Stat of the art in cognitive radio

State of the Art in Cognitive Radio

ByMohsen M. Tantawy

National Telecommunication Institute (NTI), Egypt.

2

Contents

Introduction

CR Network Architecture

MAC Protocols for CRNs

Routing in CRNs

TCP in CRNs

CRN Security

CR Standards

New Trends in CR

CR in 5G

New Applications in CR

Green CR

Cloud-based CR

CRSN

Regulatory Issues in CR

CR Business Model

IntroductionCognitive Radio Motivation

• Spectrum scarcity – Increase in spectrum demand – Spectrum is a scarce resource – Static spectrum allocation policy

Source: http://ntra.gov.eg

4

IntroductionCognitive Radio Definitions

• Mitola

• ITU

• FCC

• NTIA

• WWRF

• They talk about – “radio”.

– “interaction with the environment”.

– “measuring”.

– “decision making”.

– “automaticity”.

– “adaptation”.

More Definitions

5

Dynamic Spectrum Access

• CR technology works on the principle of DSA, where CR users utilize spectrum holes.

Source: Natarajan Meghanathan, “Cognitive Radio Technology Applications for Wireless and Mobile Ad Hoc Networks”, IGI Global Publisher, 2013. More

6

Cognitive Radio Network Architecture

Source: Geoffrey Ye Li, “Cognitive Radio Networks Project”, Georgia Institute of Technology, 2013.

7

Spectrum Allocation and Sharing Schemes

Spectrum Allocation and Sharing Schemes According to Three Criteria

Network Architecture

Centralized

Model

Distributed

Model

Spectrum Bands in use by a CR User

Open Spectrum Sharing Model

Hierarchical

spectrum modelSp

ectrum Underlay

Spectrum Overlay

Access Behavior of CR Users

Cooperative

Model

Non Cooperat

ive Model

More about Underlay, Overlay, and Interweave

8

Underlay vs. Overlay

PU - Primary Users

SU - Overlay CR

SU - Underlay CR

Frequency

PSD

PU PUPU

More about Underlay, Overlay, and Interweave

9

Cognitive Radio MAC Protocols - Example

More about Cognitive Radio MAC Source: Mahfuzulhoq Chowdhury, Asaduzzaman, and M. Fazlul Kader, “Cognitive Radio MAC Protocols: A Survey, Research Issues, and Challenges”, Smart Computing Review, vol. 5, no. 1, 2015.

•Time-slotted•Random Access•Hybrid

CR MAC

•Single Radio•Multiple RadioRadio

•Centralized•DistributedArchitecture

•Without CCC•With CCC•Global•Local

CCC

10

Detailed Classifications of Distributed MAC Protocols - Example Considering Common Control Channel (CCC)

Distributed MAC

Single Radio

Without CCC(e.g., POMDP) With CCC

Global Time

Synch.(Netw

ork Wide)(e.g.,

C-MAC)

Local Time

Synch.(only neighboring nodes

)(e.g., HC-

MAC)

Multiple Radio

Without CCC(e.g., CA MAC) With CCC

Dedicated

Global (e., OP-

MAC)

Dynamicall

y Configurable

Global (e.g., DOSS)

Local (e.g., Comesh)

Source: Mahfuzulhoq Chowdhury, Asaduzzaman, and M. Fazlul Kader, “Cognitive Radio MAC Protocols: A Survey, Research Issues, and Challenges”, Smart Computing Review, vol. 5, no. 1, 2015.

C-MAC: Cognitive MACHC MAC: Hardware Constrained MACPOMDP: partially observable Markov decision processDOSS: Dynamic Open Spectrum SharingOP-MAC: Opportunistic MACCA-MAC: Concurrent MAC

11

Routing in CRNs

Source: Natarajan Meghanathan, “A Critical Review of the Routing Protocols for Cognitive Radio Networks and a Proposal for Load Balancing Local Spectrum Knowledge Based Routing”, Computer Science & Information Technology (CS & IT), pp. 17–26, 2013.

• Relay Nodes• Spectrum for each link

Routing Deciding

• Full Spectrum Knowledge• Local Spectrum Knowledge

Routing According to

• Minimum Delay• Maximum Throughput• Minimum Power• Link Stability

Local Spectrum Knowledge Metrics

12

Transport Layer Issues in CRNs

TCP in CR

PU Behavi

or

Spectrum

Sensing

Spectrum

Changing

BW variation

due to Spectrum

Availability

More about TCP in Cognitive Radio

In addition to traditional network congestion, Link error, collision, mobility, …etc.

