Cooperative spectrum sensing technique is used to maximize the utilization of unused licensed spectrum. As the cooperation among the secondary users increases the detection performance increases, which increases the average channel throughput and energy efficiency but it depends on the number of cooperative secondary users, fusion rules, channel conditions and detection threshold. In this thesis average channel throughput, energy consumption and energy efficiency are estimated for variable number of secondary users and detection thresholds using hard fusion rules i.e. AND, OR and MAJORITY fusion rules. From the results it has been observed that the performance of AND fusion rule is better at low detection thresholds and for less number of secondary users. The performance of OR fusion rule is better at high detection thresholds and for large number of secondary users. The performance of MAJORITY fusion rule follows the performance of AND fusion rule at low detection thresholds and it follows the performance of OR fusion rule at high detection thresholds.
However as the number of cooperative secondary users increases the energy required for spectrum sensing and reporting sensing results to the fusion center increases, which increases the energy consumption and reduces the energy efficiency. Therefore energy efficiency can be improved by maximizing the average channel throughput or by minimizing the energy consumption. To minimize the energy consumption in cooperative spectrum sensing, optimization technique has been proposed in this thesis and it is used for further improvement of energy efficiency. With this optimization technique, optimal number of cooperative secondary users are derived by maximizing the energy efficiency using AND and OR fusion rules but not with MAJORITY fusion rule. Because it is very difficult to estimate the optimal number of cooperative secondary users using MAJORITY fusion rule, so optimization of final decision threshold was proposed in the existing methods to maximize the energy efficiency using MAJORITY fusion rule. Therefore AND and OR fusion rules are used in this work to optimize the number of cooperative secondary users.
Table of Contents
1 INTRODUCTION
1.1 Characteristics of Cognitive Radio
1.1.1 Cognitive Capability
1.1.2 Reconfigurability
1.2 Architecture of Cognitive Radio Network
1.2.1 Primary Network
1.2.2 Cognitive Radio Network
1.3 Cognitive Cycle
1.3.1 Spectrum Sensing
1.3.2 Spectrum Decision
1.3.3 Spectrum Sharing
1.3.4 Spectrum Mobility
1.4 Classification of Spectrum Sensing Techniques
1.4.1 Primary Transmitter Detection
1.4.2 Receiver Detection
1.4.3 Interference Temperature Management
1.5 Evaluation Metrics
1.6 Conventional versus Cooperative Spectrum Sensing
1.7 Cooperative Spectrum Sensing
1.7.1 Centralized Cooperative Spectrum Sensing
1.7.2 Distributed Cooperative Spectrum Sensing
1.7.3 Relay Assisted Cooperative Spectrum Sensing
1.8 Elements of Cooperative Spectrum Sensing
1.8.1 Cooperation Models
1.8.2 Sensing Techniques
1.8.3 Hypothesis Testing
1.8.4 Control Channel and Reporting
1.8.5 Data Fusion
1.8.6 User Selection
1.8.7 Knowledge Base
1.9 Framework of Cooperative Spectrum Sensing
1.10 Research Objectives
1.10.1 General Objectives
1.10.2 Specific Objectives
2 REVIEW OF LITERATURE
2.1 Background
2.2 Review of Cognitive Radio Networks
2.3 Review of Cooperative Spectrum Sensing
2.4 Review of Energy Efficiency in Cooperative Spectrum Sensing
2.5 Review of Optimization in Cooperative Spectrum Sensing
2.6 Review of Cooperative Spectrum Sensing Under Fading Channels
2.7 Research Gap
2.4 Summary of Literature Review
3 OPTIMIZATION OF DECISION THRESHOLD IN COOPERATIVE SPECTRUM SENISNG
3.1 Introduction
3.2 System Model
3.3 Analysis of Energy Efficiency
3.4 Optimization of Final Decision Threshold
3.5 Conclusion
4 ENERGY EFFICIENCY IN COGNITIVE RADIO NETWORKS USING COOPERATIVE SPECTRUM SENSING
4.1 Introduction
4.2 System Model
4.3 Average Channel Throughput of OR, AND and MAJORITY Fusion Rules
4.4 Energy Consumption of OR, AND and MAJORITY Fusion Rules
4.5 Energy Efficiency of OR, AND and MAJORITY Fusion Rules
4.6 Conclusion
5 OPTIMIZATION OF COOPERATIVE SECONDARY USERS IN COGNITIVE RADIO NETWORKS
5.1 Introduction
5.2 Optimization of Cooperative Secondary Users using OR, AND Fusion Rules
5.2.1 Optimal Number of Cooperative Secondary Users using OR Fusion Rule
5.2.2 Optimal Number of Cooperative Secondary Users using AND Fusion Rule
5.3 Performance of OR, AND Fusion Rules
5.4 Conclusion
6 PERFORMANCE OF COOPERATIVE SPECTRUM SENSING OVER RAYLEIGH FADING CHANNELS
6.1 Introduction
6.2 Probability of Detection and Probability of False Alarm in Cooperative Spectrum Sensing
6.3 Total Error Rate
6.4 Success Probability
6.5 Conclusion
7 CONCLUSION AND FUTURE SCOPE
Research Objectives and Thematic Focus
This work aims to enhance the performance and energy efficiency of cooperative spectrum sensing in cognitive radio networks by optimizing key parameters such as decision thresholds and the number of participating secondary users. The research investigates the trade-offs between sensing performance, energy consumption, and channel throughput under various fading and non-fading channel conditions using different fusion rules.
