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Accounting interference:
impact of interference on
revenue
                   Vânia Gonçalves
                   IBBT-SMIT, VUB

                NG Wireless Workshop
      Cognitive Networks: Interference Sensibility
                21-01-10, IBBT-Ghent
Overview


  Spectrum allocation
      Spectrum is underutilised
      Changes taking place
  Spectrum sensing
  Modelling revenue
  Case studies
      802.15.4 and Wi-Fi
      UMTS and UWB
      WiMAX and FWA
  Conclusions

                                   2
Spectrum allocation


  Spectrum allocation has always been assigned on a static
   basis in order to avoid interference




                                EFFICIENT?

                                                          3
Spectrum is underutilised




                            McHenry M.,Tenhula P. & McCloskey D.,
                            Chicago Spectrum Occupancy
                            Measurements & Analysis
                            and a Long-term Studies Proposal, 2005
                                                           4
Spectrum is underutilised




    Willkomm D. et al, 2009
                              5
Changes are taking place


  Regulatory changes: FSM, DSA, ...
  Cognitive radios
  Sharing is becoming a necessity
  Coexistence of secondary networks with primary owners
   of spectrum is possible
  Opportunities for new sources of revenue



                                 BUT…

                                                           6
Spectrum usage varies greatly in a matter of
minutes




                                               7
Spectrum sensing


  Sensing is the enabler for spectrum sharing
  But perfect sensing of primary users of spectrum is difficult
  Technical requirements and procedures might still be set
   to mitigate harmful interference
  Higher likelihood of services interfering with each other
  Few incentives for primary owners to allow opportunistic/
   secondary usage
  Possible losses in revenue?
  Important to model the impact of secondary users on
   primary users’ performance and primary owners’ revenue


                                                              8
Modelling revenue


  Ercan et al. (2008) propose a three player Stackelberg
   game model between the PO, PUs and SUs in which:
      SUs share the channel with primary users in time
      Secondary user access through a non-perfect listen-
       before-send scheme
      SUs are allowed to use the channel it when it is not
       being used by any PU but keeping interference to PUs
       below a maximum
      Accounts for interference probability



                                                          9
Modelling revenue

  Shown that the spectrum owner can enhance revenue by
   allowing opportunistic access with a non-zero interference
   probability to the primary users:
       In exchange for the degraded QoS of the PUs due to
        interference from SUs, the PO offers the PUs a lower
        subscription fee
       The enhancement of the revenue comes from the
        subscription fee of the SUs and better spectrum usage
  Weaknesses:
       Only one channel and a single spectrum owner is
        considered
       Simple listen-before-send model
       Maximum tolerated interference not dependent of
        technologies involved
       The user utility metrics are assumed to be equal to their
        average throughput and not based on the time of application
                                                                10
Case studies


  Maximum tolerated interference varies with technologies
   involved: estimation of interference probability different if PU
   technology ≠ SU technology
  The impact to the application/service needs to be considered
       Service metrics
          User throughput
          Delay/jitter
          Users’ outage
          Coverage
          QoS
          …
       The context the application serves
          emergency services ≠ office building
                                                                      11
802.15.4 and Wi-Fi
  Office environment scenario
  200 802.15.4 sensor nodes spread out over 3 floors
  Main interference source: wifi networks




                                                        Nighttime measurements


                                                        Measured at IBCN, 2009
                                                                                 12
ZigBee and Wi-Fi




                   Daytime measurements


                   Measured at IBCN, 2009

                                   13
UMTS and UWB
  Operational UMTS network
  Main interference source: UWB devices
  Distance of 1 meter between UMTS terminal and UWB devices


  UMTS in idle mode
  Degradation is
noticeable but
connection is not lost,
except for the cases
with 12 and 16 UWB
devices




                                                  Hämäläinen, M et al., 2006
                                                                          14
UMTS and UWB

  UMTS in voice and
data modes

  With a small number
of active devices, no
measurable impact is
seen

  For voice connections,
the connection is lost
with more than 12
active UWB devices



                            Hämäläinen, M et al., 2006 15
WiMAX and FWA
    FWA service
    Main interference source: WiMAX
    Urban dense areas
    Co-channel, adjacent channel, and zero guard band transmission




                                                    Shamsan and Rahman, 2008 16
WiMAX and FWA
    FWA service
    Main interference source: WiMAX
    Urban dense areas
    Co-channel, adjacent channel, and zero guard band transmission




                                                   Shamsan and Rahman, 2008
                                                                              17
Conclusions


  Spectrum sensing may create opportunities for efficient usage
   of spectrum and increased revenue
  The impact of interference to be a combination of the
   interference generated by the technologies, application and
   context
  Maximum tolerated interference to be dependent on intended
   output of service metrics and technologies
  Next steps:
       To be able to narrow down to costs -> definition of concrete
        scenarios:
           Frequency bands
           Spectrum access
           Interference scenarios/technologies involved
           Application and context
                                                                  18
Thank you!




               Questions?



             vania.goncalves@vub.ac.be




                                         19
References


  Hamalainen, M., et al., Co-existence measurements between
   UMTS and UWB systems. IEE Proceedings - Communications,
   2006. 153(1): p. 153-158.
  Shamsan, Z.A. and T.A. Rahman, On the comparison of
   intersystem interference scenarios between IMT-Advanced and
   Fixed Services over various deployment areas at 3500MHz.
   Progress In Electromagnetics Research, 2008. 5: p. 169–185.
  Ercan, A.O., et al., A Revenue Enhancing Stackelberg Game
   for Owners in Opportunistic Spectrum Access., in Proceedings
   of DySPAN 2008, 2008.
  Willkomm, D., et al., Primary user behavior in cellular networks
   and implications for dynamic spectrum access. Comm. Mag.,
   2009. 47(3): p. 88-95.


