Cognitive Radio PPT

Advanced Topics in Wireless Communications COGNITIVE RADIO NETWORKS

INTRODUCTION

2

FIXED SPECTRUM ASSIGNMENT

3

Fixed Spectrum Utilization Maximum Amplitudes Amplitude (dBm)

Heavy Use

Heavy Use

Sparse Use

Medium Use

Frequency (MHz) 4

Problems of Fixed Spectrum Utilization 

 

Spectrum usage is concentrated on certain portions of the spectrum A significant amount of the spectrum remains unutilized. According to FCC (Federal Communication Commission): Utilization of the fixed spectrum assignment is approx. 15-85% based on temporal and geographical variations

 Limited Available Spectrum and Inefficient Spectrum Usage! 5

COGNITIVE RADIO NETWORKS; DYNAMIC SPECTRUM ALLOCATION NETWORKS (DSANs);

xG INITIATIVE

Dynamic Spectrum Allocation 6

COGNITIVE RADIO 





A “Cognitive Radio” is the key enabling technology for Dynamic Spectrum Access!! Capability to use or share the spectrum in an opportunistic manner. “BANDWIDTH HARVESTING”

Dynamic spectrum access techniques allow the CR to operate in the best available channel. 7

SPECTRUM MANAGEMENT FRAMEWORK 1) Determine which portions of the spectrum is available and detect the presence of licensed users when a user operates in a licensed band

(Spectrum Sensing)

2) Select the best available channel (Spectrum Decision) 3) Coordinate access to this channel with other users (Spectrum Sharing)

4) Vacate the channel when a licensed user is detected (Spectrum Mobility). 8

2. COGNITIVE RADIO

9

WHAT IS A COGNITIVE RADIO? A “Cognitive Radio” is a radio that can change its transmitter parameters based on interaction with the environment in which it operates. (Federal Com Commission’05) FCC (Non-Federal Use of the Spectrum) 10

WHAT IS A COGNITIVE RADIO? A radio or system that senses its operational EM 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..

NTIA (National Telecom and Info Administration)’05

US Department of Commerce: (NTIA)

(FEDERAL USE OF THE SPECTRUM)

11

WHAT IS A COGNITIVE RADIO? A radio or system that senses and is aware of its operational environment and can dynamically and autonomously adjust its radio operating parameters accordingly.

ITU (Wp8A working document)’05

12

WHAT IS A COGNITIVE RADIO? A type of radio that can sense and autonomously reason about its environment and adapt accordingly. This radio could employ knowledge representation, automated reasoning, and machine learning mechanisms in establishing conducting or terminating communication or networking functions with other radios.

CRs can be trained to dynamically and autonomously adjust its operating parameters.

IEEE 1900.1 Group

13

HOW ABOUT???

A RADIO THAT IS COGNITIVE !!!!

14

ADVANTAGES OF COGNITIVE RADIO  Senses

RF Environment and modifies frequency, power or modulation

 Allows

for Real Time Spectrum Management

 Significantly

Increases Spectrum Efficiency 15

Possible CR Functionalities 

Dynamic Frequency Selection (DFS)



Adaptive modulation Transmit Power Control (TPC)





Adjust transmit parameters based on location spectrum sharing between a licensee and a third party Other functionalities are being developed as technology progresses 16

Analogy between a Cognitive Radio and a Car Driver

Cognitive Radio’s Capabilities:  Senses, and is aware of, its operational environment and its capabilities  Can dynamically and autonomously adjust its radio operating parameters accordingly  Learns from previous experiences  Deals with situations not planned at the initial time of design 17

Analogy between a Cognitive Radio and a Car Driver

Car Driver’s Capabilities:    

Senses, and is aware of, its operational environment and its capabilities Can dynamically and autonomously adjust the driving operation accordingly Learns from previous experiences Deals with situations not planned at the initial time of learning to drive

 They behave almost exactly the same!!! 18

Spectrum Hole Concept Power

Spectrum Hole

Frequency

Spectrum occupied by Licensed users

Time

19

Ultimate Objective of Cognitive Radio  CR enables the usage of temporally unused spectrum  Spectrum Hole or White Space. If this band is further used by a licensed user, CR moves to another spectrum hole or stays in the same band Alters its transmission power level or modulation scheme to avoid interference. 20

MAIN CHARACTERISTICS OF CR

A. Cognitive Capability B. Reconfigurability (SDR)

21

Cognitive Capability SPECTRUM AWARENESS!! – – – – –

Capture or sense the information (e.g., licensed user’s activity) from radio environment Capture the temporal and spatial variations in radio environment Avoid interference to other users Identification of unused spectrum portions at a specific time or location Selection of best spectrum and appropriate operating parameters 22

Reconfigurability (SDR functionality) Enabling the radio * to be dynamically programmed to transmit and receive on a variety of frequencies according to the radio environment and

* to use different transmission access technologies supported by its hardware design 23

Physical Architecture of the Cognitive Radio (Wideband RF/Analog Front-End Architecture) PSD of the received Available licensed signal Channel

Power Spectrum Density (PSD)

...

Baseband (low freq.) (A/D Conversion/Signal Processing)

Band of interest

...