- Optimization of decision thresholds to maximize energy efficiency.
- Evaluation of AND, OR, and MAJORITY fusion rules in cooperative spectrum sensing.
- Development of techniques to determine the optimal number of secondary users for specific channel conditions.
- Performance analysis of cooperative spectrum sensing over AWGN and Rayleigh fading channels.
- Investigation into the impact of imperfect reporting channels on system success probability.
Excerpt from the Book
Energy Detection
If the secondary user does not have prior information of the primary user, then matched filter method is not a preferred solution for identifying the primary user. Therefore energy detection method is considered as a suitable solution in which the primary user is detected by a secondary user based on the sensed energy. The block diagram of the Energy Detector is shown in the Figure 1.6.
In this method, the received signal is transmitted through a band-pass filter with a bandwidth of W. It will allow signals of bandwidth W and limits the noise. The output of the band-pass filter is transmitted through a square law device which is used to improve the received signal strength. Each bit is integrated within the time interval of one bit by an integrator circuit and is compared with a predetermined threshold and the final decision i.e. presence or absence of the PU is given by the detection threshold. The threshold value will vary according to the channel conditions.
Some of the disadvantages of Energy Detection method are
1. Not able to differentiate signal and noise power because the primary user’s information is unknown to the secondary user.
Summary of Chapters
1 INTRODUCTION: Outlines the fundamental concepts of cognitive radio, spectrum sensing architectures, and the research objectives focused on improving detection accuracy and spectrum utilization.
2 REVIEW OF LITERATURE: Surveys existing research on cooperative spectrum sensing, energy efficiency, and optimization techniques, identifying key research gaps to be addressed.
3 OPTIMIZATION OF DECISION THRESHOLD IN COOPERATIVE SPECTRUM SENISNG: Proposes an optimization technique for the decision threshold at the fusion center to maximize the system's energy efficiency.
4 ENERGY EFFICIENCY IN COGNITIVE RADIO NETWORKS USING COOPERATIVE SPECTRUM SENSING: Analyzes channel throughput, energy consumption, and overall energy efficiency using various hard fusion rules.
5 OPTIMIZATION OF COOPERATIVE SECONDARY USERS IN COGNITIVE RADIO NETWORKS: Develops methods to determine the optimal number of cooperative secondary users, balancing sensing performance against energy requirements.
6 PERFORMANCE OF COOPERATIVE SPECTRUM SENSING OVER RAYLEIGH FADING CHANNELS: Evaluates system performance in challenging fading environments, focusing on error rates and success probability with imperfect reporting channels.
7 CONCLUSION AND FUTURE SCOPE: Summarizes the thesis findings and suggests potential future research directions, including multi-primary user scenarios and security enhancements.
Keywords
Cognitive Radio, Cooperative Spectrum Sensing, Energy Efficiency, Data Fusion, Decision Threshold, Optimization, Secondary Users, AWGN, Rayleigh Fading, Throughput, Primary User, Spectrum Sensing, Channel Utilization, Signal-to-Noise Ratio
Frequently Asked Questions
What is the core focus of this research?
The research focuses on enhancing the energy efficiency and detection performance of cognitive radio networks through cooperative spectrum sensing techniques.
What are the primary thematic areas covered in the thesis?
Key areas include spectrum sensing techniques, data fusion rules (AND, OR, MAJORITY), energy consumption analysis, and optimization of network parameters.
What is the ultimate goal of the proposed work?
The primary goal is to maximize the energy efficiency of cooperative spectrum sensing while maintaining a high probability of detection in various channel conditions.
Which scientific methods are primarily utilized?
The thesis utilizes simulation-based approaches, mathematical modeling, and optimization techniques (such as bisection algorithms and exhaustive search) to determine optimal system parameters.
What specific topics are explored in the main body?
The main body examines the impact of decision thresholds on energy efficiency, the performance of hard fusion rules, and the optimization of secondary user participation.
What are the characterizing keywords for this study?
Core keywords include Cognitive Radio, Cooperative Spectrum Sensing, Energy Efficiency, Data Fusion, and Fading Channels.
How does the MAJORITY fusion rule behave according to this study?
The study observes that the MAJORITY fusion rule acts similar to the AND fusion rule at low detection thresholds and shifts to behave like the OR fusion rule at high detection thresholds.
What effect does increasing the number of secondary users have on the system?
While increased cooperation can improve detection, it also increases energy consumption, leading to a point where overall energy efficiency may decline if too many users are added.
- Citation du texte
- Chilakala Sudhamani (Auteur), 2020, Performance of Cooperative Spectrum Sensing in Cognitive Radio Networks, Munich, GRIN Verlag, https://www.grin.com/document/901617
