Bandwidth compression of noisy signals with square-wave subcarrier

This article discusses a method for downconverting the square-wave subcarrier of spacecraft signals, such as the one from Galileo, which results in a compression bandwidth that lowers the sample rate significantly. The study is focused on three issues. The first is the selection of an adequate down-mixing signal for the resulting signal to have a format similar to that of the original signal, except at a lower subcarrier frequency. The second is the control of the noise level so that the signal to noise ratio is not degraded due to the downconversion. The third is to determine the bandwidth of the downconverted signal considering the uncertainty of the residual carrier frequency

Symbol signal-to-noise ratio loss in square-wave subcarrier downconversion

This article presents the simulated results of the signal-to-noise ratio (SNR) loss in the process of a square-wave subcarrier down conversion. In a previous article, the SNR degradation was evaluated at the output of the down converter based on the signal and noise power change. Unlike in the previous article, the SNR loss is defined here as the difference between the actual and theoretical symbol SNR's for the same symbol-error rate at the output of the symbol matched filter. The results show that an average SNR loss of 0.3 dB can be achieved with tenth-order infinite impulse response (IIR) filters. This loss is a 0.2-dB increase over the SNR degradation in the previous analysis where neither the signal distortion nor the symbol detector was considered

SNR degradation in square-wave subcarrier downconversion

This article presents a study of signal-to-noise ratio (SNR) degradation in the process of square-wave subcarrier downconversion. The study shows three factors that contribute to the SNR degradation: the cutoff of the higher frequency components in the data, the approximation of a square wave with a finite number of harmonics, and nonideal filtering. Both analytical and simulation results are presented

A closed-loop time-alignment system for baseband combining

In baseband combining, the key element is the time alignment of the baseband signals. This article describes a closed-loop time-alignment system that estimates and adjusts the relative delay between two baseband signals received from two different antennas for the signals to be coherently combined. This system automatically determines which signal is advanced and delays it accordingly with a resolution of a sample period. The performance of the loop is analyzed, and the analysis is verified through simulation. The variance of the delay estimates and the signal-to-noise ratio degradation in the simulations agree with the theoretical calculations

A complex symbol signal-to-noise ratio estimator and its performance

This article presents an algorithm for estimating the signal-to-noise ratio (SNR) of signals that contain data on a downconverted suppressed carrier or the first harmonic of a square-wave subcarrier. This algorithm can be used to determine the performance of the full-spectrum combiner for the Galileo S-band (2.2- to 2.3-GHz) mission by measuring the input and output symbol SNR. A performance analysis of the algorithm shows that the estimator can estimate the complex symbol SNR using 10,000 symbols at a true symbol SNR of -5 dB with a mean of -4.9985 dB and a standard deviation of 0.2454 dB, and these analytical results are checked by simulations of 100 runs with a mean of -5.06 dB and a standard deviation of 0.2506 dB

Testing the performance of feedback concatenated decoder with a nonideal receiver

One of the inherent problems in testing the feedback concatenated decoder (FCD) at our operating symbol signal-to-noise ratio (SSNR) is that the bit-error rate is so low that we cannot measure it directly through simulations in a reasonable time period. This article proposes a test procedure that will give a reasonable estimate of the expected losses even though the number of frames tested is much smaller than needed for a direct measurement. This test procedure provides an organized robust methodology for extrapolating small amounts of test data to give reasonable estimates of FCD loss increments at unmeasurable miniscule error rates. Using this test procedure, we have run some preliminary tests on the FCD to quantify the losses due to the fact that the input signal contains multiplicative non-white non-Gaussian noises resulting from the buffered telemetry demodulator (BTD). Besides the losses in the BTD, we have observed additional loss increments of 0.3 to 0.4 dB at the output of the FCD for several test cases with loop signal-to-noise ratios (SNR's) lower than 20 dB. In contrast, these loss increments were less than 0.1 dB for a test case with the subcarrier loop SNR at about 28 dB. This test procedure can be applied to more extensive test data to determine thresholds on the loop SNRs above which the FCD will not suffer substantial loss increments

Towards optimum demodulation of bandwidth-limited and low SNR square-wave subcarrier signals

The optimum phase detector is presented for tracking square-wave subcarriers that have been bandwidth limited to a finite number of harmonics. The phase detector is optimum in the sense that the loop signal-to-noise ratio (SNR) is maximized and, hence, the rms phase tracking error is minimized. The optimum phase detector is easy to implement and achieves substantial improvement. Also presented are the optimum weights to combine the signals demodulated from each of the harmonics. The optimum weighting provides SNR improvement of 0.1 to 0.15 dB when the subcarrier loop SNR is low (15 dB) and the number of harmonics is high (8 to 16)

Seamless data-range change using punctured convolutional codes for time-varying signal-to-noise ratios

In a time-varying signal-to-noise ration (SNR) environment, symbol rate is often changed to maximize data return. However, the symbol-rate change has some undesirable effects, such as changing the transmission bandwidth and perhaps causing the receiver symbol loop to lose lock temporarily, thus losing some data. In this article, we are proposing an alternate way of varying the data rate without changing the symbol rate and, therefore, the transmission bandwidth. The data rate change is achieved in a seamless fashion by puncturing the convolutionally encoded symbol stream to adapt to the changing SNR environment. We have also derived an exact expression to enumerate the number of distinct puncturing patterns. To demonstrate this seamless rate change capability, we searched for good puncturing patterns for the Galileo (14,1/4) convolutional code and changed the data rates by using the punctured codes to match the Galileo SNR profile of November 9, 1997. We show that this scheme reduces the symbol-rate changes from nine to two and provides a comparable data return in a day and a higher symbol SNR during most of the day

Degradation in finite-harmonic subcarrier demodulation

Previous estimates on the degradations due to a subcarrier loop assume a square-wave subcarrier. This article provides a closed-form expression for the degradations due to the subcarrier loop when a finite number of harmonics are used to demodulate the subcarrier, as in the case of the buffered telemetry demodulator. We compared the degradations using a square wave and using finite harmonics in the subcarrier demodulation and found that, for a low loop signal-to-noise ratio, using finite harmonics leads to a lower degradation. The analysis is under the assumption that the phase noise in the subcarrier (SC) loop has a Tikhonov distribution. This assumption is valid for first-order loops

Catalogo oficial de la exposicion y feria de muestras y album de Malaga y su provincia : 1924

Copia digital. realizada por la Biblioteca de Andalucí