Pass-band (high freq.) (for communications)

Frequency

24

Challenges for Development of CR RF Front-End Wideband RF antenna receives signals from various transmitters operating at different power levels, bandwidths, and locations.

 the RF front-end must be able to detect a weak signal in a large dynamic range.  Requires a multi GHz speed A/D converter with high resolution  infeasible!! 25

Alternative Approach: Directional Antennas Use multiple antennas such that signal filtering is performed in the spatial domain rather than in the frequency domain.  Multiple antennas can receive signals selectively using beamforming techniques.

f1

f2

Licensed User f1

f1

Licensed User f2 f2

26

3. ARCHITECTURE

27

Cognitive Radio Network Architecture Spectrum Band

Unlicensed Band Primary Network Access

Licensed Band I Primary User

CR User

CR Base-station

Primary Base-station

Licensed Band II

Primary Network

Spectrum Broker

Other Cognitive Radio Networks

CR Network Access

Cognitive Radio Network (With Infrastructure) 28

Cognitive Radio Network Architecture Spectrum Band

Unlicensed Band

CR User

Primary Network Access

Licensed Band I Primary User

Primary Base-station

Licensed Band II

Primary Network

CR Ad Hoc Access

Cognitive Radio Network (Without Infrastructure) 29

Cognitive Radio Network Architecture Spectrum Band

Unlicensed Band Primary Network Access

Licensed Band I Primary User

Primary Base-station

Licensed Band II

Primary Network

CR User

CR Ad Hoc Access

Cognitive Radio Network (Without Infrastructure)

Spectrum Broker

CR Base-station

CR Network Access

Other Cognitive Radio Networks

Cognitive Radio Network (With Infrastructure) 30

Architecture Primary Network (Primary User, Primary Base Station)

Cognitive Radio Network (CR User, CR Base Station)  Spectrum Broker 31

Primary Network * An existing network infrastructure (or ad hoc network) which has an access right to a certain spectrum band. * Examples include the common cellular and TV broadcast networks.

32

Primary User

(or Licensed User) *

Has a license to operate in a certain spectrum band.

*

This access can only be controlled by the primary basestation and should not be affected by the operations of any other unlicensed users.

REMARK: Primary users do not need any modification or additional functions for co-existence with CR base-stations and CR users. 33

Primary Base-Station (or Licensed Base-Station)

 A fixed infrastructure network component which has a spectrum license such as BTS in a cellular system.

 Does not have any CR capability for sharing spectrum with CR users.  It may be requested to have both legacy and CR protocols for the primary network access of CR users. 34

Cognitive Radio Network

(or Dynamic Spectrum Access Network, or Secondary Network or Unlicensed Network)

* Does not have license to operate in a desired band. * Hence, the spectrum access is allowed only in an opportunistic manner.

* CR networks can be deployed both as an infrastructure network and an ad hoc network 35

Cognitive Radio User

(or Unlicensed User, Secondary User)

 has no spectrum license Hence, additional functionalities are required to share the licensed spectrum band.

36

Cognitive Radio Base-Station

(or Unlicensed Base-Station or Secondary Base-Station)

–

A fixed infrastructure component with CR capabilities.

–

CR base-station provides single hop connection to CR users without spectrum access license.

–

Through this connection, a CR user can access other networks. 37

Spectrum Broker (or Scheduling Server)

– A central network entity that plays a role in sharing the spectrum resources among different CR networks. – It can be connected to each network and can serve as a spectrum information manager to enable coexistence of multiple CR networks.

38

Architecture  CR Network Access: CR users can access their own CR base-station both on licensed and unlicensed spectrum bands.

 CR Ad hoc Access: CR users can communicate with other CR users through ad hoc connection on both licensed and unlicensed spectrum bands.

 Primary Network Access: CR users can also access the primary base-station through the licensed band. 39

Classifications CR Network on Licensed Band CR user is capable of using bands assigned to licensed users, apart from unlicensed bands, such as ISM band.  CR Network on Unlicensed Band CR can only utilize unlicensed parts of radio frequency spectrum. 40

Cognitive Radio Network on Licensed Band Primary Base-Station Primary Network Dynamic Spectrum Access

CR Base-station

Primary User

CR User

CR User Cognitive Radio Network

41

CR Network on Licensed Band Temporally unused spectrum holes exist in the licensed spectrum band. CR networks can exploit these spectrum holes through cognitive communication techniques. In Figure, CR network coexists with the primary network at the same location and on the same spectrum band 42

CR Network on Licensed Band  Main purpose of the CR network is to determine the best available spectrum

 Here in the licensed band, CR functions are aimed at the detection of the presence of primary users.

 Channel capacity of the spectrum holes depends on the interference at the nearby primary users. 43

CR Network on Licensed Band  Interference avoidance with primary users is the most important issue here  Also if primary users appear in the spectrum band occupied by CR users, they should vacate the current spectrum band and move to the new available spectrum immediately  called spectrum handoff. 44

Cognitive Radio Network on Unlicensed Band Spectrum Broker

Cognitive Radio Network A

CR Base-Station

Cognitive Radio Network B CR Ad Hoc Network

CR User

45

CR Network on Unlicensed Band  Since there are no license holders, all network entities have the same right to access the spectrum bands.  Multiple CR networks co-exist in the same area and communicate using the same portion of the spectrum.  Intelligent spectrum sharing algorithms can improve the efficiency of spectrum usage and support high QoS.

46

CR Network on Unlicensed Band CR users focus on detecting the transmissions of other CR users. Since all CR users have the same right to access the spectrum, CR users should compete with each other for the same unlicensed band.

47

CR Network on Unlicensed Band REQUIREMENTS: 1. Sophisticated spectrum sharing methods among CR users. 2. Fair spectrum sharing among networks if multiple CR network operators reside in the same unlicensed band.

48

4. COGNITIVE CYCLE

49

Cognitive Cycle A CR determines appropriate communication parameters and adapts to the dynamic radio environment Tasks required for adaptive operation in open spectrum referred as COGNITIVE CYCLE.

50

Cognitive Cycle Transmitted Signal

Spectrum Mobility

Spectrum Sharing

Radio Environment RF Stimuli

Licensed User Detection Decision Request

Channel Capacity

Spectrum Sensing Spectrum Hole

Spectrum Decision

51

Spectrum Sensing A CR monitors the available spectrum bands, captures their information, and then detects the spectrum holes.

52

Spectrum Decision – Based on the spectrum availability, CR users can determine a channel. – This operation not only depends on spectrum availability, but it is also determined based on internal (and possibly external) policies.

53

Spectrum Sharing  Multiple CR users try to access the spectrum  CR network access should be coordinated in order to prevent multiple users colliding in overlapping portions of the spectrum.

