Spectrum Spectrum sensing sensing techniques techniques and and aspects related to propagation Valeria Petrini, Ph.D. Student

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Student vpetrini@arces.unibo.it DEIS/ARCES - Tutor : Prof.

1 Spectrum sensing techniques and aspects related to propagation Bologna, 24/01/2012 Valeria Petrini, Ph.D. Student DEIS/ARCES - Tutor : Prof. Ing. Giovanni Emanuele Corazza Fondazione Ugo Bordoni - Cotutor: Ing. Guido Riva

2 Outline Cognitive Radio Autonomous WSD and database-assisted WSD White Space model in UK Ofcom) Applications of Cognitive Radio Cognitive Approach to Satellite System Energy Efficiency in Mobile Radio Systems: a Cognitive approach Other work

3 What is a Cognitive Radio (CR)?

environment and can dynamically and autonomously adjust its radio operating

4 What is a Cognitive Radio (CR)? (1) Cognitive Radio: a radio or system that senses its operational electromagnetic environment and can dynamically and autonomously adjust its radio operating parameters to modify system operation, such as maximize throughput, mitigate interference, facilitate interoperability and access secondary markets

can be classified in two groups: Primary Network:

referred to as the primary network, which has an

Secondary Network: does not have license to operate

Hence, the spectrum access is allowed only in an

5 What is a Cognitive Radio (CR)? (2) The components of the Cognitive Radio network can be classified in two groups: Primary Network: an existing network infrastructure is generally referred to as the primary network, which has an exclusive right to a certain spectrum band Secondary Network: does not have license to operate in a desired band. Hence, the spectrum access is allowed only in an opportunistic manner Cognitive Radio Loop Spectrum Sensing Spectrum Analysis Spectrum Management Spectrum Reconfigurability

6 Autonomous WSD and database-assisted WSD Autonomous WSD: performs sensing and radiate only if it cause no interference to the DTT worst case Database-assisted WSD: operates with assistance from a geolocation database

7 Estimation of Spectrum Availability for White Space Devices

8 Estimation of Spectrum Availability for White Space Devices (1) The idea is using a geolocation database for regulating ERP of White Space Device (WSD) which will reuse the broadcasting spectrum ( MHz) Before transmitting, a WSD will interrogate a database, called the geolocation database, providing its location and its characteristics, and it will receive a list of channels it may use, as well as on its maximum permissible ERP for each of these channels The objective of my work is to compute the data required to populate the geolocation database and use them in order to get some statistical data

9 Estimation of Spectrum Availability for White Space Devices (2) Through the Spectrum Sensing a WSD can control the variability of the channel Spectrum Sensing WSD Primary Network WSD Position Primary Base Station Primary User Channel ERP Geolocation Database

Estimation of Spectrum Availability for White Space Devices (3) UK

study the digital terrestrial television coverage in the UK It isused

and from each UK transmitting site At the heart of any computer planning

strength from a transmitter at a receiving location The basis is the

10 Estimation of Spectrum Availability for White Space Devices (3) UK Planning Model (UKPM) (1) The UK Planning Model was mainly developed to study the digital terrestrial television coverage in the UK It isused tocalculate l thewanted and interfering i field strength distributions to and from each UK transmitting site At the heart of any computer planning method is propagation prediction which is the prediction of field strength from a transmitter at a receiving location The basis is the prediction of received field strength at a location, taking into account the environment in between

11 Estimation of Spectrum Availability for White Space Devices (4) UK Planning Model (UKPM) (2) The UKPM calculates the DTT location probability, q, for every 100 m x 100 m pixel across the UK This is defined as the probability with which wanted and unwanted DTT signal powers meet the relevant criterion for correct operation of a DTT receiver Specifically, the location probability can be written (in linear domain) as: q1 PrE s E S,min K k 1 r U, k E U, k E s is the wanted field strength at the DTT receiver E S,min is the minimum received wanted field strength required for correct operation in a noise-limited environment K is the number of (co-channel channel and/or adjacent-channel) channel) DTT interferers E U,k is the received field strength level of the K th DTT interferer, and r U,k is the minimum ratio of wanted DTT field strength to DTT interfere field strength required for correct operation (DTT-to-DTT protection ratio)

