Cognitive Radio Final Year Project

Cognitive radio network (CRN) is a promising mechanism that is launched to change the future of upcoming wireless networks by assuring effectual dynamic spectrum utilization. These cognitive radios sense the real-world environment to analyze the spectrum information like availability. Then it adapts appropriate channel access and transmission techniques with efficient routing protocols for enhanced performance. This page is about the thought-provoking Cognitive Radio Final Year Project Topics with current research areas!!!

           Now, we can see the unique functionalities of the cognitive radios compared to other standard radios in the network. Her, we have classified the radios into 3 forms as cognitive, software, and conventional/typical radios. Let’s have a look over them,

How is Cognitive Radio different from Other Radios?

Cognitive Radio

  • Easy to modify the processes for satisfying QoS requirements
  • Support software-defined radios (SDR) with artificial intelligence (AI)
  • Facility to make custom based waveforms and eliminate new interface

Software Radio

  • Support interface for varied models
  • Offer multi-services with variable quality of service
  • Allow any number of different protocols, interfaces, and models

Typical Radio

  • Enable multi-services only at design mode
  • Include the finite number of nodes/models
  • Possible to re-configure while system design 

Cognitive module includes the High layer (PDCP / RLC) and Mac layer. Similarly, the self-configuration module includes the RRC layer. Further, the Physical layer is common to both the cognitive module and self-configuration module. When the layers perform their operation, then it is connected to the cognitive engine which uses learning approaches for the database.

What are the modules in CRN? 

  CRN mainly consists of two modules as Cognitive Module and Self-Configuration Module and each module contains separate network stack layers as follows, 

  • RRC Layer – Analyze the spectrum mobility and allocate the spectrum for equal sharing without interference
  • MAC Layer – Collision avoidance and probability checking using MAC statistics 
  • High Layer (PDCP / RLC) – Assess the traffic in terms of quality of service metrics 
  • PHY Layer – Sense the gaps in the spectrum i.e., unused spectrum, and configure the spectrum using an antenna, power, AMC, and RB

Now, we can see some factors that inspire the creation of several notable Cognitive Radio Final Year Project ideas for students/scholars. These blow-specified points are not effective in the current research. So, all these are looking for a better solution effectively.

Top 15+ Interesting Cognitive Radio Network Final Year Project

Motivations for CRN

  • Presence of massive unused spectrum
  • Involvement of multiple wireless services
  • Lack of spectrum 
  • Scalable cognitive radio spectrum access
  • Improper distribution of static spectrum 

Next, we can see other important and common issues that are not solved yet or not properly recognized by the students/scholars in the field of cognitive radio networks. So, these areas give add-on hope to the CRN research.

Traditional Challenges of Cognitive Radio

  • Optimization in energy utilization
  • Co-channel interference for control messages
  • Detection of termination in CRN
  • Identification of common control channel 
  • Difficult to achieve cooperation of PUs and SUs 
  • End-to-End throughput and delay analysis
  • Tough to assure link trustworthiness and security

For your information, here our resource team has given you how we perform the Cognitive Radio Final Year Project with our objectives. All these objectives are achieved to get the fine-tuned CRN research and projects which are unique from others.

How do we work on CRN final year projects? 

  • At first, we will collect the widespread CRN research gaps to find current research opportunities. 
  • Then, we spot out the important and high-demanding research unresolved problems that waiting to solve soon for constructing enhanced CRN. 
  • Next, we describe the suitable development infrastructure to implement the proposed methodologies. 
  • Afterward, we propose to show how the study will attain the vision through the agenda
  • At last, state the implication of CRN in terms of research and conceptual theory 

Further, we have given you a few different cognitive radio access models in CRN. In your CRN research, your project is based on any of the following models. And they are interwave access, overlay access, and underlay access. Let’s have a glance over them in detail,

Cognitive Radio (CR) Access Paradigms

  • Interweave Access: In this, if there is no PUs then it let SU transmit up to its extreme power. Also, it is popularly referred to as the traditional cognitive radio network.
  • Overlay Access: In this, both PU and SU will access the same channel at the same time for data transmission but SU will not go beyond the maximum power. Also, SU uses more PUs as a relay for passing the data over the channel. As a result, mutual understanding and cooperation between PUs and SUs. 
  • Underlay Access: In this, both PU and SU will access the same channel at the same time for data transmission. But the SU assure that it will exceed the transmit power limit and will not cause interference to PU.

Now, we can see that the significant wireless technologies that are holding their hands with the new developing cognitive radio networks field. These technologies play a major role in developing every Cognitive Radio Final Year Project.

CRN Wireless Technologies

  • Deployment scenarios
    • Picocell – Office or Indoor Hotspot
    • Femtocell – Office or In-home
    • Wi-Fi – Hot Spot and In-home
    • Relay – High-speed railway (HSR), Office, Tunnel and Hotspot
    • Distributed Antenna System (DAS) – Indoor extension
  • Coverage range
    • Picocell – 150m
    • Femtocell – ranges from 20 to 50m 
    • Wi-Fi – between 100 and 200 m
    • Relay – Macro capacity extension  
    • Distributed Antenna System (DAS) – Macro capacity extension 
  • Backhaul
    • Picocell – X2 interface
    • Femtocell – Cable, Optical Fiber and Digital Subscriber Line (DSL) 
    • Wi-Fi – Cable, Optical Fiber and Digital Subscriber Line (DSL) 
    • Relay – Wireless out-band or in-band Spectrum
    • Distributed Antenna System (DAS) – RF connections to Macrocell / Optical Fiber
  • Services
    • Picocell – Real-World data (voice)
    • Femtocell – Real-World data (voice)
    • Wi-Fi – Primarily VoIP and Data 
    • Relay – Real-World data (voice)
    • Distributed Antenna System (DAS) – Real-World data (voice)
  • Peak data rate 
    • WiFi – 600 Mb/s (dual-band 802.11N)
    • Femtocell – LTE-Advanced (3GPP R10): 300M b/s (UpLink) and 1Gb/s (DownLink) 
  • Typical power
    • Picocell – Indoor: <100mW and Outdoor: 250Mw to 2W
    • Femtocell – ranges from 10 to 100mW
    • Wi-Fi – between 100 and 200 mW
    • Relay – Indoor:<100 mW and Outdoor 250mW to 2mW
    • Distributed Antenna System (DAS) – NIL
  • Access mode
    • Picocell – Open Access
    • Femtocell – Open or Closed or Hybrid
    • Wi-Fi – Open or Closed access
    • Relay – Open Access
    • Distributed Antenna System (DAS) – Open Access