54

Spectrum Mobility  CR users are regarded as "visitors" to the spectrum.  If primary users need a specific portion of the spectrum then the CR users must continue in another vacant portion of the spectrum.

55

Reconfigurability Capability of adjusting operating parameters for the transmission on-the-fly without any modifications on the hardware components. This capability enables CR to adapt easily to the dynamic radio environment.

56

Reconfigurable Parameters i) ii) iii) iv)

Operating Frequency Modulation Transmission Power Communication Technology

57

Operating Frequency A CR is capable of changing the operating frequency. Based on the information about the radio environment, the most suitable operating frequency can be determined and

the communication can be dynamically performed on this appropriate operating frequency. 58

Modulation 

A CR should reconfigure the modulation scheme adaptive to the user requirements and channel conditions.

Example: Delay Sensitive Applications data rate important  Modulation scheme enabling higher spectral efficiency!! Example: Loss-Sensitive Applications  error rate important !  Modulation scheme with low bit error rate.. 59

Transmission Power Transmission power can be reconfigured within the power constraints. If higher power operation is not necessary, CR reduces the transmitter power to a lower level to allow more users to share the spectrum and to decrease the interference.

60

Communication Technology A CR can be used to provide interoperability among different communication systems.

61

Reconfigurable Parameters  Not only at the beginning of a transmission but also during the transmission.  Parameters can be reconfigured such that * CR is switched to a different spectrum band * Tx and Rx parameters are reconfigured * Appropriate communication protocol parameters and modulation schemes are used. 62

5. SPECTRUM SENSING

63

What is Spectrum Sensing ? How to detect spectrum holes by the COGNITIVE RADIO so that it can adapt itself to its environment !!

64

Spectrum Sensing Transmitted Signal

Spectrum Mobility

Spectrum Sharing

Radio Environment RF Stimuli

Primary User Detection Decision Request

Channel Capacity

Spectrum Sensing Spectrum Hole

Spectrum Decision

65

EFFICIENT WAY TO DETECT SPECTRUM HOLES

A general CR based communication scenario No interaction between CR user and Primary Tx/Rx

CR User 2

CR user must rely on locally sensed signals to infer primary user activity

Licensed band 2 CR User 1 Primary Tx

Licensed band 1

Channels found occupied by CR user (Licensed bands 1 and 2) are now avoided during communication between CRs

Primary Rx

66

EFFICIENT WAY TO DETECT SPECTRUM HOLES !!

 Detect primary users that are receiving data within the communication range of a CR user.  In reality  Difficult for a CR to detect primary user activity in the absence of interaction between primary users and itself.  RECENT RESEARCH  How to detect primary users based on “local observation” of CR users (from its environment)

67

Classification of Spectrum Sensing Techniques

Spectrum Sensing

Matched Filter Detection

Transmitter Detection

Receiver Detection

Energy Detection

Cyclostationary Feature Detection

Interference Temperature Management

68

Transmitter Detection  CR should distinguish between Used and Unused spectrum bands.  CR should have the capability to determine if a signal from primary user (transmitter) is locally present in a certain spectrum.  Transmitter Detection Approach  Detection of the signal (weak signal as the worst case) from a primary user through local observations of CR users. 69

Basic Hypothesis Model for Transmitter Detection

The signal x(t) received (detected) by the CR (secondary) user is

H0 n(t ) x(t )    hs (t )  n(t ) H1 where n(t)  AWGN (Additive White Gaussian Noise) s(t)  Transmitted signal of the primary user h  Amplitude gain of the channel

H0  Null hypothesis  No licensed user signal in a certain spectrum band. H1  Alternative hypothesis  There exists some licensed user signal. 70

Transmitter Detection D. Cabric, S. M. Mishra, and R. W. Brodersen, “Implementation Issues in Spectrum Sensing for Cognitive Radios,” in Proc. 38th Asilomar Conference on Signals, Systems and Computers, pp. 772776, Nov. 2004.

Three schemes are generally used for the transmitter detection according to the hypothesis model. –

– –

Matched Filter Detection Energy Detection and Cyclostationary Feature Detection Techniques

71

Matched Filter Detection Spectrum Sensing Transmitter Detection

Matched Filter Energy Detection Detection

Receiver Detection

Interference Temperature Management

Cyclostationary Feature Detection

72

Matched Filter Detection Matched Filter Received Signal r(t) = s(t) + n(t)

0

Threshold Device H1

r ( ) s (T  t   )d

Y

 Y  H o

Decide H0 or H1

r(t)

s(t) 0



t

Sample at t = T

T

0

maximum at T

T 0

T

2T

s(t): the transmitted signal of the primary user n(t): AWGN T: Symbol interval  : Threshold

0

T

2T

Need  Transmitted signal information s(t)  Synchronization for sampling timing (t=T) 73

Matched Filter Detection A. Sahai, N. Hoven and R. Tandra, “Some Fundamental Limits in Cognitive Radio, in Proc. Allerton Conf. on Comm., Control and Computing 2004

 When the shape of the primary user signal is known to the CR user, the optimal detector in an AWGN channel is the matched filter since it maximizes the received SNR.

Advantage of Matched Filter:

Requires less time to achieve high processing gain due to coherency

74

Matched Filter Detection But

it requires a priori knowledge of the primary user signal such as the modulation type and order, the pulse shape, and the packet format

 Hence, if this information is not accurate, then the matched filter performs poorly.  However, since most wireless network systems have pilot, preambles, synchronization word or spreading codes, these can be used for the coherent detection. 75

Energy Detection Spectrum Sensing

Matched Filter Detection

Transmitter Detection

Receiver Detection

Energy Detection

Cyclostationary Feature Detection

Interference Temperature Management

76

Energy Detection D. Cabric, S. M. Mishra, and R. W. Brodersen, “Implementation Issues in Spectrum Sensing for Cognitive Radios,” in Proc. 38th Asilomar Conference on Signals, Systems and Computers, pp. 772776, Nov. 2004. H. Tang, “Some Physical Layer Issues of Wideband Cognitive Radio System,” in Proc. IEEE DySPAN, pp. 151159, Nov. 2005.

