Mitigation of spectral leakage for single carrier, block-processing cognitive radio receivers

Cognitive Radio （CR） is a multiuser, wireless communication concept that allows for a dynamic and adaptive assignment of spectral resources. The coexistence of multiple users, often transmitting at significantly different power levels, makes CR receivers vulnerable to spectral leakage caused by components＇ nonlinearities and timetruncation of the processed signal records. In this work we propose a method for mitigating the latter with an adaptive choice of the length of the processing block size. With simulations we show that a significant leakage reduction that leads to receiver dynamic range improvement of around 10 dB can be achieved with the proposed method.

A software sampling frequency adaptive algorithm for reducing spectral leakage

Spectral leakage caused by synchronous error in a nonsynchronous sampling system is an important cause that reduces the accuracy of spectral analysis and harmonic measurement.This paper presents a software sampling fre-quency adaptive algorithm that can obtain the actual signal frequency more accurately,and then adjusts sampling in-terval base on the frequency calculated by software algo-rithm and modifies sampling frequency adaptively.It can reduce synchronous error and impact of spectral leakage;thereby improving the accuracy of spectral analysis and harmonic measurement for power system signal where fre-quency changes slowly.This algorithm has high precision just like the simulations show,and it can be a practical method in power system harmonic analysis since it can be implemented easily.

Enhanced Wideband Frequency Estimation via FFT: Leveraging Polynomial Interpolation and Array Indexing

Accurate frequency estimation in a wideband digital receiver using the FFT algorithm encounters challenges, such as spectral leakage resulting from the FFT’s assumption of signal periodicity. High-resolution FFTs pose computational demands, and estimating non-integer multiples of frequency resolution proves exceptionally challenging. This paper introduces two novel methods for enhanced frequency precision: polynomial interpolation and array indexing, comparing their results with super-resolution and scalloping loss. Simulation results demonstrate the effectiveness of the proposed methods in contemporary radar systems, with array indexing providing the best frequency estimation despite utilizing maximum hardware resources. The paper demonstrates a trade-off between accurate frequency estimation and hardware resources when comparing polynomial interpolation and array indexing.

Windowing Techniques, the Welch Method for Improvement of Power Spectrum Estimation

This paper revisits the characteristics of windowing techniques with various window functions involved,and successively investigates spectral leakage mitigation utilizing the Welch method.The discrete Fourier transform(DFT)is ubiquitous in digital signal processing(DSP)for the spectrum analysis and can be efciently realized by the fast Fourier transform(FFT).The sampling signal will result in distortion and thus may cause unpredictable spectral leakage in discrete spectrum when the DFT is employed.Windowing is implemented by multiplying the input signal with a window function and windowing amplitude modulates the input signal so that the spectral leakage is evened out.Therefore,windowing processing reduces the amplitude of the samples at the beginning and end of the window.In addition to selecting appropriate window functions,a pretreatment method,such as the Welch method,is effective to mitigate the spectral leakage.Due to the noise caused by imperfect,nite data,the noise reduction from Welch’s method is a desired treatment.The nonparametric Welch method is an improvement on the periodogram spectrum estimation method where the signal-to-noise ratio(SNR)is high and mitigates noise in the estimated power spectra in exchange for frequency resolution reduction.The periodogram technique based on Welch method is capable of providing good resolution if data length samples are appropriately selected.The design of nite impulse response(FIR)digital lter using the window technique is rstly addressed.The inuence of various window functions on the Fourier transform spectrum of the signals is discussed.Comparison on spectral resolution based on the traditional power spectrum estimation and various window-function-based Welch power spectrum estimations is presented.

A Blackman-Harris windowed triple-spectrum-line interpolation method for measuring SNR of ADCs

In the practical measurement of signal to noise ratio(SNR)of analog-to-digital converters(ADCs)by using fast Fourier transformation(FFT)method,the non-coherent sampling is inevitable,leading to spectral leakage which in turn affects the calculation accuracy and final measurement results.In this paper,a new method based on the Blackman-Harris windowed triple-spectrum-line interpolation is presented for the measurement of ADCs SNR by FFT.The simulation platform is built based on MATLAB and the behavioral dynamic models of the high-speed ADC products of Analog Devices Inc.(ADI)are simulated.The simulation results show that,even in the case of the maximum non-coherent degree,the SNR error is less than0.23dB and reaches the testing standards provided by ADI,confirming that the proposed method is effective for suppressing the spectral leakage effects and improving the SNR test accuracy.