ESTIMATION OF CHANNEL USING FFT IN INTELLIGENT REFLECTING SURFACES FOR 5G AND BEYOND
Objective
The objective is to evaluate an FFT-based channel estimation method for an IRS-assisted 5G OFDM communication system, focusing on beamforming, multipath delay spread, SNR variations, RE count, and training sequence sparsity.
Abstract
Intelligent reflecting surfaces (IRS) are made up of numerous independently controlled passive reflecting elements (RE) that can combine coherently to allow beamforming and adjust the amplitude and phase of the reflected signals. Estimating the incoming and outgoing channels' channel coefficients is necessary for beamforming. This work investigates the effectiveness of the Fast Fourier transform (FFT)-based channel estimation technique using an IRS-assisted Fifth Generation (5G) orthogonal frequency division multiplexing (OFDM) waveform communication system. Since DFT-based channel estimate does not take the entire OFDM symbol for pilot transmission, it can be carried out while data is being provided. For different Signal-to-Noise Ratio (SNR) values with and without a direct channel, the impacts of multipath delay spread, the number of REs, and training sequence sparsity in the OFDM symbol are thus mentioned. The findings demonstrate that delay spread can reduce training cycles and has a significant effect on performance.
Keywords: 5G, Intelligent Reflecting Surfaces (IRS), Reflecting Elements (RE), Orthogonal Frequency Division Multiplexing (OFDM) and Fast Fourier Transform (FFT).
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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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