Title :
Optimum memoryless bandpass nonlinearities
Author :
Blachman, Nelson M.
Author_Institution :
GTE Government Systems Corp., Mountain View, CA, USA
Abstract :
Previous work on optimum memoryless bandpass nonlinearities is extended here and applied to cases involving various types of interference, which may, for example, include a cochannel or adjacent-channel angle-modulated waveform as well as narrowband Gaussian noise. At low input signal-to-interference ratios the nonlinearity that maximizes the output signal-to-noise-plus-interference-and-intermodulation ratio (SNIIMR) is identical with that which maximizes the signal´s probability of detection if the time-bandwidth product is large, i.e., the locally optimum Bayesian detector. Its performance is as much as 4.8 dB better than that of the optimum biased power-law rectifier. In the absence of noise, the output SNIIMR of the optimum memoryless bandpass nonlinearity (OMBPNL) is 0 dB whenever the desired signal is weaker than the interference. In the presence of weak input noise accompanying a weak input signal and a strong angle-modulated interfering waveform, the output SNIIMR of the OMBPNL becomes at least τ/(2+τ), where τ is the input signal-to-noise ratio (SNR), regardless of how strong the cochannel interference is. Thus, very large SNR improvements can be obtained without a notched filter, however large the bandwidth of the interference. Although the output SNIIMR will not exceed 0 dB when the input signal is weak, it can be raised to useful levels by the processing gain associated with a spread-spectrum signal
Keywords :
Bayes methods; Gaussian noise; adjacent channel interference; angle modulation; band-pass filters; cochannel interference; interference suppression; memoryless systems; military communication; nonlinear filters; optimal systems; signal detection; adjacent channel interference; angle-modulated waveform; cochannel interference; locally optimum Bayesian detector; narrowband Gaussian noise; optimum memoryless bandpass nonlinearities; performance; probability of detection; processing gain; weak input noise; weak input signal; Bayesian methods; Detectors; Filters; Gaussian noise; Interchannel interference; Narrowband; Rectifiers; Signal detection; Signal processing; Signal to noise ratio;
Conference_Titel :
Military Communications Conference, 1993. MILCOM '93. Conference record. Communications on the Move., IEEE
Conference_Location :
Boston, MA
Print_ISBN :
0-7803-0953-7
DOI :
10.1109/MILCOM.1993.408509