Effects of reconstruction filters and sampling rate for a digital signal component separator on LINC transmitter performance

1995 ◽  
Vol 31 (14) ◽  
pp. 1124 ◽  
Author(s):  
L. Sundström
Keyword(s):  
Sampling Rate ◽  
Digital Signal ◽  
Signal Component

The influence of sampling frequency and interpolation on the bit error rate of GMSK signal

2021 ◽  
pp. 108-114
Author(s):  
D.D. Privalov
Keyword(s):  
Signal Detection ◽  
Bit Error Rate ◽  
Error Rate ◽  
Clock Synchronization ◽  
Additive White Gaussian Noise ◽  
Sampling Rate ◽  
Digital Signal ◽  
Sampling Frequency ◽  
Synchronization Error ◽  
Minimum Number

The sampling rate at a given bit rate is a requirement for the speed of digital signal processors. In this regard, it is necessary to strive to reduce it in the development of electronic devices, especially portable ones. However, this can lead to an increase in the bit error rate during signal detection. Therefore, it is important to determine the degradation of signal detection with decreasing sampling frequency and to develop practical recommendations to ensure the specified quality of communication. The aim of the article is to study the influence of sampling frequency and interpolation on the bit error rate of GMSK Signal. The article considers the incoherent detection of a GMSK signal in a channel with additive white Gaussian noise, taking into account the influence of the clock synchronization error. Numerical results are presented that characterize an increase in the bit error rate with a decrease in the signal sampling frequency. It is shown that when using the cubic Farrow interpolator, there is no significant degradation in the bit error probability. The minimum number of samples per symbol is determined, at which the bit error rate is close to the theoretical values in the absence of synchronization error. The presented results can be used in development of wireless data transmission systems.

Low-memory digital signal component separator for LINC transmitters

2001 ◽  
Vol 37 (7) ◽  
pp. 460 ◽  
Author(s):  
C.P. Conradi ◽  
J.G. McRory ◽  
R.H. Johnston
Keyword(s):  
Digital Signal ◽  
Signal Component

A Real Time Power System Harmonic Estimator Considering Fundamental Frequency Variations

2010 ◽  
Vol 11 (4) ◽  
Author(s):  
Mohammad Reza Dadash Zadeh
Keyword(s):  
Power Systems ◽  
Power System ◽  
Real Time ◽  
Fundamental Frequency ◽  
Digital Signal Processor ◽  
Sampling Rate ◽  
Window Size ◽  
Digital Signal ◽  
Computation Method ◽  
Harmonic Components

A new technique based on orthogonal filters and iterative frequency tracking is proposed to estimate harmonic components in power systems for real time applications. Frequency interpolation is used to estimate fundamental frequency and harmonics when the nominal frequency of the signal is a non-integer value. Fixed data window size and fixed sampling rate are the two advantageous features of the proposed technique. An off-line computation method with linear interpolation is proposed to reduce the number of computations involved during the generation of filter coefficients. The proposed technique was implemented using a real-time DSP (digital signal processor) data acquisition system. The performance of the proposed technique was studied by estimating the harmonic components of various signals. A FFT (Fast Fourier Transform) based technique was also used to estimate harmonic components for comparison. It has been shown that the accurate fundamental frequency is computed using iterative technique, and then accurate harmonic components are estimated when the fundamental frequency is not equal to the power system nominal frequency.

scholarly journals Calculation of signal spectrum by means of stochastic inversion

2010 ◽  
Vol 28 (7) ◽  
pp. 1409-1418 ◽  
Author(s):  
T. Nygrén ◽  
Th. Ulich
Keyword(s):  
Fourier Transform ◽  
Sampling Rate ◽  
Digital Signal ◽  
Close Relation ◽  
Signal Spectrum ◽  
Inversion Method ◽  
Stochastic Inversion ◽  
Data Points ◽  
Sinusoidal Functions ◽  
The Fourier Transform

Abstract. The standard method of calculating the spectrum of a digital signal is based on the Fourier transform, which gives the amplitude and phase spectra at a set of equidistant frequencies from signal samples taken at equal intervals. In this paper a different method based on stochastic inversion is introduced. It does not imply a fixed sampling rate, and therefore it is useful in analysing geophysical signals which may be unequally sampled or may have missing data points. This could not be done by means of Fourier transform without preliminary interpolation. Another feature of the inversion method is that it allows unequal frequency steps in the spectrum, although this property is not needed in practice. The method has a close relation to methods based on least-squares fitting of sinusoidal functions to the signal. However, the number of frequency bins is not limited by the number of signal samples. In Fourier transform this can be achieved by means of additional zero-valued samples, but no such extra samples are used in this method. Finally, if the standard deviation of the samples is known, the method is also able to give error limits to the spectrum. This helps in recognising signal peaks in noisy spectra.

