CASE: Channel Allocation for optimized Spectral Efficiency using deep neural network in underlay cognitive radios
- Resource Type
- Conference
- Authors
- Gupta, Karan; Dhurandher, Sanjay Kumar
- Source
- 2023 International Conference on Computer, Information and Telecommunication Systems (CITS) Computer, Information and Telecommunication Systems (CITS), 2023 International Conference on. :1-6 Jul, 2023
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
General Topics for Engineers
Robotics and Control Systems
Signal Processing and Analysis
Computer aided software engineering
Spectral efficiency
Computational modeling
Artificial neural networks
Minimization
Dynamic scheduling
Computational efficiency
Cognitive radio networks
Channel Allocation
Computation time
Neural Network
- Language
Channel allocation is a critical aspect to be addressed in underlay cognitive radios, especially when the upcoming 5G communications are based on the concept of cognitive radio. To ensure an efficient spectrum allocation, the paper presents an efficient channel allocation for optimizing the spectral efficiency using deep neural network. The proposed scheme named as CASE intends to evaluate the efficiency by considering the maximization of efficient spectrum allocation and minimizing computation time in an underlay cognitive radio network (CRN). The CASE system model provides an overall improvement in the spectrum access by 98.47%, 95% and 85% in terms of computation time compared to the existing IRAWCS technique and random scheme.