Wanted Signal: Channel n 100 m 100 m The

12 Estimation of Spectrum Availability for Whit S i (5) White Space D Devices UK Planning Model (UKPM) (3) K q1 Pr Es ES,min ru,k EU,k k 1 Interferer Signal: Channel n E q1 Pr ES U E Pr S 1 U E Pr ES ( db V / m ) U E ( db V / m ) 0 Pixel Wanted Signal: Channel n 100 m 100 m The terms ES(dBµV/m) and UE(dBµV/m) are approximated as Gaussian random variables with medians ms(dbµv/m) and mu(dbµv/m), and standard deviations σs(db) and σu(db), respectively Interferer Signal: Channel n +1 (or n-1 )

13 Estimation of Spectrum Availability for White Space Devices (6) Computation of the maximum permissible ERP E WSD is the field strength of WSD K q 2 PrEs ES,min ru, k EU, k r( f ) G E k 1 G is the WSD DTT receiver coupling gain r( f) is the WSD to DTT protection ti ratio WSD X r(f ) (db ) G db E WSD(dB ) X can be modelled as a Gaussian random variable with mean m x and standard deviation σ x q 1 q 2 q As long as the mean field strength of the interference from WSD is kept m x then the location probability reduction will be less than q Therefore m x is the maximum permissible mean value for the WSD protected field strength

14 Cognitive Approach to Satellite System

used) Secondary Network: Satellite Network Secondary Network: Terrestrial Network Scenario #1 Satellite Terrestrial Scenario #2 Satellite

15 Cognitive Approach to Satellite System (1) White spaces: spectrum holes Black spaces: the contents t of which h are completely l full due to the combined presence of communication and noise Gray spaces: spaces that are partially occupied by asignal (the given spectrum is partially used) Secondary Network: Satellite Network Secondary Network: Terrestrial Network Scenario #1 Satellite Terrestrial Scenario #2 Satellite Terrestrial Primary - Broadband Wireless Links Primary Return Links - Secondary Forward and Return Links - Secondary - Broadband Wireless Links

16 Cognitive Approach to Satellite System (2) Secondary Network: Terrestrial Network A Ground Station transmitting with: P 0 : the transmitted power G 0 :the antenna gain A geostationary satellite receiving with: G S : antenna gain L: distance between the GS and the satellite Assumptions: Interfering links are affected by Rayleigh fading All cognitive devices are at distance L from the satellite Path loss α = 2 (free space propagation) An interfering network spatially deployed as a 2D Poisson Point Process φ with density λ int each interfering terminal transmits an ERP equal to P I G I

17 Cognitive Approach to Satellite System (3) The Interference Model (1) Objective: to evaluate the outage probability: the probability that the cognitive device power is higher than a certain threshold, equivalent to: Pr SINR T 2 P0 G0GS L Pr 2 2 N P I G I G S L I SINR: Signal to Interference plus Noise Ratio T: SINR threshold above which the useful primary link is still working σ 2 N : AWGN power The only source of randomness is given by the aggregate interference

18 Cognitive Approach to Satellite System (4) Cognitive devices density λ int Outage probability Numerical Results (1)

19 Energy Efficiency in Mobile Radio Systems

20 Energy Efficiency in Mobile Radio Systems (1) Different cellular coverage strategies were studied to find a trade-off to reach the best performance in terms of radio coverage, system throughput and energy efficiency Emitted Power Density (EPD) [W/km 2 ] Emitted (radio) Power per square km for a given offered service It mainly depends on the RAN (power emitted by the BS s) It depends on radio interface technology and planning Cell size, propagation losses, traffic density, deployment strategy

21 Energy Efficiency in Mobile Radio Systems (2) EPD evaluation in ideal environment Ideal environment: Single cell Dual-slope quasi-hata propagation model Fully analytical model Cell border (d=r) evaluation (P SENS = -90dBm) : P R (db) α=2 P T 1 4d R P 0 R sens G T G R d 0 2 N h TX α>2 RX EPD P T (R) A cell (R) d 0 b d Log (distance)

22 Energy Efficiency in Mobile Radio Systems (3) Theoretical scenario fixed traffic / cell EPD (W/Km 2 ) R[Km]

23 Energy Efficiency in Mobile Radio Systems (4) EPD evaluation in simplified urban environment Scenario: Manhattan-like Microcellular and macrocellular cases Objective: coverage strategy to minimize the EPD Ray-tracing tool to properly predict propagation Average building height: 30 m

24 Energy Efficiency in Mobile Radio Systems (5) Idea: Result: Hybrid Case (Macro cell + Micro cell deployment) Cell Shape To minimize EPDMICRO Micro cell Lower floors Macro cell Higher floors F E F C B A B C D TX C B A B C D Target coverage reached!

