Cognitive Radio Networks (CRN) Research Topics is one of the important topics and it is widely used in many applications. In this the multiple users or devices share the possible spectrum. In this we provide information or detail related to the proposed research.

1. Define Multiuser based on CRN

At the beginning of the research we first look over the definition of multi user CRN. CRN is a wireless communication system which intellectually uses possible sources of spectrum. In a multi user CRN framework, multiple devices or users actively share and obtain the possible spectrum, to reduce spectral efficacy by adjusting their communication parameters. This combined and flexible technique allows effective use of the spectrum by considering the different communication requirements of multiple users over the network.

2. What is Multiuser based on CRN?

Afterwards the definition, we overviewed the deep interpretation for our proposed research. In the system of CRN a multiuser situation that contains multiple devices or users sequentially obtaining and using the accessible spectrum. In a multiuser CRN, the knowledgeable methods and procedures follow active acquisition of spectrum, permitting the users to adjust their communication metrics in actual-time to decrease the efficacy of spectrum. This combined approach improves spectrum usage by considering the variety of communication needs of multiple users over the network.

3. Where Multiuser based on CRN used?

Thereafter we converse where to employ the multiuser CRN technology. Our proposed technology is used in places like Smart Cities, Internet of Things (IoT), Wireless Networks, Ad Hoc Networks, Public Safety Communications and Satellite Communications.

4. Why Multiuser based on CRN technology proposed? , Previous technology issues

Here the Multiuser CRN technology is proposed in this work and the purpose of this research is to enhance the multi-band multi-user by increasing the transmitting power significant problem in CRN. The purpose of this research is to enhance the transmitting power and whole sum rate to decrease multiband, multi-user CRN. To encourage spectrum utilization efficiency and data throughput and the power transmission abilities of the network, the research grants a distinct hybrid spectrum transfer method.

5. Algorithms / Protocols

For this research a multiuser CRN technique is proposed to overcome some existing technology issues. The methods that we proposed for this research are Game Theory, Stochastic Optimization, Bellman – Ford Dingo Optimization Algorithm (BFDOA) and K-hop cluster-based joint optimization approach.

6. Comparative study / Analysis

In this research we compare various methods to analyze the best method. The proposed technique methods that we compared are as follows.

• For energy usage we utilize Hybrid K-hop cluster-based joint Optimisation Strategy and this creative technique essentially decreases scalability and energy consumption when ensuring the effective use of the possible spectrum, creating a possible choice for the resource and active scalability and sustainable operation of CRNs.
• Stochastic Optimisation methods are important for this technique, to manage the essential unpredictability of wireless communication systems.
• For the purpose of simulating and interpreting the strategic communication among users challenging for spectrum resources and the game theory provides a strong model.
• BDFOA is utilized to enhance the route choosing procedure after decreasing the interference and describe the ideal course of action.

7. Simulation Results / Parameters

Our proposed research performance metrics can be compared with some existing technology to obtain the best outcome for this research. The metrics that we compared are Routing Overhead, Average Network Lifetime, Total Transmission Power, Energy Consumption, Throughput, Number of alive nodes and Packet Delivery Ratio.

8. Dataset LINKS / Important URL

We provide some important links that are useful when we have to interpret the concept or details about our proposed research on the basis of multiuser CRN.

• https://ieeexplore.ieee.org/abstract/document/9982407
• file:///C:/Users/i5-4G-PC2/Downloads/computers-12-00158%20.pdf
• https://ieeexplore.ieee.org/abstract/document/9845681

9. Multiuser based on CRN Applications

The application that employs our proposed technique is a multiuser CRN as follows.  Public safety and Emergency Communications, Satellite Communications, Wireless Communications Networks, Ad Hoc Networks, Cognitive Radio-based Cognitive Radio Networks, Wireless Sensor Networks and Internet of things (IoT).

10. Topology for Multiuser based on CRN

Now we see the topology to be used for this research. The topologies that we used are Cluster-based Topology, Centralized Topology, Mesh Topology, Ad Hoc Topology, Decentralized Topology and Hybrid Topology

11. Environment in Multiuser based on CRN

Let’s discuss the environment to be utilized for our proposed research. The environment that we used is Dynamic Channel Conditions, Spectrum Availability, Geographical Characteristics, User Mobility, Interference Levels, Energy Availability, Network Density, Security Threats and Regulatory Constraints.

12. Simulation Tools

The software requirements that needed for this research are as follows. The developmental tool that is used for this research is NS 3.26 or Above Version. Then the programming languages here we utilized for this research are C++ and Python. The operating system utilized to implement this research is Ubuntu 16.06 [LTS] or Above Version.

13. Results

In this the proposed research is compared with several methods and then the performance metrics or the parameters are compared to obtain the best findings. The multiuser CRN technique is a wireless communication system that uses the possible spectrum sources. This can be implemented by utilizing the operating system Ubuntu 16.06 [LTS] or above version.

Cognitive Radio Network Research Ideas

The following are the multiuser CRN based research topics that are utilized for any queries or doubts related to this research.

