Cog-TV - NSF · TV white spaces • Cognitive radio-equipped TV sets (Cog-TVs): – TV tuner, integrated CR interface, and Wi-Fi interface • Cog-TV provides three main capabilities

Cog-TV Business and Technical Analysis of Cognitive Radio TV Sets for

Enhanced Spectrum Access (CNS 1247941/1247914) • PI (UNL): Mehmet C. Vuran (CSE, [email protected]) • Co-PI (UNL): Demet Batur (Management, [email protected]) • PI (OSU): Eylem Ekici (ECE, [email protected])

• Existing argument: Emerging cognitive radio networks result in a technical and an economical conflict with the TV broadcast companies

• Our view: Conflict Opportunity • Is it economically and technically viable for broadcast companies to utilize TV white spaces for

– low-cost Internet provision – web-enabled TV services?

NSF EARS: Collaborative Research: Cog-TV: Business and Technical Analysis of Cognitive Radio TV Sets for Enhanced Spectrum Access 1

mailto:[email protected]



Research Goals of Cog-TV

Research Goals: • Business Aspects of Cog-TV: Dynamic pricing scheme to balance demand

between peak and non-peak periods; infrastructure cost analysis for Cog-TV integrated network.

• Neighborhood Watch : Analysis of spectrum sensing accuracy and correlation in the spectrum sensing information; optimal sensing scheduling algorithms to minimize sensing overhead and maximize bandwidth.

• Cog-TV-initiated Spectrum Handoff: Methodologies to estimate the opportune times to initiate spectrum handoff; strategies for broadcast companies to address the self-competition challenge that results in serving two types of customers: TV viewers and cognitive Internet users.

Potential Payoffs: • Enable transformative and economically viable CRN development and

management approaches • Bring affordable Internet service to a large group of American households • Impact consumer market by creating a niche market in new TV sets


• Dynamic pricing:

– The capacity of CRN varies based on factors such as the availability of TV white space, choice of TV channel view, and population density.

– The TV broadcasting company will post hourly prices in real time based on changing capacity and predicted demand, especially higher prices at periods of peak demand.

– Changing prices will motivate customers to shift their Internet activity to periods of high capacity but low demand.

• As a result, customers will minimize their connection cost. TV broadcast companies will maximize their profit and increase customer satisfaction by providing Internet to more customers at even lower prices

• Cost of Cog-TV integrated network: Cost of building the Cog-TV infrastructure in the urban and rural areas will be analyzed separately to determine economic feasibility.

NSF EARS: Collaborative Research: Cog-TV: Business and Technical Analysis of Cognitive Radio TV Sets for Enhanced Spectrum Access

Business Aspects of Cog-TV

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• TV spectrum ownership gives TV broadcast companies a major advantage in extending their business to become an Internet service provider using the TV white spaces

• Cognitive radio-equipped TV sets (Cog-TVs):

– TV tuner, integrated CR interface, and Wi-Fi interface

• Cog-TV provides three main capabilities

– Low-cost access to the Internet in residential and commercial spaces

– Interference measurement of TV services for enhanced quality of user experience

– Localized collaborative spectrum sensing for fine-grained spectrum management

• Broader Impacts: Interdisciplinary research in operations research, decision sciences, wireless communication, networking, and optimization

• Dynamic Pricing: Change price dynamically to manage demand

– Provide real-time pricing information to customers

– Customers can access Internet strategically to lower their bills

• Neighborhood Watch: Utilize network of Cog-TVs to improve unlicensed band utilization through collaborative sensing mechanism


Cog-TV

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• Correlation-based Collaborative Spectrum Sensing: Provably optimal cooperative algorithms through a novel sensing deficiency virtual queue [1] concept

– Exploit the four dimensions of correlation (spatial, temporal, spectral)

– Explore resource cost functions based on price paid by the customer

– Develop distributed algorithms

• Cog-TV-Initiated Spectrum Handoff: Account for TV tune-in events and predictions to enable proactive spectrum handoff decisions

– TV viewers and cognitive Internet users are both customers

– Evaluate the costs and benefits of staying on a given channel despite TV tune-in on the channel

– Self-competition for Cog-TV-initiated spectrum handoff

• Evaluation Testbed: Utilizes distinct properties of Nebraska (sparse population) and Ohio (dense population)

• Education and Outreach: Attract undergraduate students by UCARE (UNL) and UROP (OSU) programs. Reach underrepresented groups and high schools, e.g., Ohio State Women in Engineering Program, UNL 4-H program.