25 Energy Efficiency in Mobile Radio Systems (6) Cognitive Networking Application Layer Transport Layer Cognitive approach To reduce the the network energy consumption, the nodes have to be reconfigured in order optimize the network in a broader way Network Layer MAC Layer Physical Layer Cognitive Radio Additional communication parameters have to be considered: throughput delay traffic characteristics femto cell

26 Other Work

27 Other work Applications of Cognitive Radio Cognitive Approach to Emergency Management Characterisation of WiMAX propagation Experimental propagation characterization at 3.5 GHz in different environments (outdoor, indoor and mixed) Cross Layer Coding (UL-FEC) Analysis of a wireless communication system in which channel coding is Analysis of a wireless communication system in which channel coding is applied to both physical and upper layer. The splitting of redundancy between the coding schemes applied to the two layers was studied

28 Pubblications A study on the energy efficiency of urban cellular radio deployment solutions, V. Degli Esposti, V. Petrini, M. Barbiroli, C. Carciofi, APS-URSI 2012-Chicago (Submitted) A fully reconfigurable approach to Emergency Management, D.Tarchi, V.Petrini and G.E. Corazza, IJARAS, Vol.3, No 3 "Cognitive Hybrid Satellite-Terrestrial System, R.Suffritti, G.E. Corazza, A. Guidotti, V.Petrini, D.Tarchi, A.Vanelli-Coralli, M. Di Renzo, CogART-ISABEL 2011 "Planning Criteria to Improve Energy Efficiency of Mobile Radio Systems, M.Barbiroli, C.Carciofi, V.Degli Esposti, P.Grazioso, D.Guiducci, V.Petrini, G.Riva, ICEAA 2011 "Experimental Characterisation of WiMAX Propagation in Different Environments, Valeria Petrini, Daniel Robalo, Marina Barbiroli, Claudia Carciofi, Fernando J. Velez, Joao Oliviera, Franco Fuschini, Paolo Grazioso, Eurocon & Conftele 2011 "Optimizing Cross Layer Coding Redundancy in Slow Fading Channels, Marco Papaleo, Valeria Petrini, Rosario Firrincieli, Alessandro Vanelli-Coralli, Giovanni Emanuele Corazza, ASMS/SPSC 2010

29 Credits Newcom++ Spring School on "Cognitive Wireless Communication Networks (21 cdf) Cost2100/Conet/Newcom++ Training School on "Cooperating Objects and Wireless Sensor Networks (20 cdf) COST Action IC0902 :"First International Summer School on Cognitive Wireless Communications (60 cdf) University Course: "Trends in Communications (30 cdf) English Course (30 cdf)

30 Vl Valeria Ptii Petrini Dipartimento Elettronica Informatica Sistemistica DEIS Advanced Research Center on Electronic Systems for Information and Communication Technologies E. De Castro ARCES Fondazione Ugo Bordoni FUB

31 Cognitive Approach to Emergency Management

32 Cognitive Approach to Emergency Management (1) Emergency phases: Prediction and prevention Efficient handling of emergency activities Carrying out the operations following a natural disaster Basic requirements of an ICT infrastructure: Resilience/robustness Self-management Decision support system Interconnection/Interoperability Mobility Power-efficiency Broadcasting/Multicasting Security Localization engine

33 Cognitive Approach to Emergency Management (2) DISTRIBUTED COMPUTING INFRUSTRUCTURE UC U Autonomic system features: Self-Healing Self-Protection Self-Configuration Self-Optimization

34 Cognitive Approach to Emergency Management (3) EMERGENCY MANAGEMENT LEARNING LOOP

Spectrum Management and Cognitive Radio

Spectrum Management and Cognitive Radio Alessandro Guidotti Tutor: Prof. Giovanni Emanuele Corazza, University of Bologna, DEIS Co-Tutor: Ing. Guido Riva, Fondazione Ugo Bordoni The spectrum scarcity problem