and   target   breakdown.   EARTH   project   report,   Deliverable  D2.3  (2010).  
  28. 28. HOMER  for  hybrid  power  system  modeling •  NPC  represents  the  system’s   life  cycle  cost     •  Assesses  costs  within  the   project  life<me;  ini<al  set-­‐ up,  component  replacements   and  maintenance   •  Project  life<me:  20  years   •  Others:  dual-­‐tracking  system,   SPV  cost:  $4/W  
  29. 29. Part  I   M.  H.  Alsharif,  R.  Nordin,  and  M.  Ismail  (2015).  Energy  Op3miza3on  of  Hybrid  Off-­‐Grid  System  for  Remote  Telecommunica3on  Base   Sta3on  Deployment  in  Malaysia.  EURASIP  Journal  on  Wireless  Communica,ons  and  Networking,  2015:64.     Energy  Op3miza3on  of  Off-­‐Grid  System  for  Remote   LTE-­‐BS  
  30. 30. Energy  Model   Economic  Factors   DG  Factors   Daily  solar   (kWh/m2)   SPV   (kW)   DG   (kW)   BaDery   (unit)   Inverter   (kW)   Ini<al   Capital   Opera<ng   ($/yr)   NPC  ($)   Diesel   (L)   DG   (h)   5.1   2   1   4   1.5   $11,210   1,993   40,188   1,880   6,091   5.2   2   1   4   1.5   $11,210   1,980   40,000   1,866   6,039   5.3   2   1   4   1.5   $11,210   1,968   39,820   1,854   5,999   5.4   2   1   4   1.5   $11,210   1,956   39,653   1,840   5,954   5.5   2   1   4   1.5   $11,210   1,946   39,497   1,830   5,923   Ø  The  op<mal  size  of  the  solar  energy  system  is  obviously  the  same  for  all  solar  radia<on   rates  proposed  (5.1  -­‐  5.5  kWh/m2/day).     Ø  However,  the  energy  contribu<on  differs,  with  the  contribu<on  of  energy  from  the  solar   power  system  increasing  with  increasing  radia<on  rate.     1.  Op<miza<on  Criteria   Results    
  31. 31. 2.  Energy  Yield   Results  (Cont’d)  
  32. 32. Cash  flow  summary  of  the  SPV/DG  hybrid  power  system  within  the  project  life<me  at  5.1  kWh/m2/day.     3.  Cash  Flow   Results  (Cont’d)  
  33. 33. Comparison  between  Malaysia  and  Germany   The  Net  Present  Cost  
  34. 34. Part  II   M.  H.  Alsharif,  R.  Nordin,  and  M.  Ismail  (2015).  Intelligent  Coopera3on  Management  among  Solar  Powered  Base  Sta3ons  towards  a   Green  Cellular  Network  in  a  Country  with  an  Equatorial  Climate.  Telecommunica,on  Systems.     Intelligent  Coopera3on  Management  Among  Solar   Powered  LTE-­‐BSs    for  urban  areas  
  35. 35. 1. LTE Network Topology Key  challenge:  coverage     2. Problem Formulation Intelligent  Coopera3on  Management  Among  BSs    
  36. 36. Results  (Cont’d)   Cell radii versus receiver sensitivity power for different MCSs Data rate
  37. 37. Optimal design of the hybrid PV/electric grid system for master cell (operates 24 hours) Optimal design of the hybrid PV/electric grid system for cell operates at high traffic only (13 hours) 1. Optimisation Criteria Results    
  38. 38. 2. Energy Yield Results  (Cont’d)   4,290   4,407   4,524   4,177   4,281   5,074   5,040   4,997   5,112   5,059   4,920   4,940   4,960   4,980   5,000   5,020   5,040   5,060   5,080   5,100   5,120   5,140   4,000   4,100   4,200   4,300   4,400   4,500   4,600   5.1   5.2   5.3   5.4   5.5   Grid  Purchases  (kWh/yr)   PV  Produc3on  (kWh/yr)   Global  Solar  (kWh/m2/day)   SPV  contribu<on  for  master  cell     EG  contribu<on  for  master  cell     2,574   2,644   2,715   2,784   2,378   2,691   2,663   2,635   2,607   2,781   2,500   2,550   2,600   2,650   2,700   2,750   2,800   2,100   2,200   2,300   2,400   2,500   2,600   2,700   2,800   2,900   5.1   5.2   5.3   5.4   5.5   Grid  Purchases  (kWh/yr)   PV  Produc3on  (kWh/yr)   Global  Solar  (kWh/m2/day)   SPV  contribu<on  for  cell  operates  13  hrs   EG  contribu<on  for  cell  operates  13  hrs   Master cell Cell operates at high traffic only (13 hours)
  39. 39. Results  (Cont’d)   -­‐14,000   -­‐12,000   -­‐10,000   -­‐8,000   -­‐6,000   -­‐4,000   -­‐2,000   0   2,000   4,000   1   2   3   4   5   6   7   8   9   10   11   12   13   14   15   16   17   18   19   20   Nominal  Cash  Flow  ($)   Year  Number   Salvage  ($  3,719)   Replacement  Cost  ($)   O&M  Cost  ($  800)   Capital  Cost  ($  12,200)   Replacement   BaDeries   Replacement   Inverter   3. Cash Flow Cash  flow  summary  of  the  hybrid  power  system  within  the  project  life<me  at  5.1  kWh/m2/day  for  master  cell  
  40. 40. Future  direc*ons  &  challenges  related  to   green  wireless   •  5G  Networks:  Adjustments  in  massive  MIMO  (antenna  switching  off/on)  at  high  traffic  load   condi<ons,  with  the  BSs  switching  off/on  technique   •  Energy-­‐harves<ng,  such  as,  energy  harves<ng,  e.g.:  RF,  mechanical,  relay,  etc.     •  Inves<ga<on  of  coopera<on  between  mobile  network  providers  (switching  off/on)  in  the  same   geographical.  
  41. 41. More  details…   Fundamentals  and  Applica<ons  of  Green  Communica<on  for   Current  and  Future  Mobile  Networks   •  Monday,  23rd  November  2015   •  Hilton  Hotel  Kuching   Acknowledgement:  Project  supported  by  Universi<  Kebangsaan  Malaysia  (UKM),  under  Grant  Ref:  ETP-­‐2013-­‐072