Title :
Locally linearized Markov chain approximate models in signal detection
Author_Institution :
Dept. of Electron. Eng., Jiangnan Univ., Wuxi
Abstract :
The author presents a novel method of signal detection based on the locally linearized Markov chain approximate models of the Rayleigh process, the Rician process, and the Gaussian process. Monte Carlo simulation demonstrates that these models are superior in quality and, that the new method of detection is effective
Keywords :
Markov processes; Monte Carlo methods; signal detection; Gaussian process; Monte Carlo simulation; Rayleigh process; Rician process; locally linearized Markov chain approximate models; signal detection; Detectors; Differential equations; Diffusion processes; Frequency shift keying; Gaussian processes; Linear approximation; Narrowband; Rician channels; Signal detection; White noise;
Conference_Titel :
Aerospace and Electronics Conference, 1991. NAECON 1991., Proceedings of the IEEE 1991 National
Conference_Location :
Dayton, OH
Print_ISBN :
0-7803-0085-8
DOI :
10.1109/NAECON.1991.165741
