Improved type-based detection of analog signals

Author

Johnson, Don H. ; Gonçalvès, Paulo A. ; Baraniuk, Richard G.

Author_Institution

Dept. of Electr. & Comput. Eng., Rice Univ., Houston, TX, USA

Volume

5

fYear

1997

fDate

21-24 Apr 1997

Firstpage

3717

Abstract

When applied to continuous-time observations, type-based detection strategies are limited by the necessity to crudely quantize each sample. To alleviate this problem, we smooth the types for both the training and observation data with a linear filter. This post-processing improves the detector performance significantly (error probabilities decrease by over a factor of three) without incurring a significant computational penalty. However this improvement depends on the amplitude distribution and on the quantizer´s characteristics

Keywords

adaptive signal detection; computational complexity; continuous time systems; quantisation (signal); signal sampling; smoothing methods; adaptive signal detection; amplitude distribution; analog signals; computational complexity; continuous time observations; detector performance; error probabilities; linear filter; observation data; postprocessing; sample quantization; smoothing method; training data; type based detection; Concatenated codes; Detectors; Error probability; Information theory; Quantization; Signal detection; Spread spectrum communication; Statistical analysis; Testing; Training data;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on

Conference_Location

Munich

ISSN

1520-6149

Print_ISBN

0-8186-7919-0

Type

conf

DOI

10.1109/ICASSP.1997.604676

Filename

604676