So far, we have discussed the cognitive radio nature, modules, motivations, challenges, objectives, models, and supporting wireless technologies. Now, we can see the significant research areas of CRN for best project ideas.

Important Project Areas in CRN 

  • Optimized Spectrum Sensing
  • Interference-Resistant Sensing
  • Cooperative Multi-Channel Sensing
  • Internet of Things (IoT)
  • Industrial Internet of Things
  • 5G and 5G Beyond Technologies
  • Adaptive Half and Full-duplex Communication
  • CR Wireless Sensor Network (CR-WSN)
  • Spectrum Decision using Deep and Machine Learning

In specific, we have highlighted the top-demanding research areas that grab the attention of the current research scholars and final year students for their study. Moreover, these areas have long-lasting future research scope too.

Key Areas in CRN 

  • 5G and Beyond 5G Technologies in CRN Applications 
  • Developments of Spectrum Sensing as a Service in WSN/IoT 
  • Future Cognitive Radio Technologies Trends and Challenges 
  • Dynamic Spectrum Sharing in Wireless Sensor Communication 

Next for current final year students’ benefits, our research team has given some interesting cognitive radio project notions. We support not only these ideas, but also other ideas that are waiting to create the best contribution to the research world.

Top 15 Research Ideas for Cognitive Radio Final Year Project

  • Power Control and Management
  • Machine Learning-based Spectrum Sharing 
  • TDM multiplexing in Cognitive Radio
  • Improved Communication Technologies in Cognitive Radio
  • Cognitive Radio Security, Testbeds, and Standards
  • Spectrum Mobility and QoS management Techniques
  • Adaptive Modulation Coding for QoS Improvement
  • Cross-layer System Design for Spectrum Sensing
  • Digital Signal Processing in CRN
  • Game Theory-based Dynamic Spectrum Access and Allocation
  • OFDM sub-channelization Performance Evaluation
  • Spectrum Sensing Measurements and Performance Estimation
  • Channel Aggregation and Bonding in CRN
  • Compressive Spectrum Sensing and Provisioning
  • Physical Layer and MAC Protocol Design for CRN
  • Adaptive Frequency Tuning Techniques (RF hopping, band switching, and Hopping)
  • Intelligent Cognitive radio in Artificial Intelligence and Mobile Networks
  • Distributed Space-Time Block coding (STBC) and Beam-forming (BF) Techniques for MIMO Communication

For illustration purposes, here we have taken the automated modulation classification process as a sample. And, it represents how the cognitive radios perform the classification using a convolutional neural network (CNN) algorithm. Along with this, we also listed the various statistical characteristics that are focused on in CRN development.

Convolutional Neural Network for Automatic Modulation Classification


  • Do Passland sampling in wideband sensing
  • Analyze using the Spectral Correlation method or Extract the statistical feature
  • In CNN, Pass on to the Convolutional Layer and Fully Connected Layer 
  • Perform Classification based on Modulation Type
  • Classified into Noise, Primary and Secondary systems 
  • And proceed with the policy of system coexistence 

Statistical Features Considered 

  • Signal magnitude mean
  • Instantaneous phase deviation
  • Normalized signal deviation (amplitude)
  • Nonlinear component absolute deviation (instantaneous phase)
  • Normalization of power spectral density and signal samples
  • Absolute deviation – the signal’s normalized instantaneous (amplitude) 
  • The signal power ratio between a quadrature and in-phase components 
  • The ratio of peak-to-RMS and peak-to-average 
  • Normalized root mean square (RMS) and amplitude of signal samples 
  • Absolute deviation – the signal segment’s normalized centered instantaneous (frequency)

Future Challenges in CRN 

The cognitive radio works under the principle of dynamic spectrum allocation through advanced communication techniques. These techniques ensure to improve the spectrum sensing and accessing operations and create a positive impact in CRN. As a result, wireless network technologies are growing fast in several different aspects as follows,

  • Intelligent System Process and Control 
  • For instance: self-organizing network (SON) solutions 
  • New-fangled Concepts and Technologies 
  • For instance: IRS and Cell-free systems 
  • Automated Multi-Region Infrastructure Deployment 
  • For instance: Deploying Huge-Scale Small cells 
  • Spatial-Temporal Dimension Spectrum Sensing 
  • Effective Media Access Control Strategies for IoT 
  • Prevention of Co-Channel Interference in Spectrum Sensing 
  • Protocol and Information Exchange of Spectrum Sensing in WSN 
  • Advanced and Cooperative Intelligent Sensing in Cognitive Radio 
  • Role and Impact of Intelligent Reflecting Surfaces (IRS) 
  • Multi-Protocol Switching in different Cognitive Radio 

Generally speaking, if you are interested to hold your hand with our experts for the best service, then communicate with us. We will support you in each step of your research Cognitive Radio final Year Project and development phases.