 If the CR user cannot gather sufficient information about the primary user signal s(t), the matched filter is not suitable.  However, if the CR user is aware of the power of the random Gaussian noise, then the energy detector is optimal. 77

Energy Detection A. Ghasemi and E. S. Sousa, “Collaborative Spectrum Sensing for Opportunistic

Access in Fading Environment,“ in Proc. IEEE DySPAN, pp. 131-136, Nov. 2005

Squaring Device

Filtering Input

r (t )

()

Integrator T

2

r 2 (t )



0

dt

Threshold Device H1

Y



T

0

r 2 (t )dt

 Y  Ho

Decide H0 or H1

T: Observation (sensing) Time

78

Energy Detection In order to measure the energy of the received signal by the CR user, the output signal of bandpass filter with bandwidth W is squared and integrated over the observation interval T.

79

Energy Detection

 Finally, the output of the integrator, Y, is compared with a threshold, λ, to decide whether a licensed user is present or not. (AWGN case)

80

Energy Detection  A low Pd  missing the presence of the primary user with high probability  increases the interference to the primary user  A high Pf  low spectrum utilization (since false alarms increase the number of missed opportunities (white spaces)).  Implementation is easy!! 81

Problems of Energy Detection  Performance is susceptible to uncertainty in noise power. SNR problem!!!  Energy detector cannot differentiate signal types but can only determine the presence of the signal.  Energy detector is prone to the false detection triggered by the unintended signals.  Energy detector needs longer sensing time – Matched filter: T~1/SNR when detecting weak signals: – Energy Detector: T~1/SNR2 SNR < 1 (-10dB to -40 dB) 82

Cyclostationary Feature Detection Spectrum Sensing Transmitter Detection

Matched Filter Detection

Energy Detection

Receiver Detection

Interference Temperature Management

Cyclostationary Feature Detection 83

Cyclostationary Feature Detection D. Cabric, S. M. Mishra, and R. W. Brodersen, “Implementation Issues in Spectrum Sensing for Cognitive Radios,” in Proc. 38th Asilomar Conference on Signals, Systems and Computers, pp. 772776, Nov. 2004. A. Fehske, J. D. Gaeddert, and J. H. Reed, “A New Approach to Signal Classification Using Spectral Correlation and Neural Networks,” in Proc. IEEE DySPAN, pp. 144150, Nov. 2005.

 Modulated signals are in general coupled with sine wave carriers, pulse trains, repeating spreading, hopping sequences, or cyclic prefixes, which result in built-in periodicity. 84

Cyclostationary Feature Detection  These modulated signals are characterized as cyclostationary since their mean and autocorrelation exhibit periodicity.

 These features are detected by analyzing a spectral correlation function.  Advantage of the spectral correlation function:  differentiates the noise energy from modulated signal energy 85

Cyclostationary Feature Detection Sine based Cyclostationary Detection Primary Tx frequency repeats over symbol durations at regular intervals T

Problem: Can these cyclical regularities be detected at the CR user?

86

Cyclostationary Feature Detection r(t)

Correlate R(f+ )R*(f- )

r(t) : R(f) :  : R*(f) :

Average over T

Feature detect

Received signal Fourier transform of r(t) Cyclic frequency Complex conjugate of R(f)

If cyclostationary with period T then cycle autocorrelation has component at =1/T. If the correlation factor is high (greater than the threshold), there is a primary user. 87

Cyclostationary Feature Detection H. Tang, “Some Physical Layer Issues of Wideband Cognitive Radio System,” in Proc. IEEE DySPAN, pp. 151159, Nov. 2005.

This scheme performs better than the energy detector in discriminating against noise due to its robustness to the uncertainty in noise power. Computationally complex and requires significantly long observation time.

88

Limitations of the Transmitter Detection Receiver Uncertainty Problem CR Transmitter Range

Interference

Primary Transmitter Range Primary Base-station

Primary User

Shadowing Problem Hidden Terminal Problem due to Shadowing

CR User Interference CR User Cannot detect the transmitter

Interference due to uncertainty of receiver location

CR Transmitter Range

Primary Transmitter Range Primary Base-station

Primary User

Cannot detect the transmitter

89

Receiver Uncertainty Problem With the transmitter detection, the CR user cannot avoid the interference due to the lack of the primary receiver’s information (Fig.a). Moreover, the transmitter detection model cannot prevent the hidden terminal problem.

90

Shadowing Problem A CR user is located in the transmission range of the primary transmitter, but may not be able to detect the transmitter due to the shadowing (Fig. b). Consequently, the sensing information from other users is required for more accurate detection

→ Cooperative Detection 91

Transmitter Detection

Non-Cooperative vs Cooperative Detection 

Detection Method



Transmitter Detection

Matched Filter Detection

Energy Detection

Detection Behavior Transmitter Detection

Cyclostationary Feature Detection

Non-Cooperative Detection

Cooperative Detection

92

Non-Cooperative vs Cooperative Detection  Non-Cooperative Detection – CR users detect the primary transmitter signal independently through their local observations.

 Cooperative Detection - Information from multiple CR users are utilized for primary user detection. – Mitigates multi-path fading and shadowing effects  improves the detection probability in heavily faded/shadowed environments.

