Transformation of AC to DC using Direct Sequence Spread Spectrum (DSSS) Technique for Electromagnetic Inference

2021 ◽  
Vol 6 (3) ◽  
pp. 12-21
Author(s):  
R. Rajendra Kumar ◽  
◽  
Vivekananda Ganji ◽  
Keyword(s):  
Power Spectrum ◽  
Spread Spectrum ◽  
Dead Time ◽  
Electromagnetic Emission ◽  
Alternate Current ◽  
Direct Sequence Spread Spectrum ◽  
Strip Line ◽  
Direct Sequence ◽  
Single Chip ◽  
Switching Node

Before more functions of the circuit are integrated into several electromagnetic a single die or small integrated die or small integrated interference (EMI) people impacted by ac-dc converter kit, expanding. The dominant electromagnetic emission. In this paper Alternate Current (AC) - Direct Current (DC) converter source is delineated by gauging the ac-dc converter source of the nodes' power spectrum. The activity of the noise scanner is linked to a noise scanner, a crowded ac-dc converter single-chip prototype. The data revealed the converter's superior electromagnetic source of the emission is the switching node, not the output node. The technique of direct sequence spread spectrum to counteract the switching node toxins, the ac- dc converter should be used and its profitability is the temperature distribution and pragmatically validated. The Mathematical statement of the technique of direct sequence spread spectrum is proposed for the study of its pharmacokinetics in the significant decrease of EMI and optimal installation using the technique of direct sequence spread spectrum with 0.18-μm CMOSS, dead-time control is assembled and coding. The plotted reduction in the power spectrum. The optimum direct sequence spread spectrum technique installation and managerial staff of dead-time is the node at the 16 dB switch. The stock of the proposed declines in the EMI reduction. The IC-strip line approach improved the design by 12.6 dB on fundamental frequency switching.

A single-chip 12.7 Mchips/s digital IF BPSK direct sequence spread-spectrum transceiver in 1.2 μm CMOS

1994 ◽  
Vol 29 (12) ◽  
pp. 1614-1623 ◽  
Author(s):  
C. Chien ◽  
R. Jain ◽  
E.G. Cohen ◽  
H. Samueli
Keyword(s):  
Spread Spectrum ◽  
Direct Sequence Spread Spectrum ◽  
Direct Sequence ◽  
Single Chip

Analisis Karakterisasi Teknologi Direct Sequence Spread Spectrum Dan Frequency Hopping Spread Spectrum

2019 ◽  
Vol 2 (2) ◽  
pp. 129-138
Author(s):  
Fawzan Galib Abdul Karim Bawahab ◽  
Elvan Yuniarti ◽  
Edi Kurniawan
Keyword(s):  
Spread Spectrum ◽  
Communication Systems ◽  
Multiple Access ◽  
Frequency Hopping ◽  
Direct Sequence Spread Spectrum ◽  
Direct Sequence ◽  
Frequency Hopping Spread Spectrum ◽  
Two Systems ◽  
The Difference

Abstrak. Pada penelitian ini, telah dilakukan analisa karakterisasi pada teknologi Direct Sequence Spread Spectrum dan Frequency Hopping Spread Spectrum, sebagai salah satu teknik multiple-access pada sistem komunikasi. Karakterisasi dilakukan untuk mencari bagaimana cara meningkatkan keoptimalan kedua sistem tersebut, dalam mengatasi masalah interferensi dengan sistem dan channel yang sama. Dan juga untuk menentukan veriabel apa yang mempengaruhi keoptimalan kedua sistem tersebut. Karakterisasi dilakukan dengan menentukan variabel-variabel yang mempengaruhi keoptimalan keduanya. Hasil dari karakterisasi, diketahui variabel-variabel yang mempengaruhi kemampuan sistem DSSS yaitu nilai frekuensi spreading (). Sedangkan untuk sistem FHSS yaitu nilai frekuensi spreading ( dan ) dan selisih antara frekuensi hopping data dengan frekuensi hopping interferensi . Kata Kunci: BER, DSSS, FHSS, Interference, Spread spectrum. Abstract. In this study, characterization of Direct Sequence Spread Spectrum and Frequency Hopping Spread Spectrum technologies have been done, as one of the multiple-access techniques in communication systems. Characterization is done to find out how to improve the ability of the two systems, in solving interference problems with the same system and channel. And also to determine what veriabel affects the ability of the two systems. Characterization is done by determining the variables that affect the ability of both. The results of the characterization, known variables that affect the ability of the DSSS system are the spreading frequency value (). As for the FHSS system, the spreading frequency value ( and ) and the difference between frequency hopping data with frequency hopping interference .

Enhanced performance direct sequence spread spectrum code acquisition

1995 ◽  
Vol 31 (16) ◽  
pp. 1323-1325
Author(s):  
A.J. Eynon ◽  
T.C. Tozer
Keyword(s):  
Spread Spectrum ◽  
Direct Sequence Spread Spectrum ◽  
Direct Sequence ◽  
Code Acquisition

scholarly journals Adaptive Detection of Direct-Sequence Spread-Spectrum Signals Based on Knowledge-Enhanced Compressive Measurements and Artificial Neural Networks

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2538
Author(s):  
Shuang Zhang ◽  
Feng Liu ◽  
Yuang Huang ◽  
Xuedong Meng
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Spread Spectrum ◽  
High Efficiency ◽  
Detection System ◽  
Direct Sequence Spread Spectrum ◽  
Detection Performance ◽  
Detection Methods ◽  
Direct Sequence ◽  
Artificial Neural

The direct-sequence spread-spectrum (DSSS) technique has been widely used in wireless secure communications. In this technique, the baseband signal is spread over a wider bandwidth using pseudo-random sequences to avoid interference or interception. In this paper, the authors propose methods to adaptively detect the DSSS signals based on knowledge-enhanced compressive measurements and artificial neural networks. Compared with the conventional non-compressive detection system, the compressive detection framework can achieve a reasonable balance between detection performance and sampling hardware cost. In contrast to the existing compressive sampling techniques, the proposed methods are shown to enable adaptive measurement kernel design with high efficiency. Through the theoretical analysis and the simulation results, the proposed adaptive compressive detection methods are also demonstrated to provide significantly enhanced detection performance efficiently, compared to their counterpart with the conventional random measurement kernels.

Sign in / Sign up

Export Citation Format

Share Document