Robust adaptive spread-spectrum receiver with neural net preprocessing in non-Gaussian noise

2001 ◽  
Vol 12 (3) ◽  
pp. 546-558 ◽  
Author(s):  
Teong Chee Chuah ◽  
B.S. Sharif ◽  
O.R. Hinton
Keyword(s):  
Gaussian Noise ◽  
Spread Spectrum ◽  
Neural Net ◽  
Robust Adaptive ◽  
Non Gaussian

M-Ary Alpha-Stable Noise Modulation in Spread-Spectrum Communication

2015 ◽  
Vol 14 (03) ◽  
pp. 1550022 ◽  
Author(s):  
Mehmet Emre Cek
Keyword(s):  
Gaussian Noise ◽  
Spread Spectrum ◽  
Additive White Gaussian Noise ◽  
Characteristic Exponent ◽  
Random Signal ◽  
Spread Spectrum Communication ◽  
Order Moment ◽  
Gaussian Density ◽  
Shift Keying ◽  
Non Gaussian

In this paper, a spread-spectrum communication system based on a random carrier is proposed which transmits M-ary information. The random signal is considered as a single realization of a random process taken from prescribed symmetric α-stable (SαS) distribution that carries digital M-ary information to be transmitted. Considering the noise model in the channel as additive white Gaussian noise (AWGN), the transmitter sends the information carrying random signal from non-Gaussian density. Alpha-stable distribution is used to encode the M-ary message. Inspired by the chaos shift keying techniques, the proposed method is called M-ary symmetric alpha-stable differential shift keying (M-ary SαS-DSK). The main purpose of preferring non-Gaussian noise instead of conventional pseudo-noise (PN) sequence is to overcome the drawback of self-repeating noise-like sequences which are detectable due to the periodic behavior of the autocorrelation function of PN sequences. Having infinite second order moment in α-stable random carrier offers secrecy of the information due to the non-constant autocorrelation behavior. The bit error rate (BER) performance of the proposed method is illustrated by Monte Carlo simulations with respect to various characteristic exponent values and different data length.

Adaptive Antenna Array Receivers for Spread-Spectrum Signals in Non-Gaussian Noise

2001 ◽  
Vol 11 (2) ◽  
pp. 144-158 ◽  
Author(s):  
Dimitris A. Pados ◽  
Michael J. Medley ◽  
Stella N. Batalama
Keyword(s):  
Antenna Array ◽  
Gaussian Noise ◽  
Spread Spectrum ◽  
Adaptive Antenna ◽  
Adaptive Antenna Array ◽  
Non Gaussian ◽  
Spread Spectrum Signals

Interference Suppression Detector for Spread Spectrum System Based on Amplitude Domain Processing

2009 ◽  
Vol 419-420 ◽  
pp. 653-656
Author(s):  
Jing Gang Wang ◽  
Jia Huan Wang
Keyword(s):  
Gaussian Noise ◽  
Spread Spectrum ◽  
Signal To Noise Ratio ◽  
Interference Suppression ◽  
Narrowband Interference ◽  
Electromagnetic Environment ◽  
Signal To Noise ◽  
Optimum Detection ◽  
Non Gaussian ◽  
Acquisition Method

Amplitude Domain Processing (ADP) is proposed in this paper for modern and complicated electromagnetic environment; the algorithm is derived from Locally Optimum Detection (LOD) theory. In non-Gaussian noise environment, ADP technique could be used in Squared-Sum Detector to obtain a new code acquisition method. The result of simulation shows that the Amplitude Domain Processing proposed by this article could eliminate the narrowband interference in Spread Spectrum Navigation Receiver automatically and improve its SNR (Signal to Noise Ratio).

STATEMENT OF THE PROBLEM ON SYNTHESIS OF OPTIMAL EVALUATION OF SIGNAL PARAMETERS IN NON-GAUSSIAN NOISE

2012 ◽  
Vol 71 (17) ◽  
pp. 1541-1555
Author(s):  
V. A. Baranov ◽  
S. V. Baranov ◽  
A. V. Nozdrachev ◽  
A. A. Rogov
Keyword(s):  
Gaussian Noise ◽  
Signal Parameters ◽  
Non Gaussian ◽  
Optimal Evaluation
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