On SNR as a Measure of Performance for Narrowband Interference Rejection in Direct Sequence Spread Spectrum Systems

We simulate a nonlinearized Kalman [5], Kalman and a modified Kalman (linear) filter for suppressing a narrowband Gaussian interference in direct sequence spread spectrum receiver and examine the suitability of Signal-to-Noise Ratio (SNR) of the test statistic as a measure of performance of the receiver. We consider Gaussian autoregressive interference with a peaked spectrum and the three cases: small processing gain (PG) and short pseudonoise (PN) sequence, small PG and long PN sequence, and moderate PG and PN sequence. Based on the simulations, we conclude that for the two cases corresponding to small processing gain, if the thermal noise variance is small and the interference is strong, the Gaussian approximation to the test statistic does not yield the correct BER for any of the receivers. For small PG and short PN sequence, even though the SNR corresponding to nonlinear filter is significantly higher than the SNRs of the two linear filters, the BER of the non-linear is higher than that of the linear receivers. SNR is not a useful measure in these situations

On optimal design and applications of linear transforms

Linear transforms are encountered in many fields of applied science and engineering. In the past, conventional block transforms provided acceptable answers to different practical problems. But now, under increasing competitive pressures, with the growing reservoir of theory and a corresponding development of computing facilities, a real demand has been created for methods that systematically improve performance. As a result the past two decades have seen the explosive growth of a class of linear transform theory known as multiresolution signal decomposition. The goal of this work is to design and apply these advanced signal processing techniques to several different problems. The optimal design of subband filter banks is considered first. Several design examples are presented for M-band filter banks. Conventional design approaches are found to present problems when the number of constraints increases. A novel optimization method is proposed using a step-by-step design of a hierarchical subband tree. This method is shown to possess performance improvements in applications such as subband image coding. The subband tree structuring is then discussed and generalized algorithms are presented. Next, the attention is focused on the interference excision problem in direct sequence spread spectrum (DSSS) communications. The analytical and experimental performance of the DSSS receiver employing excision are presented. Different excision techniques are evaluated and ranked along with the proposed adaptive subband transform-based excises. The robustness of the considered methods is investigated for either time-localized or frequency-localized interferers. A domain switchable excision algorithm is also presented. Finally, sonic of the ideas associated with the interference excision problem are utilized in the spectral shaping of a particular biological signal, namely heart rate variability. The improvements for the spectral shaping process are shown for time-frequency analysis. In general, this dissertation demonstrates the proliferation of new tools for digital signal processing

Investigation of pre-detection signal processing of pseudonoise communication signals in the presence of additive white gaussian noise and CW and bursty interference

By comparison to conventional communication systems, spread-spectrum systems are known to be less affected by interference because of their large dimensionality in signal space. Nevertheless, significant performance degradation is experienced when large interference exists in a few or even one signal coordinates. In this case, interference reduction techniques are also known to provide additional processing gain. A novel class of pseudonoise (PN) invariant algorithms is derived to reduce the impact of interference and restore much of the structure of PN signals received in the presence of interference and noise. A PN signal received by a pre-detection signal process (PDSP) implementing a PN invariant algorithm remains unchanged at the output. When an interference waveform is added to the PN signal, most of the DC bias as well as other smooth components of the interference may be significantly reduced at the output of the same PDSP. If n is the longest run in the PN sequence of maximal length N, and Ro is the chip rate, it is shown that the algorithms work well when the interference is sinusoidal with a frequency deviation from the carrier up to Ro/N. At such a low frequency deviation, the processing gain is observed to be relatively high and independent of the phase deviation. As the frequency deviation Increases to nRo/N, the performance of the spread-spectrum system decreases to the level that would have been obtained in the absence of the PDSP

Ultra Wideband Impulse Radio Superregenerative Reception

Postprint (published version