93

Cooperative Detection Detect the primary user correctly

CR User 3

Shadowing

BUSY

Cannot detect the primary user due to the obstacles

Primary Base-station

Multi-path fading

CR User 1

Weak signals are received due to the multi-path fading  may not detect the primary user

IDLE

CR User 2 IDLE

Primary User

By exchanging their sensing information, CR users can detect the primary user under fading and shadowing environments 94

Detection and False Alarm Probability for Cooperative Detection

A. Ghasemi and E. S. Sousa, “Collaborative Spectrum Sensing for Opportunistic Access in Fading Environment,“ in Proc. IEEE DySPAN, pp. 131-136, Nov. 2005





Assume n CR users have the same sensing capabilities (same Pd and Pf ) All CR users assume a channel to be occupied even if at least one CR user detects a primary user in that channel.  - Increases the cooperative detection probability Qd - Suitable for a highly faded/shadowed radio environments

95

Detection and False Alarm Probability for Cooperative Detection

A. Ghasemi and E. S. Sousa, “Collaborative Spectrum Sensing for Opportunistic Access in Fading Environment,“ in Proc. IEEE DySPAN, pp. 131-136, Nov. 2005



Note: Cooperative detection also increases the probability of false-alarm. Qd  1  Pr{all n CR users miss the detection }  1  (1  Pd ) n Q f  1  Pr{all n CR users detect the spectrum hole correctly }  1  (1  Pf ) n Qd Qf Pd Pf

is the cooperative detection probability is the cooperative false alarm probability is the non-cooperative (individual) detection probability is the non-cooperative (individual) false alarm probability 96

Detection and False Alarm Probability for Cooperative Detection

Increasing Qf Increasing Qd

Cooperative Detection Probability

Cooperative False Alarm Probability 97

Cooperative Detection Cooperative Methods – –

Provide more accurate sensing performance ! However, they cause overhead traffic and power consumption for exchanging sensing information.

STILL ADDITIONAL PROBLEM: Primary receiver uncertainty problem caused by the lack of the primary receiver location knowledge is still unsolved!! 98

Primary Receiver Detection Spectrum Sensing

Matched Filter Detection

Transmitter Detection

Receiver Detection

Energy Detection

Cyclostationary Feature Detection

Interference Temperature Management

99

Primary Receiver Detection

B. Wild and K. Ramchandran, “Detecting Primary Receivers for Cognitive Radio Applications“ in Proc. IEEE DySPAN, pp. 124130, Nov. 2005.

Primary Base-station

When primary users receive the signals from the transmitter, they emit the LO leakage power.

Local Oscillator (LO) Leakage Power

CR users detect the LO leakage power for the detection of primary users instead of the transmitted signals

CR User Primary User

100

Primary Receiver Detection RF Front-end of the Primary Receiver

Antenna RF Filter

Mixer

Channel Selection Filter

AGC

LNA VCO



PLL

A/D

Local Oscillator - Generates a sine signal for the baseband conversion - CR users detect this signal

101

How can the LO Leakage Power be detected?

 Same methods as before, i.e., (Matched filter detection, Energy detection or Cyclostationary feature detection )

102

How can the LO Leakage Power be detected?

 Primary receiver detection can solve the receiver uncertainty problem in the transmitter detection  However, since the LO leakage signal is typically weak, implementation of a reliable detector is not trivial.  Currently this method is only feasible in the detection of the TV receivers. 103

Interference Temperature Management Spectrum Sensing

Matched Filter Detection

Transmitter Detection

Receiver Detection

Energy Detection

Cyclostationary Feature Detection

Interference Temperature Management

104

Interference Temperature Model

o

Minimum Service Range with Interference Cap

Licensed Signal New Opportunities for Spectrum Access

Power at Receiver

Interference Temperature Limit

Service Range at Original Noise Floor

Original Noise Floor Distance from Licensed Transmitting Antenna

105

Interference Temperature Model The model shows the signal of a radio designed to operate in a range at which the received power approaches the level of the noise floor.  As additional interfering signals appear, the noise floor increases at various points within the service area, as indicated by the peaks above the original noise floor. 106

Interference Temperature Model Model manages interference at the receiver through the interference temperature limit, which is represented by the amount of new interference that the receiver could tolerate.

107

Interference Temperature Model  I.o.w., the interference temperature model accounts for the cumulative RF energy from multiple transmissions and sets a maximum cap on their aggregate level.  As long as CR users do not exceed this limit by their transmissions, they can use this spectrum band. 108

Interference Temperature Measurement Problems  No practical way for a CR to measure or estimate the interference temperature. (CR users cannot distinguish between actual signals from the primary user and noise/interferences).  Interference temperature limit should be location dependent of the primary users which is not easy to determine.  Increasing the interference temperature limit will affect primary network’s capacity and coverage. 109

6. SPECTRUM DECISION

110

Spectrum Decision Transmitted Signal

Spectrum Mobility

Spectrum Sharing

Radio Environment RF Stimuli

Primary User Detection Decision Request

Channel Capacity

Spectrum Sensing Spectrum Hole

Spectrum Decision 111

Spectrum Decision – Unused spectrum bands will be spread over wide frequency range including both unlicensed and licensed bands. – CR networks require capabilities to decide the best spectrum band among the available bands – This notion is called “spectrum decision” and constitutes a rather important but yet unexplored topic in CR networks.

 Spectrum decision is closely related to the channel characteristics and the operations of primary users. 112

Spectrum Decision Usually consists of two steps: 1. Each spectrum band is characterized based on not only local observations of CR users but also statistical information of primary networks. 2. Then, based on this characterization, the most appropriate spectrum band can be chosen. 113

Spectrum Decision 1st Stage Spectrum Characterization 

RF information • Interference • Path

Loss • Wireless Link Error • Link layer delay



Primary Network Information • •

Primary User Activity Holding Time

2nd Stage Decision

Single Spectrum Decision

MultiSpectrum Decision

114

Spectrum Characterization To describe the dynamic nature of CR networks, each spectrum hole should be characterized by considering the time-varying radio environment & the primary user activity and the spectrum band information (e.g., operating frequency and bandwidth). 115

Definitions * * * * *

Interference level Channel error rate Path-loss Link layer delay Holding time

116

Interference  Some spectrum bands are more crowded compared to others.  Hence, the spectrum band in use determines the interference characteristics of the channel.  From the amount of the interference at the primary receiver, the permissible power of a CR user can be derived, which is used for the estimation of the channel capacity. 117

Path Loss  The path loss increases as the operating frequency increases.  Therefore, if the transmission power of a CR user remains the same, then its transmission range decreases at higher frequencies.  Similarly, if transmission power is increased to compensate for the increased path loss, then this results in higher interference for other users. 118

Wireless Link Errors Depending on the modulation scheme and the interference level of the spectrum band, the error rate of the channel changes.