                                                                 20

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Vânia goncalves isbo ng wi nets - accounting interference

  • 1. Accounting interference: impact of interference on revenue Vânia Gonçalves IBBT-SMIT, VUB NG Wireless Workshop Cognitive Networks: Interference Sensibility 21-01-10, IBBT-Ghent
  • 2. Overview   Spectrum allocation   Spectrum is underutilised   Changes taking place   Spectrum sensing   Modelling revenue   Case studies   802.15.4 and Wi-Fi   UMTS and UWB   WiMAX and FWA   Conclusions 2
  • 3. Spectrum allocation   Spectrum allocation has always been assigned on a static basis in order to avoid interference EFFICIENT? 3
  • 4. Spectrum is underutilised McHenry M.,Tenhula P. & McCloskey D., Chicago Spectrum Occupancy Measurements & Analysis and a Long-term Studies Proposal, 2005 4
  • 5. Spectrum is underutilised Willkomm D. et al, 2009 5
  • 6. Changes are taking place   Regulatory changes: FSM, DSA, ...   Cognitive radios   Sharing is becoming a necessity   Coexistence of secondary networks with primary owners of spectrum is possible   Opportunities for new sources of revenue BUT… 6
  • 7. Spectrum usage varies greatly in a matter of minutes 7
  • 8. Spectrum sensing   Sensing is the enabler for spectrum sharing   But perfect sensing of primary users of spectrum is difficult   Technical requirements and procedures might still be set to mitigate harmful interference   Higher likelihood of services interfering with each other   Few incentives for primary owners to allow opportunistic/ secondary usage   Possible losses in revenue?   Important to model the impact of secondary users on primary users’ performance and primary owners’ revenue 8
  • 9. Modelling revenue   Ercan et al. (2008) propose a three player Stackelberg game model between the PO, PUs and SUs in which:   SUs share the channel with primary users in time   Secondary user access through a non-perfect listen- before-send scheme   SUs are allowed to use the channel it when it is not being used by any PU but keeping interference to PUs below a maximum   Accounts for interference probability 9
  • 10. Modelling revenue   Shown that the spectrum owner can enhance revenue by allowing opportunistic access with a non-zero interference probability to the primary users:   In exchange for the degraded QoS of the PUs due to interference from SUs, the PO offers the PUs a lower subscription fee   The enhancement of the revenue comes from the subscription fee of the SUs and better spectrum usage   Weaknesses:   Only one channel and a single spectrum owner is considered   Simple listen-before-send model   Maximum tolerated interference not dependent of technologies involved   The user utility metrics are assumed to be equal to their average throughput and not based on the time of application 10
  • 11. Case studies   Maximum tolerated interference varies with technologies involved: estimation of interference probability different if PU technology ≠ SU technology   The impact to the application/service needs to be considered   Service metrics  User throughput  Delay/jitter  Users’ outage  Coverage  QoS  …   The context the application serves  emergency services ≠ office building 11
  • 12. 802.15.4 and Wi-Fi   Office environment scenario   200 802.15.4 sensor nodes spread out over 3 floors   Main interference source: wifi networks Nighttime measurements Measured at IBCN, 2009 12
  • 13. ZigBee and Wi-Fi Daytime measurements Measured at IBCN, 2009 13
  • 14. UMTS and UWB   Operational UMTS network   Main interference source: UWB devices   Distance of 1 meter between UMTS terminal and UWB devices   UMTS in idle mode   Degradation is noticeable but connection is not lost, except for the cases with 12 and 16 UWB devices Hämäläinen, M et al., 2006 14
  • 15. UMTS and UWB   UMTS in voice and data modes   With a small number of active devices, no measurable impact is seen   For voice connections, the connection is lost with more than 12 active UWB devices Hämäläinen, M et al., 2006 15
  • 16. WiMAX and FWA   FWA service   Main interference source: WiMAX   Urban dense areas   Co-channel, adjacent channel, and zero guard band transmission Shamsan and Rahman, 2008 16
  • 17. WiMAX and FWA   FWA service   Main interference source: WiMAX   Urban dense areas   Co-channel, adjacent channel, and zero guard band transmission Shamsan and Rahman, 2008 17
  • 18. Conclusions   Spectrum sensing may create opportunities for efficient usage of spectrum and increased revenue   The impact of interference to be a combination of the interference generated by the technologies, application and context   Maximum tolerated interference to be dependent on intended output of service metrics and technologies   Next steps:   To be able to narrow down to costs -> definition of concrete scenarios:  Frequency bands  Spectrum access  Interference scenarios/technologies involved  Application and context 18
  • 19. Thank you! Questions? vania.goncalves@vub.ac.be 19
  • 20. References   Hamalainen, M., et al., Co-existence measurements between UMTS and UWB systems. IEE Proceedings - Communications, 2006. 153(1): p. 153-158.   Shamsan, Z.A. and T.A. Rahman, On the comparison of intersystem interference scenarios between IMT-Advanced and Fixed Services over various deployment areas at 3500MHz. Progress In Electromagnetics Research, 2008. 5: p. 169–185.   Ercan, A.O., et al., A Revenue Enhancing Stackelberg Game for Owners in Opportunistic Spectrum Access., in Proceedings of DySPAN 2008, 2008.   Willkomm, D., et al., Primary user behavior in cellular networks and implications for dynamic spectrum access. Comm. Mag., 2009. 47(3): p. 88-95. 20