Accounting interference: impact of interference on revenue

Vânia Gonçalves IBBT-SMIT, VUB

NG Wireless Workshop Cognitive Networks: Interference Sensibility

21-01-10, IBBT-Ghent

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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

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Spectrum allocation

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

EFFICIENT?

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Spectrum is underutilised

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

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Spectrum is underutilised

Willkomm D. et al, 2009

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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…

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Spectrum usage varies greatly in a matter of minutes

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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

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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

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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

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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

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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

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ZigBee and Wi-Fi

Daytime measurements

Measured at IBCN, 2009

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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

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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

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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

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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

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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

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Thank you!

Questions?

vania.goncalves@vub.ac.be

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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.