1. A Study Of Dynamic Thresholds Power Detection Spectrum Sensing Techniques In CRN
2. A Hybrid Architecture Based on Conformer and CRN Parallelism for Regulated Speech Quality Measurement Model
3. Blockchain Based Spectrum Mapping and Access to Secondary Users for Enhanced Channel Security Efficiency in CRN
4. Pixel-CRN: A New Machine Learning Approach for Convective Storm Nowcasting
5. Reconfigurable Intelligent Surfaces-assisted Overlay Energy Harvesting-CRN under Resilient Primary User Outages
6. Secrecy Analysis of Underlay CRN in the Presence of Correlated and Imperfect Channel
7. Spectrum-Efficient User and Qos-Aware Resource Allocation With Enhanced Uplink Transmission in U-LTE Networks Co-Occurrence With Wi-Fi by CRN
8. On Performance of a SWIPT Enabled FD CRN With HIs and Imperfect SIC Over α–μ Fading Channel
9. Multi-Objective Spectrum Allocation Scheme for Multi-User mmWave-assisted CRN-5G Networks
10. Throughput maximization of EH-CRN-NOMA based on PPO
11. Energy-Efficient Resource Allocation in Multiple UAVs-Assisted Energy Harvesting-Powered Two-Hop Cognitive Radio Network
12. Spectral-Temporal Model for Opportunistic Spectrum Access in Cognitive Radio Networks
13. DDPG-Based Joint Time and Energy Management in Ambient Backscatter-Assisted Hybrid Underlay CRNs
14. Resnet Associated Cross-Layered Routing in Cognitive Radio Network
15. Trust-based Energy Aware Routing Protocol to Improve Network Lifetime in CRNs
16. Joint Sensing and Transmission Optimization for IRS-Assisted Cognitive Radio Networks
17. Multiuser NOMA With Multiple Reconfigurable Intelligent Surfaces for Backscatter Communication in a Symbiotic Cognitive Radio Network
18. Secrecy Rate Maximization for Multicarrier-Based Cognitive Radio Networks With an Energy Harvesting Jammer
19. A Reliable Spectrum Sensing Method Based on Deep Learning for Primary User Emulation Attack Detection in Cognitive Radio Network
20. Performance of Energy Harvesting Cooperative Cognitive Radio Network Under Higher Order QAM Schemes
21. Elite Oppositional Hunger Games Search Optimization Based Cooperative Spectrum Sensing Scheme for 6G Cognitive Radio Networks
22. Impacts of Sensing Energy and Data Availability on Throughput of Energy Harvesting Cognitive Radio Networks
23. Robust Beamforming for RIS Enhanced Transmissions in Cognitive Radio Networks
24. Frequency Selective Hybrid Beamforming and Optimal Power Loading for Multiuser Millimeter Wave Cognitive Radio Networks
25. Securing Communications for IRSs-Assisted mmWave Cognitive Radio Networks
26. Energy Consumption for Cognitive Radio Network Enabled Multi-Access Edge Computing
27. Prediction of NOx emissions and pathways in premixed ammonia-hydrogen-air combustion using CFD-CRN methodology
28. SAT-496 – Evaluation of the performance of a novel single-nuclei digital pathology method for the continuous quantification of steatosis and inflammation in liver biopsies and its correlation with NASH-CRN scores in patients with NASH
29. 334 hepatic reticuloendothelial system cell iron deposition is independently associated with advanced fibrosis in nash: analysis of 2833 patients from the nash-crn
30. Dynamic resource allocation in IRS-assisted UAV wideband cognitive radio networks: A DDQN-TD3 approach
31. Multi-objective distributed cooperative spectrum sensing for cognitive radio networks using greedy-based coalitional game
32. User fairness-enhanced beamforming for IRS-assisted cognitive radio networks based on prior judgment mechanism
33. Multi-objective optimization for energy efficient cooperative communication in energy-constrained overlay Cognitive Radio Networks
34. Robust transmission for multi-user OFDM-based IRS-assisted cognitive radio networks
35. LSTM-enabled prediction-based channel switching scheduling for multi-channel cognitive radio networks
36. Dynamic channel estimation-aware routing protocol in mobile cognitive radio networks for smart IIoT applications
37. Throughput maximization for downlink DF MIMO relay based SWIPT cognitive radio networks
38. Efficient distributed broadcasting algorithms for cognitive radio networks-enabled smart agriculture
39. CEAR: A cooperation based energy aware reward scheme for next generation green cognitive radio networks
40. A trade-off strategy and correlation analysis for secrecy rate and power consumption in IRS-assisted cognitive radio networks
41. One-bit spectrum sensing using Gustafson–Kessel fuzzy clustering for cognitive radio network
42. Joint spectrum sensing and D2D communications in Cognitive Radio Networks using clustering and deep learning strategies under SSDF attacks
43. Blockchain based smart contract for cooperative spectrum sensing in cognitive radio networks for sustainable beyond 5G wireless communication
44. Blockchain based smart contract for cooperative spectrum sensing in cognitive radio networks for sustainable beyond 5G wireless communication
45. A novel method for spectrum sensing in cognitive radio networks using fractional GWOsingle bondCS optimization
46. Distributed dynamic spectrum access through multi-agent deep recurrent Q-learning in cognitive radio network
47. Deep Q-learning multiple networks based dynamic spectrum access with energy harvesting for green cognitive radio network
48. Optimized Resource Management over Connected Vehicles in RF-CRN Environment
49. MIMO-NOMA oriented CRN Physical Layer Security on Imperfect CSI using Power Optimization and Beamforming Methods
50. Performance Analysis of Wideband Spectrum Sensing (WSS) in Cognitive Radio Networks (CRN) over Erroneous Sensing and Reporting Channels