119

Link Layer Delay To address different path loss, wireless link error, and interference, different types of link layer protocols are required at different spectrum bands. This results in different link layer packet transmission delay. 120

Primary User Activity – Since there is no guarantee that a spectrum band will be available during the entire communication of a CR user, it is important to consider how often the primary user appears on the spectrum band. – Primary User Activity is defined as the probability of the primary user appearance during the CR user transmission. 121

Holding Time – Expected time duration that the CR user can occupy a licensed band before getting interrupted. – Obviously, the longer the holding time, the better the quality would be. – Since frequent spectrum handoff can decrease the holding time, previous statistical patterns of handoff should be considered while designing CR networks with large expected holding time.

122

CHANNEL CAPACITY Can be derived from the parameters explained above, is the most important factor for spectrum characterization. Usually, SNR at the receiver is used for capacity estimation.

123

CHANNEL CAPACITY  However, in order to avoid the interference at the primary users, the transmission power of CR users may be limited. Received power 0

 In

case there is no primary user, CR user can transmit with the max. power

2 4 0

Primary user

6 2

Primary user



8 4

CR user

CR user 

Transmission range

In case the primary user is detected, the transmission power of the CR user is constrained to avoid the interference. The location of the primary users can affect the channel capacity of CR users 124

CHANNEL CAPACITY

Thus, the channel capacity of CR users depends on the interference at the licensed (primary) receivers, i.e., limited by a primary user’s activity.

125

Spectrum Capacity  Spectrum capacity, C, can be estimated as: 

S C  B log( 1  ) NI



SINR (Signal to Interference plus Noise Ratio) The received power is constrained by primary users, which affect the channel capacity

 where B is the bandwidth S is the received signal power from the CR user N is the CR receiver’s noise power I is the interference power received at the CR receiver due to the primary transmitter. 126

Spectrum Characterization Recent work on spectrum analysis  only focuses on spectrum capacity estimation. Other factors such as delay, link error rate, and holding time also have significant influence on the quality of services.

127

Spectrum Characterization Capacity is closely related to both interference+noise level and path loss.

A complete analysis and modeling of spectrum in CR networks is yet to be developed.

128

Decision Procedure  Once all available spectrum bands are characterized, appropriate operating spectrum band should be selected for the current transmission considering the QoS requirements and the spectrum characteristics.

 Thus, the spectrum decision function must be aware of user QoS requirements.  Based on the user requirements, the data rate, acceptable error rate, delay bound, the transmission mode, and the bandwidth of the transmission can be determined.

129

SINGLE SPECTRUM DECISION 

Each CR user selects only one spectrum band according to the application requirements Idle spectrum band

Occupied by primary users

Frequency(Hz)

CR user A CR user A

CR user B Spectrum Handoff

CR user B

130

Problems of Single Spectrum Decision – Because of the operation of primary networks, CR users cannot obtain a reliable communication channel for a long time. – CR users may experience temporary disconnections (latency) during the spectrum handoff.

131

Multi-Spectrum Decision 

CR users select multiple non-contiguous spectrum bands and use them simultaneously for the transmission. Occupied by primary users

Idle spectrum band

Frequency(Hz)

Sub-channels for CR user A

Sub-channels for CR user B CR user A CR user B

Spectrum Handoff

132

Multi-Spectrum Decision  High throughput can be achieved !  Immune to the interference and the primary user activity.

– Transmission in multiple spectrum bands allows lower power to be used in each spectrum band  less interference with primary users is caused - Even if spectrum handoff occurs in one of the current spectrum bands, the rest of the spectrum bands will maintain current transmissions.

 How to determine the number of spectrum bands and how to select the set of appropriate bands are still open research issues. 133

Further Challenges:

Decision Model

 SNR is not sufficient to characterize the spectrum band!  Besides the SNR, many spectrum characterization parameters would affect QoS.  Applications may require different QoS requirements.

 Thus, how to combine these spectrum characterization parameters for the application-adaptive spectrum decision model is still an open issue. 134

Further Challenges:

Cooperation with Reconfiguration  CR technology enables the transmission parameters of a radio to be reconfigured for optimal operation in a certain spectrum band.  For example, if SNR is fixed, BER can be adjusted to maintain the channel capacity by exploiting adaptive modulation techniques.

 Hence, a cooperative framework that considers both spectrum decision and reconfiguration is required. 135

7. SPECTRUM SHARING

136

Spectrum Sharing Transmitted Signal

Spectrum Mobility

Spectrum Sharing

Radio Environment RF Stimuli

Primary User Detection Decision Request

Channel Capacity

Spectrum Sensing

Spectrum (Channel) Characterization

Spectrum Hole

Spectrum Decision

137

Spectrum Sharing Spectrum Sharing  similar to MAC Problems – –

Multiple CR users try to access the spectrum Access must be coordinated (to prevent collisions in overlapping portions of the spectrum)

Uniqueness – Coexistence with licensed (primary) users – Wide range of available spectrum 138

SPECTRUM SHARING CLASSIFICATION

o

Intra-Network SS – Centralized (Infrastruct. based) – Distributed (Ad hoc – based) Cooperative Non-cooperative

Inter-Network SS * Centralized * Distributed

139

Intra-Network Spectrum Sharing

Centralized Spectrum Sharing

140

Intra-Network Spectrum Sharing Spectrum sharing entity

Sending local observations Sending spectrum allocations Spectrum sharing entity

Distributed Spectrum Sharing (Non-Cooperative)

Distributed Spectrum Sharing (Cooperative) 141

Intra-Network Spectrum Sharing  Spectrum sharing inside a CR network  same as MACs  Focuses on “spectrum allocation” between the CR users Coordinates multiple accesses among CR users in order to prevent their collision in overlapping portions of the spectrum

 Also CR users need to access the available spectrum without causing interference to the primary users.