Source: X. Zhong, Y. Qin, and Li Li, “Transport Protocols in Cognitive Radio Networks: A Survey”, KSII Transactions on Internet and Information Systems (TIIS), vol. 8, no. 11, pp. 3711-3730, 2014.

13

CR Attacks and Countermeasures

Attack Countermeasures

Attacks on CCC CCC Frequency hopping, CCC key distribution

PUE Attacks(malicious or selfish SU)

priori known characteristics of PU signals, location determination techniques, access to geo-location information about a priori known PUs

Spectrum Sensing Data Falsification (SSDF) Attack

(Byzantine attack)

Mutual authentication, data integrity, and data encryption, Deployment of dedicated trusty sensors, mechanisms to selectively forget past information.

Jamming Attack(trigger DoS)

Channel surfing, or frequency hopping, legitimate users change their location to escape the interference range imposed by the attacker.

Objective Function Attack(manipulate the values of the radio

parameters)

No good solution has been suggested, A simple suggestion is to define threshold values for every updatable radio parameter, help from IDS.

More Cognitive Radio Attacks

Source: Marinho et al, “A survey on security attacks and countermeasures with primary user detection in cognitive radio networks”, EURASIP Journal on Information Security, 2015.

14

Cognitive Radio Attacks by Layers

Physical Layer Attacks

Jamming

PU Emulation

Overlapping SU

Objective Function Attacker manipulates trans. rate parameters so calculated results of the function are biased towards

the attacker’s interests

More Cognitive Radio AttacksSource: Deanna Hlavacek, J. Morris Chang , “A layered approach to cognitive radio network security: A survey”, Journal of Computer Networks, 2014. http://dx.doi.org/10.1016/j.comnet.2014.10.001

15

Major Standardization Organizations and Standards for Cognitive Radio

• Institute of Electrical and Electronic Engineers (IEEE)

– IEEE 802.11af-2014: Wireless Local Area Network based on TVWS (White-Fi)

– IEEE 802.22-2011: Cognitive Wireless Regional Area Network (WRAN)

– IEEE 802.15.4m-2011: Wireless Personal Area Network (Low Rate PAN in TVWS)

– IEEE 802.19.1: Solves the coexistence problem by coordinating spectrum usage by several networks in

the same area

– IEEE 1900.4a (SCC41 or DySPAN): Optimize the resource usage when many different types of networks

are available.

• Internet engineering task Force (IETF)

– IETF Protocol to Access White Space (PAWS)- RFC 7545: Database access

• International Telecommunication Union (ITU)

– ITU-WP1B: International Telecommunication Union Working Party 1B – Spectrum Management

Methodologies

• European Telecommunications Standards Institute (ETSI)

– ETSI BRAN: European Telecommunications Standards Institute Broadband Radio Access Networks

• European Association for Standardizing Information and Communication Systems.

– CEPT ECC SE43: European Conference of Postal and Telecommunications Administrations Electronics

Communications Committee Spectrum Engineering

16

Game Theory in Cognitive Radio

Game Theory in CR has

3 Compon

ents

• Set of Players

• Set of Actions

• Utility Function

Game theory in CR has two types: • Cooperative game theory: aims to maximize

total network performance by achieving Nash Bargaining state. Individual user shares their vital information like utility with other users in network.

• Non cooperative game theory which considers CR users as rational users and aims to maximize their own utility function i.e., allocating resources. – This type of game converges at Nash

equilibrium state– Stackelberg models : One CR user serves as

leader and implement its decision before other CR users and anticipate the reacts to its decision.

Source: U. Sharma, P. Mittal and C. Nagpal, “ Implementing Game Theory in Cognitive Radio Network for Channel Allocation: An Overview”, International Journal of Energy, Information and Communications vol. 6, no. 2, pp. 17-22, 2015.

17

New Trends in Cognitive Radio

Cognitive Radio in 5G

New Applications for CRNs

Green Cognitive Radio Networks

Cloud-based Cognitive Radio

Enhancement in CR MAC Protocols

Wireless Sensor Network-aided Cognitive Radio (CRSN)

Regulatory Aspects of CRNs

Cognitive Radio – Business Model

18










19

Cognitive Radio and 5G(CR role in 5G)

• Transmission Adaption: CR can dynamically and

autonomously adjust the operating parameters to satisfy

the QoS requirement by offload delay tolerant data traffic

to different tiers and radio access technologies .