[1] D. Xue, E. Ekici, M. C. Vuran, ``(CORN)^2: Correlation-based Cooperative Spectrum Sensing in Cognitive Radio Networks,’’ in Proc. Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt'12), Paderborn, Germany, May 2012.

Main Threads of the Project

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Case Study:

Available Channel Capacity with

Cog-TV vs. current FCC Rules Lincoln, NE & New York, NY


or “Is it really worth it?”

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TV Rating Assumption

5 10 15 20 25 30 35 40 45 500

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1.5

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2.5

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3.5Random Generated TV Rating for Channel 2~51

channel

perc

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Assumptions: (1) 8% of population are watching TV, (2) Randomly generated rating data


Population Density of Lincoln

97.0 W 96.9

W 96.8 W 96.7 W 96.6 W 96.5 W 96.4 W

40.7 N

40.8 N

40.9 N

Population Density in Lincoln, 2010, in Persons per Square Mile

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Population and TV Tower Coverage Lincoln, NE


TV Channel Viewership in Lincoln


Available TV Channels in Lincoln FCC vs Cog-TV (1km Cell)

97.0 W 96.9

W 96.8 W 96.7 W 96.6 W 96.5 W 96.4 W

40.7 N

40.8 N

40.9 N

Population Density in Lincoln, 2010, in Persons per Square Mile

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FCC Cog-TV


Available Channels in Lincoln (FCC vs Cog-TV)

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Capacity Distribution of FCC rules and Cog-TV

Capacity 1: FCC 2010 rule

Capacity 2: Cog-TV

Cell Size: 1 km


Available Channels in Lincoln (FCC vs Cog-TV)

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Capacity 2: Cog-TV

7 km 10 km NSF EARS: Collaborative Research: Cog-TV: Business and Technical Analysis of Cognitive Radio TV Sets for Enhanced Spectrum Access

Capacity vs Cell size Lincoln, NE


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Capacity vs Cell Size in Lincoln, NE

FCC 2010 mean

Cog−TV mean

Manhattan, New York

74.0 W

40.7 N

40.8 N

Population Density in Manhattan, 2010

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Population Density Channel selection

Population, TV Signal Coverage, NY


Manhattan, NY, 0.2km cell

FCC Cog-TV



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Available Channels in Manhattan, NY (FCC vs Cog-TV)

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Cell Size: 200 m 300 m 500 m

1 km 3 km


Capacity vs Cell size Manhattan, NY


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Capacity vs Cell Size in Manhattan, NY

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Cog−TV mean

CORN2: Correlation-Based Cooperative Spectrum Sensing in CRNs

• Local information essential to assess spectral availability

• Most observations are highly correlated in – Space

– Time

– Spectrum

• Objective: Leverage correlations for cooperative spectrum sensing to minimize energy consumption Develop (centralized and distributed) sensing scheduling algorithms

• Nodes that perform local sensing broadcast their results

• Past and current sensing results as well as results obtained from nearby nodes are combined

• A long-term target sensing information quality is maintained


[D. Xue, E. Ekici, M. C. Vuran, ``(CORN)^2: Correlation-based Cooperative Spectrum Sensing in Cognitive Radio Networks,’’ in Proc. Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt'12), Paderborn, Germany, May 2012.

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• Algorithm design involves two virtual queues: – Local Sensing Queue ensures that nodes perform sensing at a rate > RS and do not cheat

– Sensing Deficiency Queue ensures a sensing quality > RD by eliminating deficiency at rate Mic(t)

– Mic(t) is the accumulation of all local sensing and information obtained from nearby nodes

– The centralized solution ensures stability of all queues while minimizing total energy consumption

• Distributed Algorithm: – If total contribution of all neighbors is bounded, then a fully distributed algorithm exists

– Bounded contribution holds for low SNR cases and when temporal correlation is high

– The resulting algorithm is a solution to a MWM problem on a bipartite graph with local weights and constraints Can be computed locally




RS = 0.05, RD = 0.95, PS = 3.5mJ, PTx= 0.1125mJ, wi,j(t) = 0.90

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Documents

Cog-TV - NSF · TV white spaces • Cognitive radio-equipped TV sets (Cog-TVs): – TV tuner, integrated CR interface, and Wi-Fi interface • Cog-TV provides three main capabilities