142

Inter-Network Spectrum Sharing Sending Local Observations Sending Spectrum Allocations

Spectrum Broker (or Spectrum Server)

Spectrum Sharing Entity

CR Network B CR Network B CR Network A

CR Network C

CR Network A CR Network C

Centralized Spectrum Sharing

Distributed Spectrum Sharing 143

Inter-Network Spectrum Sharing Multiple systems are deployed in overlapping locations and spectrum bands Spectrum sharing among these systems is an important research topic in CR networks

144

Game Theory Definition – A collection of mathematical models and techniques for the analysis of interactive decision processes – Provides strategic interactions among agents using formalized incentive structure – Enables the choice of optimal behavior when costs and benefits of each option depend upon the choices of other individuals. 145

Why Game Theory? Excellent match in nature to the spectrum sharing in CR networks. [Game Theory] – Provides a well-defined model to describe conflict and cooperation among intelligent rational decision makers 146

Why Game Theory? [Spectrum Sharing in CR networks]

– CR users have a common interest to have the spectrum resources as much as possible. – However, CR users have competing interests to maximize their own share of the spectrum resources. i.e., the activity of one CR user can impact the activities of the others – Also CR user’s rational decisions require anticipating rivals’ responses 147

Why Game Theory? Provides an efficient distributed spectrum sharing scheme. Provides the well-defined equilibrium criteria for the spectrum sharing problem to measure the optimality in various network scenarios.

148

Game Theory: Basic Components  Game: A model of interactive decision process

 Player: A decision making entity  Actions (Strategies): The adaptations available to the player.

 Outcomes (Payoffs) : The outputs determined by the actions and the particular system in which the players are operating  Preference: A decision maker objective (To capture the preference relation in a more compact way; we employ utility functions (payoff functions) where each player assigns a real number to each outcome) 149

Game Theory: Recap The output (outcomes) of the process (game) is the function of the inputs (actions) from several different decision makers (players) who may have potentially conflicting objectives (preferences) with regards to the outcome of the process.

150

Normal Form Games (Strategic Form Games)  Synchronous Single Shot Play: All players make their decisions simultaneously and take only a single decision without knowing the actions of the other  Three Components: – – –

A set of players N Action Space A, A set of utility functions {uj}

such that each player j  N has its own utility function, uj :A → R (R is a set of real numbers)  Specified by 3-tuple Γ = 151

Normal Form Games (Strategic Form Games)  Example: Paper (P) – Rock (R) - Scissors (S) Game – N = {P1, P2} – A = {(P,P), (P,R), (P,S), …, (S,S)} – {uj} = {-1, 0, 1} (-1: loss, 0: tie, 1: win) P2

P

R

S

P

(0,0)

(1,-1)

(-1,1)

R

(-1,1)

(0,0)

(1,-1)

S

(1,-1)

(-1,1)

(0,0)

P1

152

Nash Equilibrium (NE) DEFINITION: A set of actions (strategies) where no player has anything to gain by changing only his/her own strategy unilaterally. NEs correspond to the steady-states of the game and are then predicted as the most probable outcomes of the game. 153

Nash Equilibrium (NE) If each player has chosen a strategy and no player can benefit by changing his/her own strategy while other players keep theirs unchanged, then the current set of strategy choices and the corresponding payoffs constitute a NE.

154

Nash Equilibrium (NE) SIMPLY: You and I are in NE if I make the best decision I can, taking into account your decision, and you make the best decision you can, taking into account my decision. Likewise, many players are in NE if each one is making the best decision he can, taking into account the decisions of the others. 155

Nash Equilibrium Example Games NE

Player 1

Player 2

a2

b2

a1

1,1

-5,5

b1

5,-5

-1,-1 156

How to model CR networks using Game Theory? Player → CR Users (and Primary Users) Action (Strategy) – CR Users:

 Which licensed channels will be used by the players?

 Which transmission parameters (transmission power, time duration) to apply? or  The price they agree to play for leasing certain channels from the primary users 157

How to model CR networks using Game Theory?

Action (Strategy) – PR Users****: (???)

 Which unused spectrum they will lease?  How much they will charge CR users for using their spectrum resources, etc. ?

158

How to model CR networks using Game Theory?

Outcome (Payoff) → Network State (SNR, BW, etc) Utility Functions → Target QoS parameters (Throughput, Delay, BER, Cost, etc.)

159

Example Models Player: Two CR Users Action: Select either a low-power narrowband waveform N, or a higher power wideband waveform W Outcome: Network States (SNR, BW) Utility Function: Throughput Preference: To maximize throughput 160

Example Models Narrowband

Narrowband

Wideband

Wideband

CR Users 1

CR Users 2

Frequency

CR user 1

CR users 2 Narrowband

Wideband

Narrowband

(9.6,9.6)

(3.2, 21)

Wideband

(21,3.2)

(7,7)

Nash Equilibrium (kbps) 161

SPECTRUM SHARING CLASSIFICATION

o

Intra-Network SS – Centralized (Infrastruct. based) – Distributed (Ad hoc – based) Cooperative Non-cooperative

Inter-Network SS * Centralized * Distributed

162

Centralized Spectrum Sharing A centralized node (e.g., CR base station) controls the spectrum allocation and access procedures. Each CR user in the CR network forwards their measurements about the spectrum allocation to the central node which then constructs a spectrum allocation map. 163

Centralized Spectrum Sharing C. Raman, R. D. Yates, and N. B. Mandayam, “Scheduling Variable Rate

Links via a Spectrum Server,” Proc. IEEE DySPAN, pp.110118, Nov.’05.