Massive growth in

Connected Devices

“Communicating machines”

“50 billion devices in 2020”

More about 5G

UDND2D

MNSON CR

help 5G in

femto 2 femto

femto 2 macro

Intercell

Interference

Mitigation

20

Cognitive Radio and 5G(Challenges)

Spectrum sensing with focus on 5G

systems

Geo-location DB for 5G

CRNs

Cognitive Radio with

Massive MIMO for 5G communicatio

ns

More …

IEEE Communication Society - SIG on Cognitive Radio for 5G

MAC for 5G-CRNs

D2D comm. In 5G CRNs

5G-CRNs public safety

comm.

Cognitive small cells in 5G cellular

systems

21










22

New Applications for Cognitive Radio

Cognitive Radio

Applications (sample)

Healthcare

Emergency and Public

Safety

Smart Grid

Vehicular Networks

Mobile Network

s

Unmanned Aircraft Systems

(UAS)

23

Cognitive Radio Architectures for Unmanned Aircraft Systems (UAS)

Policy DB

Geolocation and DB With PU

Geolocation and DB Polling Without PU

Source: Timothy X. Brown, Mark McHenry, and Suppapol Jaroonvanichkul, “Cognitive Radio Architectures for Unmanned Aircraft Systems”, Handbook of Unmanned Aerial Vehicles, Springer, 2013.

24

Cognitive Radio Architectures for Smart Grid

A. Aijaz, S. Hongjia, A. Aghvami ,” CORPL: A Routing Protocol for Cognitive Radio Enabled AMI Networks”, IEEE Transactions in Smart Grid, vol. 6, no. 1, pp. 477 – 485, 2015.

Advanced metering infrastructure (AMI) or field area networks (FANs) carry info between smart meters and network gateway (power sub-station, pole-mounted device, or a comm. tower.

Home/building area networks (HANs) connect smart meters with home appliances.

WAN serves as the backbone for communication between network gateways and the utility data center.

Cognitive Radio

25










26

Green CRNs

• Green CRN requires – Not only the optimization of dynamic spectrum access

– But also the optimal utilization of green energy.

Source: X. Huang, T. Han, N. Ansari, “On Green Energy Powered Cognitive Radio Networks”, TR-ANL-2014-003, New Jersy Institute of Technology, 2014.

• Energy

Minimization

• Performance

Maximization

• Utility

Maximization

27

Energy Efficiency via Cognitive Radio

• Green Relaying,

• Cooperative CRNs– Between SUs.

– Between PUs and SUs.

• Green Cognitive Small Cells


28

Green Energy Utilization in CRN (Challenges)

Simple decision policies are required to analytically balance energy consumption and harvesting.

Environment-aware green topology management and resource allocation schemes

(Artificial Intelligence for Green CR).

Mobile charging which relies on the wireless energy transfer.

Sharing/Trading sensing results is a form of power balancing.


29










30

Cloud-based Cognitive Radio and Challenges

By using its capabilities of memory and computational capacity, Cloud computing

platform can enhance spectrum management, reduce energy consumption and

frequent hardware upgrades.

Development of spectrum management policies which describe the role of cloud

data centers in the cloud based CRN.

New protocols are required to manage the flow of information between various cloud

data centers and CRN nodes.

Security: CRN nodes need to know which data centers have access to the spectrum

info.

Compare the security and performance of commercial cloud providers in their ability

to provide effective services to the CRN nodes.

Audit the security and performance of cloud providers such that QoS for CRN nodes can

be met.

31










32

CR MAC Challenges

MAC Design focusing on

energy.

Improve time synchronization

and network coordination for

SUs without dedicated CCC.

A need to develop more practical PU activity models by

considering the characteristics of

access technologies as well as types of

traffic.

Ensuring a reliable network coordination and reconfiguration

mechanism.

QoS-aware MAC

protocols

33










34

Cognitive Radio Wireless Sensor Networks(CRSN)

CRSN Challenges

Low energy consumption spectrum

sensing design

Dynamic spectrum aware cluster formation and

maintenance techniques

Fault Tolerance

QoS

Security

• Clustered topology: Sensor nodes have a leader for a group called as cluster head which may perform operation of spectrum sensing and local spectrum bargaining.

