scholarly journals I Implementasi Sistem Hermitian Generalized LED Index Modulation (H-GLIM-OFDM) pada Board FPGA Xilinx Arty Artix-7

Electrician ◽  
2020 ◽  
Vol 14 (3) ◽  
pp. 100-111
Author(s):  
Yetti Yuniati
Keyword(s):  
Visible Light ◽  
Field Programmable Gate Array ◽  
Orthogonal Frequency Division Multiplexing ◽  
Visible Light Communication ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Transfer Data ◽  
System Generator ◽  
Field Programmable ◽  
Index Modulation

Abstrak— Komunikasi nirkabel menjadi jenis komunikasi yang digunakan secara luas, spektrum radio yang umumnya digunakan dalam komunikasi nirkabel menjadi tidak cukup untuk memenuhi tuntutan yang tinggi. Visible Light Communication (VLC) menjadi solusi untuk mengatasi kapasitas bandwidth yang kurang memadai ini. Orthogonal Frequency Division Multiplexing (OFDM) menjadi teknik yang dikembangkan untuk sistem komunikasi cahaya tampak karena pada teknik OFDM frekuensi yang digunakan saling orthogonal dan memungkinkan overlap antar frekuensi tanpa menimbulkan interferensi satu sama lain sehingga menghasilkan kecepatan transfer data yang tinggi. Jurnal ini membahas tentang Implementasi Sistem Hermitian Generalized LED Index Modulation (H-GLIM-OFDM). Skema dari H-GLIM-OFDM ini dirancang dalam System Generator pada bahasa pemograman Matlab. Desain di implementasikan dalam FPGA dan diterapkan dengan spesifikasi Arty Board Xilinx Artix-7. Field Programmable Gate Array (FPGA) merupakan perangkat semikonduktor yang dapat diprogram secara fleksibel dan dapat melakukan kinerja yang tinggi untuk implementasi VLC. Hasil yang didapat pada simulasi ini yaitu menggunakan pemanfaatan sumber daya desain 5% BRAM, 11% dari DSP, 8% dari LUT, 18% dari IO, dan 3% BUFG.   Kata Kunci : H-GLIM-OFDM, FPGA Arty Artix-7, Visible Light Communication, Vivado, System Generator

scholarly journals Hardware Implementation of MISO on Orthogonal Frequency Division Multiplexing Platform with the Help of Alamouti Algorithm

2017 ◽  
Vol 63 (2) ◽  
pp. 137-143
Author(s):  
Seetaiah Kilaru
Keyword(s):  
Field Programmable Gate Array ◽  
Orthogonal Frequency Division Multiplexing ◽  
Hardware Implementation ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Test Bed ◽  
System Generator ◽  
Field Programmable ◽  
Simulation Results ◽  
Half Decade

Abstract Many software based OFDM techniques were proposed from last half decade to improve the performance of the system. This paper tried to implement the same with Hardware implementation. We created Hardware based MISO platform with OFDM. We implemented Alamouti algorithm on this test bed. The test bed is implemented with the help of Field Programmable Gate Array (FPGA). The test bed is functionalized with the help of FPGA through Xilinx based system generator for DSP. In this paper we considered the 2×1 MISO implementation with Alamouti algorithm. The simulation results showed that BER and SNR are considerably high for MISO than SISO. The results also proved that proposed OFDM based Alamouti implementation for MISO is excellent in all performance criterions.

Dynamic Hyperchaotic Key Generation Using Optical Orthogonal Frequency Division Multiplexing-based Visible Light Communication Networks

2021 ◽  
Author(s):  
Mohammed Alresheedi ◽  
YAHYA AL-MOLIKI ◽  
Yahya Al-Harthi ◽  
Ali Alqahtani
Keyword(s):  
Visible Light ◽  
Communication Networks ◽  
Orthogonal Frequency Division Multiplexing ◽  
Average Power ◽  
Visible Light Communication ◽  
Frequency Division Multiplexing ◽  
Key Generation ◽  
Frequency Division ◽  
Degree Of Protection ◽  
Communication Time

Abstract This paper introduces an optical orthogonal frequency division multiplexing (OFDM)-based hyperchaotic key generation encryption approach that can improve confidentiality in visible light communication (VLC) networks. Using a hyperchaotic four-dimensional method, the bipolar real-valued OFDM signal can be used for constructing dynamic cypher keys modified at every frame over the communication time, resulting in a superior degree of protection against statistical and correlation attacks. In accordance with our findings, this approach decreases the ratio of peak-to-average power of the transmitted signal, and enhances the bit error rate efficiency and secrecy capacity of the OFDM-based VLC network, which improves confidentiality.

A Real-Time Deep Learning OFDM Receiver

2022 ◽  
Vol 15 (3) ◽  
pp. 1-25
Author(s):  
Stefan Brennsteiner ◽  
Tughrul Arslan ◽  
John Thompson ◽  
Andrew McCormick
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Real Time ◽  
Field Programmable Gate Array ◽  
Orthogonal Frequency Division Multiplexing ◽  
Frequency Division Multiplexing ◽  
Frequency Division ◽  
Field Programmable ◽  
Gate Array ◽  
Fully Connected

Machine learning in the physical layer of communication systems holds the potential to improve performance and simplify design methodology. Many algorithms have been proposed; however, the model complexity is often unfeasible for real-time deployment. The real-time processing capability of these systems has not been proven yet. In this work, we propose a novel, less complex, fully connected neural network to perform channel estimation and signal detection in an orthogonal frequency division multiplexing system. The memory requirement, which is often the bottleneck for fully connected neural networks, is reduced by ≈ 27 times by applying known compression techniques in a three-step training process. Extensive experiments were performed for pruning and quantizing the weights of the neural network detector. Additionally, Huffman encoding was used on the weights to further reduce memory requirements. Based on this approach, we propose the first field-programmable gate array based, real-time capable neural network accelerator, specifically designed to accelerate the orthogonal frequency division multiplexing detector workload. The accelerator is synthesized for a Xilinx RFSoC field-programmable gate array, uses small-batch processing to increase throughput, efficiently supports branching neural networks, and implements superscalar Huffman decoders.

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