Spectrum sharing on the unlicensed bands

Spectrum server allocates an optimal schedule for a set of links in CR networks using: – Maximum Sum Rate Scheduling – Max-Min Scheduling – Proportional Fair Scheduling

164

Centralized Spectrum Sharing  Performance Analysis – Maximum sum rate scheduling with no minimum rate constraint: the transmission mode with the highest sum rate is chosen. The links which are not a part of this transmission mode are not operated at all. – Maximum sum rate scheduling with nonzero minimum rate constraint: More than one transmission mode is operated since there is a minimum rate requirement for each link. – Max-min fair solution: all the links end up getting the same rate.

165

SPECTRUM SHARING CLASSIFICATION

o

Intra-Network SS – Centralized (Infrastruct. based) – Distributed (Ad hoc – based) Cooperative Non-cooperative

Inter-Network SS * Centralized * Distributed

166

Intra-Network Spectrum Sharing - Distributed & Cooperative  If infrastructure is not preferred !!  Each CR user is responsible for the spectrum allocation and access is based on local policies.  CR users exchange their information with other neighboring users for spectrum access

167

Intra-Network Spectrum Sharing - Distributed & Cooperative  Cooperative (or collaborative) solutions consider the effect of the CR user’s communication on other users.  I.o.w. the interference measurements of each CR user are shared among other CR users.  Furthermore, the spectrum sharing algorithms also consider this information.

 While all the centralized solutions can be regarded as cooperative, there also exist distributed cooperative solutions.

168

SPECTRUM SHARING CLASSIFICATION

o

Intra-Network SS – Centralized (Infrastruct. based) – Distributed (Ad hoc – based) Cooperative Non-cooperative

Inter-Network SS * Centralized * Distributed

169

Intra-Network Spectrum Sharing - Distributed & Non-Cooperative  If infrastructure is not preferred !!  Each CR user is responsible for the spectrum allocation and access is based on local policies.  CR users depend only on their local observations for spectrum access

170

Intra-Network Spectrum Sharing - Distributed & Non-Cooperative  Non-cooperative (or non-collaborative, selfish) solutions consider only the node itself  Selects the channel with the objective of maximum throughput without taking other users into consideration!  May result in reduced spectrum utilization  Requires minimal communication among other nodes. 171

SPECTRUM SHARING CLASSIFICATION

o

Intra-Network SS – Centralized (Infrastruct. based) – Distributed (Ad hoc – based) Cooperative Non-cooperative

Inter-Network SS * Centralized * Distributed

172

Inter-Network Spectrum Sharing - Centralized

O. Ileri, D. Samardzija, and N. B. Mandayam, “Demand Responsive Pricing and Competitive Spectrum Allocation via Spectrum Server,” in Proc. IEEE DySPAN, pp. 194202, Nov. 2005.

Step 1: User specific information is communicated to the SPS Spectrum Policy Server (SPS)

CR user

Step 2: Iterative bidding process: winner declared

Step 3: User evaluates the offer of the winner

Operator1

Operator2 173

Operator Bidding Scheme A central spectrum policy server (SPS) is proposed to coordinate spectrum demands of multiple CR operators. The operators dynamically compete for customers as well as portions of available spectrum

174

SPECTRUM SHARING CLASSIFICATION

o

Intra-Network SS – Centralized (Infrastruct. based) – Distributed (Ad hoc – based) Cooperative Non-cooperative

Inter-Network SS * Centralized * Distributed

175

Classification of Spectrum Sharing based on Spectrum Access Techniques Primary user

Frequency

Overlay Spectrum Sharing

o

CR user

Frequency

Underlay Spectrum Sharing

176

Overlay Spectrum Sharing  A CR user accesses the primary network using a portion of the spectrum that has not been occupied by licensed users.

 As a result, interference to the primary system is minimized.

177

Underlay Spectrum Sharing  Underlay spectrum sharing exploits the spread spectrum techniques developed for cellular networks  Once a spectrum allocation map has been acquired, a CR user begins transmission such that its transmit power at a certain portion of the spectrum is regarded as noise by the primary users. (Interference temperature idea)

 Requires sophisticated spread spectrum techniques and can utilize increased bandwidth compared to overlay techniques. 178

Comparison of Underlay and Overlay Approaches R. Menon, R. M. Buehrer, J. H. Reed, “Based Comparison of Underlay and Overlay Spectrum Sharing Techniques Outage Probability,” in Proc. IEEE DySPAN, pp. 101109, Nov. 2005.

Based on the influence of the CR network on the primary network in terms of outage probability (probability that the primary network will experience interference from the CR network)  three spectrum sharing techniques have been considered.

179

Comparison of Underlay and Overlay Approaches

METHOD 1: Spreading Based Underlay requires CR users to spread their transmit power over the full spectrum such as CDMA or UWB.

180

Comparison of Underlay and Overlay Approaches

 METHOD 2: Interference Avoidance Overlay requires CR users to choose a frequency band to transmit such that the interference at a primary user is minimized.

181

Comparison of Underlay and Overlay Approaches

 METHOD 3: Hybrid Technique (Spreading based Underlay with Interference Avoidance) A CR user spreads its transmission over the entire spectrum and also null or notch frequencies where a primary user is transmitting.

182

Comparison of Underlay and Overlay Approaches

Perfect system knowledge – Overlay scheme outperforms the underlay scheme in terms of outage probability. – Underlay scheme with interference avoidance guarantees smaller outage probability than the pure interference avoidance.

183

Comparison of Underlay and Overlay Approaches  Limited System Knowledge (more realistic)

– The overlay schemes result in poor performance due imperfections at spectrum sensing. – Underlay with interference avoidance  the interference caused to the primary user is minimized. – Another important result is that a higher number of CR users can be accommodated by the hybrid scheme than the pure interference avoidance scheme. 184