• Heterogeneous and Hierarchical CRSN: Actor node equipped with more power so it can be works as relay node due to longer transmission range.

Source: Shailesh V. Kumbhar, Asha Durafe, “Cognitive Radio Sensor Network Future of Wireless Sensor Network”, International Journal of Advanced Research in Computer and Communication Engineering vol. 4, no. 2, 2015.

Military and Public Security, Home Appliances and Indoor Applications, Bandwidth-Intensive Applications, Real-Time Surveillance Applications, …

More about WSN

35










36

Regulatory Agencies Involved in CR and Activities

Federal Communications Commission (FCC) • Report in 2002, 2006 and 2008. • FCC released the final rules for

“Unlicensed Operation in the TV Broadcast Bands” in 2010/2011.

Office of Communications (Ofcom)• In 2009 and 2015 reports, Ofcom

released a proposal which allowed unlicensed cognitive access to the spectrum.

• Ofcom suggested: (Master/Slave) (another policy for power limits)– Sensing– Geolocation– Beacon (not any more)

Conférence Européenne des Administrations des Postes et des Télécommunications (CEPT) – (CEPT’s SE43)

Fixed White Space DeviceOperates from a specified stationary location

Suitable for commercial Wi-Fi Hot-Spots, rural broadband distribution, or cellular-style installations.

Operate at comparatively higher power and with antennas mounted on a tall building or mast.

Due to its stronger signal, fixed devices are more strict on where and when the devices can operate.

Personal/Portable White Space Device

laptops, Wi-Fi access points, tablets, and smartphones.

Mode I: devices do not need geolocation capability or access to a database.

Mode II: devices must have geolocation capability (±50 m ) and the means to access a database for

list of available channels.

37

Spectrum Database (sample)

Information gathered from all TVWS devices:•The device’s geolocation•Its device type (Fixed, Portable Mode I, Mode II)•Its device identifier, which includes FCC ID and manufacturer serial no.•Data kept (30 days for portable, indefinitely for fixed)

38

Regulatory and Standardization(Challenges)

Roadmap for the time phased

transition to the new spectrum

management paradigm to consider

legacy issues and special band issues.

Issues which need to be

addressed by the regulatory bodies

be identified.

Harmonizing Terminology and

Reference Models.

Regulatory Dimensions to be Considered

(aspects of equipment,

responsibility, cognitive pilot

channels,…)

Potential Risks and Benefits that are related to CR and SDR technologies (Part of the SWOT

analysis)

Regulatory Framework to Encourage the Research and the

Development of CR. (for example,

allocating a block of spectrum for CR

control and enabling secondary licensing, …)

39










40

Cognitive Radio – Business ModelKey Actors

Infrastructure Vendors

Regulators

Challenger Operators

Incumbent Operators

Content Providers

Equipment Vendors

41

Business Model for TVWS Network(SpectrumBridge®) – first FCC-certified geolocation database operator

Source: Yuan Luo, Lin Gao ; Jianwei Huang, “Business modeling for TV white space networks”, IEEE Communications Magazine, vol. 53, no. 5, pp. 82-88, 2015.

Spectrum Market(SpecEx)

• For underutilized Licensed TV channels

• The database acts as a spectrum broker to facilitate

the trading process

Information Market(White Space Plus)

• Unlicensed TV channels used by public and shared usage.

• Its quality are not guaranteed.• The database has more information regarding the

quality of TV channels• This information can be used by unlicensed WSDs to

improve their performance.

42

Cognitive Radio – Business ModelContent Provider - Business Model (sample)

• Value propositions: Offered Products / services.

• Customer segments: Target customer groups.

• Channels: Ch. for reaching the customer.

• Customer relationships: Types of relationships created with the different customer segments.

• Revenue streams: How the company earns money.

• Key resources: Assets depends on.

• Key activities: Most important activities the company must perform in order to operate successfully.

• Key partnerships: Key partners needed to create and deliver the value proposition.

• Cost structure: Describes the costs and their implications for the business model.

43

CR Promising Business Scenarios

Promising business

scenarios to be identified

Mobile operators

use TVWS to delay or replace

deployment of a more

dense networkMobile

operators using TVWS in countries

with very high

spectrum prices

Use TVWS for indoor systems

provided by local or mobile operators.

