Data Importance Aware Radio Resource Allocation: Wireless Communication Helps Machine Learning
Objective
The primary objective of the "Data Importance Aware Radio Resource Allocation: Wireless Communication Helps Machine Learning" project is to develop and implement an intelligent and adaptive radio resource allocation framework for wireless communication systems that leverages machine learning techniques. This framework aims to optimize the allocation of scarce radio resources, such as bandwidth and power, in wireless networks while considering the specific data requirements and importance of various applications and services.
Abstract
Edge AI, a branch of artificial intelligence (AI) that blends machine learning and wireless communication, is a sort of AI that is driven by wireless networks with edge computing capabilities and plentiful mobile data. All communication data bits are valuable, but some machine learning data bits are more important than others.
We can therefore allocate more radio resources to the more significant data and less radio resources to the less significant data in order to make the best use of the few radio resources. How to define "more or less important" data in this situation is the main conundrum. In this article, we suggest two key criteria to identify the value of data based on their impacts on machine learning, one for centralized edge machine learning and the other for distributed edge machine learning.
Then, relevant radio resource allocation approaches are given in order to improve the performance of machine learning. Extensive testing are conducted to determine the effectiveness of the proposed data-importance aware radio resource allocation approaches.
Keywords: Data Importance, Edge AI, Machine Learning, Radio Resource Allocation.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
Software: Matlab 2020a or above
Hardware:
Operating Systems:
- Windows 10
- Windows 7 Service Pack 1
- Windows Server 2019
- Windows Server 2016
Processors:
Minimum: Any Intel or AMD x86-64 processor
Recommended: Any Intel or AMD x86-64 processor with four logical cores and AVX2 instruction set support
Disk:
Minimum: 2.9 GB of HDD space for MATLAB only, 5-8 GB for a typical installation
Recommended: An SSD is recommended A full installation of all MathWorks products may take up to 29 GB of disk space
RAM:
Minimum: 4 GB
Recommended: 8 GB
Learning Outcomes
· Introduction to Matlab
· What is EISPACK & LINPACK
· How to start with MATLAB
· About Matlab language
· Matlab coding skills
· About tools & libraries
· Application Program Interface in Matlab
· About Matlab desktop
· How to use Matlab editor to create M-Files
· Features of Matlab
· Basics on Matlab
· What is Communication?
· About Communication
· Introduction to Communication
· How Communication Works?
· Importing the System Design, Characterization and Visualization
· Analyzing of BER tool
· Analyzing of Error Rate Test Console
· Generation of WSN
· WSN network creation
· Nodes Communication
· Clustering
· Routing
· Convolutional
· Equalization and Synchronization etc.,
· How to extend our work to another real time applications
· Project development Skills
o Problem analyzing skills
o Problem solving skills
o Creativity and imaginary skills
o Programming skills
o Deployment
o Testing skills
o Debugging skills
o Project presentation skills
o Thesis writing skills
Paper Publishing
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Disclaimer - Takeoff Edu Group Projects are not associated or affiliated with IEEE in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, not projects of or by IEEE.
