Power Spectral Density (PSD) is an essential representation of the signal spectrum that depicts the power measurement content versus frequency. PSD is typically used to characterize broadband random signals and has a variety of usages in many fields like physics, engineering, biomedical, etc. This paper proposes a simple and practical method to estimate the PSD based on the Welch algorithm for spectrum monitoring. The proposed method can be easily implemented in most of software-based systems or low-level Field-Programmable Gate Arrays (FPGAs) and yields a smooth overview of the spectrum. The original Welch method utilizes the average of the amplitude squared of the previous Fast Fourier Transform (FFT) samples for better estimation of frequency components and noise reduction. Replacing the simple moving average with a weighted moving average can significantly reduce the complexity of the Welch’s method. In this way, the amount of required Random Access Memory (RAM) is reduced from K (where K is the number of FFT packets in averaging) to one. This new method allows users to adjust the dependency of the PSD on the previous observed FFTs and its smoothness by setting only one feedback parameter without any hardware change. The obtained results show that the algorithm gives a clear spectrum, even in the noisy situation because of the significant Signal to Noise Ratio (SNR) enhancement. The trade-off between spectrum accuracy and time convergence of the modified algorithm is also fully analysed. In addition, a simple solution based on Xilinx Intellectual Property (IP), which converts the proposed method to a practical spectrum analyzer device, is presented. This modified algorithm is validated by comparing it with two standard and reliable spectrum analyzers, Rohde & Schwarz (R&S) and Tektronix RSA600. The modified design can track any signal type as the other spectrum analyzers, and it has better performance in situations where the power of the desired signal is weak or where the signal is mixed with the background noise. It can display the spectrum when the input signal power is 5 dB lower than the visible threshold level of R&S and Tektronix. In both narrowband and wideband scenarios, the new implemented design can still display frequency components 5 dB higher than the noise, while the output spectrum of other analyzers is completely covered by noise.
By increasing the demand for radio frequency (RF) and access of hackers and spoofers to low price hardware and software defined radios (SDR), radio frequency interference (RFI) became a more frequent and serious problem. In order to increase the security of satellite communication (Satcom) and guarantee the quality of service (QoS) of end users, it is crucial to detect the RFI in the desired bandwidth and protect the receiver with a proper mitigation mechanism. Digital narrowband signals are so sensitive into the interference and because of their special power spectrum shape, it is hard to detect and eliminate the RFI from their bandwidth. Thus, a proper detector requires a high precision and smooth estimation of input signal power spectral density (PSD). By utilizing the presented power spectrum by the simplified Welch method, this article proposes a solid and effective algorithm that can find all necessary interference parameters in the frequency domain while targeting practical implantation for the embedded system with minimum complexity. The proposed detector can detect several multi narrowband interferences and estimate their center frequency, bandwidth, power, start, and end of each interference individually. To remove multiple interferences, a chain of several infinite impulse response (IIR) notch filters with multiplexers is proposed. To minimize damage to the original signal, the bandwidth of each notch is adjusted in a way that maximizes the received signal to noise ratio (SNR) by the receiver. Multiple carrier wave interferences (MCWI) is utilized as a jamming attack to the Digital Video Broadcasting-Satellite-Second Generation (DVB-S2) receiver and performance of a new detector and mitigation system is investigated and validated in both simulation and practical tests. Based on the obtained results, the proposed detector can detect a weak power interference down to −25 dB and track a hopping frequency interference with center frequency variation speed up to 3 kHz. Bit error ratio (BER) performance shows 3 dB improvement by utilizing new adaptive mitigation scenario compared to non-adaptive one. Finally, the protected DVB-S2 can receive the data with SNR close to the normal situation while it is under the attack of the MCWI jammer.
The abundance of radio signals and their increasing number creates interferences on adjacent signals and sometimes, with co-channel communication. Jammers, which are operated by hackers or by military forces, are another source of smart and powerful interferences. This paper will discuss the effect of the continuous wave interference (CWI) on a radio communication receiver, specifically with the Digital Video Broadcasting for Satellite Second Generation (DVB-S2) communication standard. It investigates the general effect of the interference on a Quadrature Phase Shift Keying (QPSK) signal over each part of the DVB-S2 receiver. It also focuses on the impact of the center frequency and power of the interference on the critical blocks of a DVB-S2 receiver. This study also tries to determine the deviation from the normal operation in the format of mathematical expressions and simulation results. Based on the obtained results, there is a vulnerability in the chain of the receiver’s blocks that allows a smart jammer to affect the device with low power interference. The notch filter is utilized as a solution to mitigate the interference. In addition, the effects of this technique on the system’s performance are studied. The simulation results show that there is a great improvement after CWI removal according to the Jamming to Signal Ratio (JSR), the Signal-to-Noise Ratio (SNR), and the Bit Error Rate (BER). In some cases, the JSR was reduced by 15 dB, the SNR was improved by 10 dB and BER also improved by 7 dB. However, the notch filter deletes some information from the original signal. This study introduces new ways to clarify the tradeoff between the amount of interference power reduction and removed bandwidth from the signal with notch filtering.
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