44

More …

Centralized/Distributed Algorithms for CRN Management.

CR I

mple

me

ntati

ons, T

est-

beds a

nd S

pectr

um

Meas

ure

me

nts.

CR Techniques for Offloading.

CRNs for IoT.

CR Satellite

45

Thank You

46

Backup Slides

Joseph Mitola and Cognitive Radio

The concept of CR was first proposed by Joseph Mitola III in a seminar at (the

Royal Institute of Technology in Stockholm) in 1998 and published in an

article by Mitola and Gerald Q. Maguire in 1999.

• Mitola later described CR as:“The point in which wireless Personal digital assistants (PDAs) and the related

networks are sufficiently computationally intelligent about radio resources and related computer-to-computer communications to detect user communications needs as a function of use context, and to provide radio resources and wireless services most

appropriate to those needs”

Back47

Cognitive Radio - Definition• International Telecommunication Union (ITU)

– ITU: A radio or system that senses, and is aware of, its operational environment and can dynamically and

autonomously adjust its radio operating parameters accordingly.

• Federal Communications Commission

– FCC: CR is a radio that can change its transmitter parameters based on interaction with the environment in

which it operated.

• National Telecommunication and Information Administration (NTIA)

– NTIA: A radio or system that senses its operational electromagnetic environment and can dynamically and

autonomously adjust its operating parameters to modify system operation, such as maximize throughput,

mitigate interference, facilitate interoperability, access secondary markets.

• Wireless World Research Forum

– WWRF: Cognitive radio employs a dynamic time-frequency-power based radio measurement and analysis of

the RF environment, to make an optimum choice of carrier frequency and channel bandwidth to guide the

transceiver in its end-to-end communication, with quality of service being an important design requirement.

48Back

• Spectrum sensing: Detecting unused spectrum and

sharing the spectrum without harmful interference with

other users.

• Spectrum decision: CR networks need to decide which

suitable spectrum bands can be used by secondary user.

• Spectrum mobility: Maintaining seamless

communication requirements during the transition to

better spectrum. Furthermore, to implant this process,

the spectrum mobility in CR networks is divided into two

parts, spectrum handoff and connection management to

compensate handoff delay.

• Spectrum sharing: Providing the fair spectrum scheduling

method among coexisting CR users.

Cognitive Radio Cycle

Back

50

Overview of Spectrum Sensing Methods

Sp. sensing Method

Disadvantages Advantages

Matched filter

Requires a priori info on PU transmissions, and extra hardware on nodes for synchronization with PUs.

Best in Gaussian noise. Needs shorter sensing duration (less power consumption).

Energy detection

Requires longer sensing duration (high power consumption). Accuracy highly depends on noise level variations.

Requires the least amount of computational power on nodes.

Feature detection

Requires a priori knowledge about PU transmissions. Requires high computational capability on nodes.

Most resilient to variation in noise levels.

Interference Temperature

Requires knowledge of location PU and imposes polynomial calculations based on these locations.

Recommended by FCC. Guarantees a predetermined interference to PU is not exceeded.

Spectrum Sensing

Cooperative

Detection

Non Cooperati

ve Detection

Energy Detection

Matched Filter

Detection

Cyclostationary Feature Detection

Interference based Detection

BackSource: Shailesh V. Kumbhar, Asha Durafe, “Cognitive Radio Sensor Network Future of Wireless Sensor Network”, International Journal of Advanced Research in Computer and Communication Engineering vol. 4, no. 2, February 2015.

51

Comparison of Cognitive Radio Paradigms

Underlay Overlay InterweaveNetwork Side Information: SUs know interference caused to PUs.

Network Side Information: SUs know channel gains, encoding techniques and possibly the transmitted data sequences of the primary users.

Network Side Information: SUs identify spectrum holes from which the primary users are absent.

Simultaneous Transmission: SUs can transmit simultaneously with PUs as long as interference caused is below an acceptable limit.

Simultaneous Transmission: SUs can transmit simultaneously with the PUs; to relay the PUs’ data sequences.

Simultaneous Transmission: SUs transmit simultaneously with a PU only when there is missed detection of the PU activity

Transmit Power Limits: Secondary user’s transmit power is limited by a constraint on the interference caused to PUs.

