Channel estimation and secure data transmission using hybrid particle swarm optimisation–gray wolf optimisation‐leaky least‐Mean‐Square and affine elliptic curves cryptography algorithm in MU‐multi‐input multi‐output orthogonal frequency division multiplexing system

Summary In a huge multi‐input multi‐output orthogonal frequency divisions multiplexing (MIMO‐OFDM), an exact Channel State Information (CSI) is required to understand the system performance, which includes high spectrum together with energy efficiency. Using the OFDM, substantial numbers of pilots a...

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Vydáno v:International journal of communication systems Ročník 38; číslo 1
Hlavní autoři: R, Jeya, Amutha, B.
Médium: Journal Article
Jazyk:angličtina
Vydáno: 10.01.2025
Témata:
channel estimation
Grey wolf optimisation
guard interval (GI)
leaky least‐Mean‐Square (LLMS)
massive multiple‐input multiple‐output (MIMO)
modified QPSK (MQPSK)
orthogonal frequency division multiplexing (OFDM)
particle swarm optimisation
quadrature phase shift keying (QPSK)
ISSN:1074-5351, 1099-1131
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Shrnutí:Summary In a huge multi‐input multi‐output orthogonal frequency divisions multiplexing (MIMO‐OFDM), an exact Channel State Information (CSI) is required to understand the system performance, which includes high spectrum together with energy efficiency. Using the OFDM, substantial numbers of pilots are distributed over a huge range of time–frequency sources to efficiently assess a vast range of channel coefficients in space along with the frequency domains, forfeiting spectral efficiency. Here, an optimised Channel Estimation (CE) framework aimed at the MU‐MIMO OFDM system is proposed utilising Hybrid Particle Swarm Optimisation–Gray Wolf Optimisation‐Leaky Least‐Mean‐Square (HPG‐LLMS) to attain high accurateness and secure data transmission (DT) with the aid of proposed Affine ECC. Herein, the video is considered as an input in the transmitter side and transformed into data frames and compressed with the help of ASCII‐based Huffman algorithm. Using Affine ECC, the compressed data are encrypted as well as modulated with the help of the MQPSK method. Then, transmute the modulated data into IFFT and incorporate the Guard Interval (GI) to the data. And then, over the Multi‐Path Channel (MPC), the symbols will be passed on to the receiver with the Additives White Gaussian Noise (AWGN). Execute the Inverse operations on the receiver side and centred on fuzzy centred priority scheduling algorithm (FPSA), sent the data to the user. Lastly, utilising HPG‐LLMS, the CE is performed.
ISSN:1074-5351
1099-1131
DOI:10.1002/dac.4791