Cognitive Radio from a Mobile Operator’s Perspective: System Performance and Business Case EvaluationsPhD Dissertation, 18.october 2013Pål GrønsundSupervisors: Paal E. Engelstad, Przemyslaw Pawelczak, Audun F. Hansen, (Ole Grøndalen)

Traffic capacity = AvailableSpectrum

(MHz)

NetworkDensity

(sites/km2)

XSpectrumEfficiency

(Mbps/MHz/site)

X

Massive growth in

Traffic VolumeMassive growth in

Connected DevicesWide range of

Requirements

• Data rate• Latency• Coverage• Energy• Device cost• ….

Mobile operators need to solve the key challenges for future wireless access

2

3

Po

wer

Sp

ectr

al D

ensi

ty

0 1 2 3 4 5 6 GHz

Most spectrum is allocated

… but not well utilized

4

Cognitive radio is an “intelligent” and flexible radio system that can observe and learn from the environment and adapt accordingly

5

Cognitive Radio can be used to dynamically access spectrum that is underutilized

CognitiveRadio

Power

Frequency

Time

Spectrum occupiedby licensed users

Spectrum Holes(White Spaces)

t1 t2t3

6

The problem statement

How can a mobile operator benefit from using cognitive radio to opportunistically access white spaces, with the potential to enable sustaining and disruptive innovation?

Increased performance

Lower costs, increased revenue

New business models, services

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Cognitive Radio brings threats and opportunities for the mobile operator

• Reduced value of spectrum licenses

• Increased interference if other cognitive radios uses the mobile operator’s own spectrum

• Increased (unfair) competition

Threats

Opportunities

• Access to more spectrum in existing networks

• Opportunity to access spectrum in new markets

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The methodology focused on both technical and economical evaluation of Cognitive Radio systems

We studied three important areas for Cognitive Radio with focus on the mobile operator's perspective

Dynamic spectrum access in primary OFDMA systems (Paper A)

Sensor Network Aided Cognitive Radio Systems (Papers B - E)

Performance of the first Cognitive Radio Standard IEEE 802.22(Papers F - I)

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Outline

Dynamic spectrum access in primary OFDMA systems (Paper A)

Sensor Network Aided Cognitive Radio Systems (Papers B - E)

Performance of the first Cognitive Radio Standard IEEE 802.22(Papers F - I)

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Dynamic spectrum access in the time dimension in primary OFDMA networks can be possible

…but, our results show that cooperation with the primary operator is important to reduce interference and increase capacity

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Outline

Dynamic spectrum access in primary OFDMA systems (Paper A)

Sensor Network Aided Cognitive Radio Systems (Papers B - E)

Performance of the first Cognitive Radio Standard IEEE 802.22(Papers F - I)

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Sensor Network aided Cognitive Radio (SENDORA) system

Three business case scenarios were studied for the SENDORA concept

Spectrum owner 1

Spectrum owner 2

Spectrum owner N

Joint venture“Spectrum Sharing”

Business case I

New entrant New entrant New entrant

Business case III

Spectrum broker

Business case II

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The “spectrum sharing” business case is probably one of the best cases for a SENDORA system

It has free access to spectrum from the mother companies, and good possibilities for re-using existing infrastructure.

The most critical aspects for profitability are:

• Fixed sensor density

• Fixed sensor OPEX

• Subscription fee (service offered)

• Share of new sites

A “new entrant” cognitive radio operator might get a positive business case if it gets the spectrum for free, otherwise it will be difficult.

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Fusion Centre

PrimaryBase Station

Primary terminal

SecondaryBase Station

Secondaryterminal

Sensor

A SENDORA system was implemented in a simulator to evaluate the capacity for different cell sizes

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Secondary SystemRadius rs = ?

Primary SystemInter-BS-dist: 2kmRadius rp =1.15km

Wireless Sensor Network*:

65 sensors/km2

Sensor radiusrws=87.7m

(*values from business case analysis)

PN=90% rs=1.15 km

Cognitive radio is best suited for smaller cells such as WiFi access points and femtocells

Access rule: the interference generated to the primary system should correspond to an increase of the noise floor of less than 0.5 dB with a certain probability PN%.

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100% co-location 25% co-location

… but relaxed interference requirements to the primary user can increase cell size

Offloading the LTE network using Cognitive Femtocells aided by a sensor network

1) deploy cognitive femtocells

2) deploy sensors

3) increase power

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We compare with the case of using conventional femtocells and additional base stations

1) deploy conventional femtocells

2) deploy macro base stations

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Offloading LTE with cognitive femtocells can be more cost effective than using conventional femtocells and additional base stations

The most business critical parameters for the cognitive femotcell:• cost for backhaul• number of users supported• coverage radius

Outline

Dynamic spectrum access in primary OFDMA systems (Paper A)

Sensor Network Aided Cognitive Radio Systems (Papers B - E)

Performance of the first Cognitive Radio Standard IEEE 802.22(Papers F - I)

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We implemented a detailed simulator to evaluate performance of the first standard for Cognitive Radio, IEEE 802.22

It uses two-stage spectrum sensing

System ModelIt provides fixed wireless broadband in rural areas

Coarse sensing stage

(tc=1ms, at end of frame)

Fine sensing stage (ts=30ms)

Switch channel

YESdetection

NO detection

YESdetection

NO detection

Performance for different sensing strategies should be considered dependent on required Quality of Service (QoS)

Scenario 3 users receiving Video with Best Effort QoS profile 1 user receiving Voice over IP (VoIP) with Guaranteed Bit Rate QoS profile

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Spectrum selection (SSE) functions that utilize sensing results to provide long term statistics can increase performance

SSE-Distance: selects the channel with shortest distance to WMs.

SSE-OnOff: selects the channel with highest probability of being available.

SSE-Hybrid: uses the optimal of SSE-Distance and SSE-OnOff depending on distance to WMs.

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In conclusion, a mobile operator can use Cognitive Radio to achieve well performing technical and economic viable solutions

Operators can get access to more spectrum, increase capacity and reduce costs significantly by using sensor network aided cognitive radio systems.

Spectrum selection functions that utilize sensing result statistics to predict primary user behavior can increase performance in IEEE 802.22.

Pål Grønsund (Pal.Gronsund@telenor.com)

There is a potential to utilize white spaces in primary OFDMA networks, but cooperation with the primary is important.