Transmit Power Limits: SUs can transmit at any power, the interference to primary users can be offset by relaying the PUs’ data sequences.

Transmit Power Limits: Secondary user’s transmit power is limited by the range of PU activity it can detect.

Hardware: SUs must measure the interference they cause to PUs’ receivers by either sounding and exploiting channel reciprocity or via cooperative sensing.

Hardware: SUs must also listen to PU transmissions. Encoding and decoding complexity is also significantly higher than other paradigms.

Hardware: Receiver must be frequency agile or have a wideband front end for spectrum hole detection.

Back

52

Cognitive Radio MAC Protocols - Example

CR MAC

Centralized

CSMA-MAC(Random Access – Single Radio)

IEEE-802.22(Time Slotted – Single Radio)

DSA driven(Hybrid MAC – Single Radio)

Distributed

Single Radio

SRAC , HC-MAC (Random Access )

OS-MAC (Hybrid MAC)

Multiple Radio

DOSS, DCA-MAC (Random Access)

C-MAC (Time Slotted)

SYN-MAC, Opportunistic MAC (Hybrid MAC)

• Time-slotted MAC protocols–Require network-wide

synchronization and operate by dividing time into discrete slots for both the control channel and data transmission.

• The random access protocols –Do not require time

synchronization, and are based on the CSMA principle.

• Hybrid MAC protocols–The control signaling occurs in

synchronized time slots and the data transmission follows random access channel schemes, or–Predefined durations for the

control/data frame – however, the access to the channel within each control or data transmission duration is completely random.

BackSource: Mahfuzulhoq Chowdhury, Asaduzzaman, and M. Fazlul Kader, “Cognitive Radio MAC Protocols: A Survey, Research Issues, and Challenges”, Smart Computing Review, vol. 5, no. 1, 2015.

C-MAC: Cognitive MACHC MAC: Hardware Constrained MACPOMDP: partially observable Markov decision processOP-MAC: Opportunistic MACSRAC: Single-Radio adaptive Channel DOSS: Dynamic Open Spectrum SharingDCA: Distributed Channel AssignmentDSA: Dynamic Spectrum Access

53

5G - Features

Source: http://parallelwireless/5GPP Vision - Radar diagram of 5G disruptive capabilities Back

54

WSN - Applications

Source: Tifenn Rault, Abdelmadjid Bouabdallah, Yacine Challal. Energy Efficiency in Wireless Sensor Networks: a top-down survey. Computer Networks, Elsevier, vol. 67, no. 4, pp. 104-122, 2014. Back

55

Classification of Energy-Efficient Mechanisms in WSN

Source: Tifenn Rault, Abdelmadjid Bouabdallah, Yacine Challal. Energy Efficiency in Wireless Sensor Networks: a top-down survey. Computer Networks, Elsevier, vol. 67, no. 4, pp. 104-122, 2014.

56

Cognitive Radio TestbedsCR Platforms• Lyrtech’s small form factor SDR development platform

– Flexible, powerful, extremely expensive, too complex for research.

• Microsoft Research SORA

• Eurecom Open-Air-Interface

– Support LTE, limited support, expensive)

• Ettus/NI USRP

– Relatively cheap, Wide use, poor RF performance

CR Software

• GNU Radio (most common used, written in C++ and python, supported by Ettus)

• OSSIE (by Virginia Tech, written in C++, …)

• IRIS (by Trinity College Dublin, written in C++, configuration method based on XML)• ASGARD (by Aalborg University in Denmark, written in C++, tackle the challenge

of next generation telecomm. systems using multi user MIMO and aggregated spectrum techniques.

Testbeds in CRN

• Gain CR product credibility

• Check realistic limitations for CR algorithms

• Check the real performance of CRNs

57

Multiple Dimensions of Spectrum Space

• Legacy sensing algorithms monitor and supervise the

spectrum through three conventional dimensions:

frequency, time and space domains.

• However, other degrees of freedom such as the used

code and the angle of arrival may be used.

Challenges

• Hybrid and new dimensions to create new spectrum

opportunities and optimize the utilization of spectral

resources.

Comparison of Transport Protocols in CRNs (single hop)

Source: X. Zhong, Y. Qin, and Li Li, “Transport Protocols in Cognitive Radio Networks: A Survey”, KSII Transactions on Internet and Information Systems (TIIS), vol. 8, no. 11, pp. 3711-3730, 2014.

