Channel Estimation in Intelligent Reflecting Surfaces for 5G and Beyond
Objective
The primary objective of this project is to develop advanced channel estimation techniques tailored to the unique capabilities and challenges posed by Intelligent Reflecting Surfaces (IRS) in the context of 5G and future generations of wireless communication systems
Abstract
The components of intelligent reflecting surfaces (IRS), which may adjust the phase and amplitude of the reflected signals and combine them coherently to provide beamforming, are many independently controlled passive reflecting elements (RE). It is necessary to estimate the incoming and outgoing channels' channel coefficients in order to perform beamforming. In this study, the effectiveness of the channel estimate approach based on the discrete Fourier transform (DFT) is investigated using an IRS-assisted communication system employing the Fifth Generation (5G) orthogonal frequency division multiplexing (OFDM) waveform. Because DFT-based channel estimate doesn't use the entire OFDM symbol for pilot transmission, it can be done while data is being transmitted. As a result, for various Signal-to-Noise Ratio (SNR) values with and without a direct channel, the impacts of multipath delay spread, the quantity of REs, and training sequence sparsity in the OFDM symbol are noticed. The findings indicate that delay spread significantly affects performance and can shorten training sequences.
Keywords: 5G, Intelligent Reflecting Surfaces (IRS), Reflecting Elements (RE), Orthogonal Frequency Division Multiplexing (OFDM) and Discrete Fourier Transform (DFT).
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.