PC104 Interface Recommended for High Speed Data Acquisition Systems

2013 ◽  
Vol 325-326 ◽  
pp. 926-929 ◽  
Author(s):  
Dorina Purcaru ◽  
Cornelia Gordan ◽  
Romulus Reiz ◽  
Anca Purcaru
Keyword(s):  
Data Acquisition ◽  
High Speed ◽  
Low Cost ◽  
Sampling Rate ◽  
Digital Signal ◽  
Signal Acquisition ◽  
Synchronized Sampling ◽  
Data Acquisition Systems ◽  
High Speed Data Acquisition ◽  
High Speed Data

The interface presented in this paper is recommended for high speed data acquisition systems; it performs a synchronized sampling of all common-mode or differential analog inputs with a high sampling rate. This is a low cost interface, entirely controlled by the PC104 CPU. Programmable electronic modules that contain such PC104 interfaces can be found running in the energetic system from Romania; these dedicated equipments perform the analog and digital signal acquisition for monitoring and recording different specific transient events. Some experimental results obtained using the disturbance monitoring device PC-08/104 are also presented in this paper.

The Design and FPGA Implementation of a Polyphase SRRC FIR Filter in DTMB

2013 ◽  
Vol 791-793 ◽  
pp. 2122-2126
Author(s):  
Jing Chen ◽  
Chang Yin Liu ◽  
Xue Ping Li
Keyword(s):  
Field Programmable Gate Array ◽  
Traditional Method ◽  
Sampling Rate ◽  
Digital Signal ◽  
Response Speed ◽  
Fir Filter ◽  
Fir Filters ◽  
Square Root ◽  
Field Programmable ◽  
Hardware Resource

Polyphase FIR filters are applied in many practical Digital Signal Processing applications where the sampling rate needs to be changed. This paper focuses on the implementation of polyphase square root raised cosine (SRRC) FIR filter based on Field Programmable Gate Array (FPGA). The filter employs methods like filter's multiphase structure, symmetrical coefficients, I/Q channel multiplexing, pipeline addition and so on to design the SRRC filter. Compared with the traditional method, the designed FIR filter exhibits the advantages of high response speed and low hardware resource s consumption.

Fundamentals of Multirate Systems

2011 ◽  
pp. 1601-1605
Author(s):  
Gordana Jovanovic Dolecek
Keyword(s):  
Signal Processing ◽  
Integrated Circuits ◽  
Digital Signal Processing ◽  
Rapid Development ◽  
Sampling Rate ◽  
Digital Signal ◽  
Digital Signals ◽  
Multiple Sampling ◽  
Multirate System ◽  
Rate Conversion

Digital signal processing (DSP) is an area of science and engineering that has been rapidly developed over the past years. This rapid development is a result of significant advances in digital computers technology and integrated circuits fabrication (Mitra, 2005; Smith, 2002). Classical digital signal processing structures belong to the class of single-rate systems since the sampling rates at all points of the system are the same. The process of converting a signal from a given rate to a different rate is called sampling rate conversion. Systems that employ multiple sampling rates in the processing of digital signals are called multirate digital signal processing systems. Sample rate conversion is one of the main operations in a multirate system (Harris, 2004; Stearns, 2002).

scholarly journals Estimation of Ultrasonic Attenuation and Mean Backscatterer Size via Digital Signal Processing

1984 ◽  
Vol 6 (1) ◽  
pp. 13-23 ◽  
Author(s):  
C. R. Meyer ◽  
D. S. Herron ◽  
P. L. Carson ◽  
R. A. Banjavic ◽  
G. A. Thieme ◽  
...  
Keyword(s):  
Ultrasonic Attenuation ◽  
Sampling Rate ◽  
Power Spectra ◽  
Digital Signal ◽  
Lung Maturation ◽  
Fetal Sheep ◽  
Rf Signals ◽  
Ultrasonic Parameters ◽  
Ultrasonic Scanner ◽  
Rf Signal

The backscattered rf signals from the lungs of fetal sheep during their last trimester of development were digitized and processed in an attempt to correlate ultrasonic parameters with measured functional parameters related to lung maturation. The broadband, post-TGC, rf signal of a commercial B-mode ultrasonic scanner was digitized at a sampling rate of 25 MHz. Sorting excluded data from regions of rib shadowing and other nonlung structures from analysis. The sorted data were used to estimate the slope of the ultrasonic attenuation coefficient with respect to frequency via linear regression on the average difference of the logarithm of power spectra from separated data segments. The power spectra were also corrected for attenuation, averaged and used to compute the power cepstrum of the backscattered signal which can be related to mean backscatterer radius. Results are presented for eight fetal sheep.

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