58More

Comparison of transport protocols in CRNs (Multiple hop)

Back

to T

CP in

Cog

nitiv

e Ra

dio

X.

Zh

on

g,

Y. Q

in,

an

d L

i L

i, “

Tra

nsp

ort

Pro

toco

ls i

n C

og

nit

ive R

ad

io N

etw

ork

s:

A S

urv

ey”

, K

SII

Tra

nsa

ctio

ns

on

In

tern

et

an

d I

nfo

rmati

on

Sys

tem

s (T

IIS

), v

ol.

8,

no.

11

, p

p.

37

11

-37

30

, 2

01

4.

DO

I:

htt

p:/

/dx.

doi.org

/10

.38

37

/tiis.

20

14

.11

.00

4

http://dx.doi.org/10.3837/tiis.2014.11.004

60

CR Attacks(1/2)

Back to Cognitive Radio Main Attacks

Sour

ce:

D. H

lava

cek,

J.M

. Cha

ng, A

laye

red

appr

oach

to c

ogni

tive

radi

o ne

twor

k se

curit

y: A

sur

vey,

Co

mpu

ter N

etw

orks

., 20

14.

http:

//dx

.doi

.org

/10.

1016

/j.c

omne

t.201

4.10

.001

61

CR Attacks(2/2)

Source:D. Hlavacek, J.M. Chang, A layered approach to cognitive radio network security: A survey, Computer Networks., 2014. http://dx.doi.org/10.1016/j.comnet.2014.10.001

Back to Cognitive Radio Main Attacks

National Telecommunication Institute Cognitive Radio Testbed (NTI-CRT)

NTI-CRT - Objective

• Objectives– To create a real national cognitive radio test-

bed. – Scientific and engineering understanding of

the technical constraints on the design and regulation

– Proposal for future cognitive radio systems operating on new bands.

Primary/Secondary Transmitters

Primary Transmitter (PTx)

Secondary Transmitter (STx)

Primary/Secondary Receivers

Primary Receiver (PRx)

Secondary Receiver (SRx)

Dispatcher

Spectrum Sensing USRP Spectrum Management USRP

National Telecommunication Institute (NTI) Cognitive Lab Architecture

NTI-CRT - Scenarios

Primary/Secondary Transmitters

Primary Transmitter (PTx)

Secondary Transmitter (STx)

Primary/Secondary Receivers

Primary Receiver (PRx)

Secondary Receiver (SRx)

Dispatcher

Spectrum Sensing USRP Spectrum Management USRP

National Telecommunication Institute (NTI) Cognitive Lab Architecture

• Sce 1: Prim Ch1 Sec Ch2 No Jamming• Sce 2: Prim Ch1 Sec Ch2 Jam Ch0• sce 3: Prim needs Ch1 Sec Ch2 Jam Ch1

– Dispatcher finds Jamming on the desired channel– Dispatcher moves Primary to another Jam free channel

(Ch0 as an example)

• Sce 4: Prim needs Ch2 Sec Ch2 Jam Ch1– Dispatcher finds Secondary on the desired channel– Dispatcher allocates Primary to the desired channel– Dispatcher moves Secondary to another Jam free channel

(Ch3 as an example)

• Sce 5: Secondary needs Ch2 Prim Ch2 Jam Ch1– Dispatcher finds Primary on the desired channel– Dispatcher rejects the Secondary Required Channel– Dispatcher moves Secondary to another Jam free channel

(Ch3 as an example)

• Sce 6: Jamming needs Ch0 Prim Ch1 Sec Ch0– Dispatcher finds Primary on the desired channel– Dispatcher rejects the Secondary Required Channel– Dispatcher moves Secondary to another Jam free channel

(Ch2 as an example)

• Sce 7: Jamming needs Ch2 Prim Ch1 Sec Ch2– Dispatcher finds Secondary on the desired channel– Dispatcher moves Secondary to another Jam free channel

(Ch0 as an example)

NTI-CRT – Scenario (1) – No jamming

NTI-CRT – Scenario (2) – Ch1 jamming

NTI-CRT – Scenario (3)(1/2) Prim needs Ch1 Sec Ch2 Jam Ch1






NTI-CRT – Scenario (6)(1/2) Jamming needs Ch0 Prim Ch1 Sec Ch0


