Title :
Compressive sampling based multiple symbol differential detection for UWB IR signals
Author :
Gishkori, Shahzad ; Leus, Geert ; Lottici, Vincenzo
Author_Institution :
Fac. of EEMCS, Delft Univ. of Technol., Delft, Netherlands
Abstract :
In this paper, a compressive sampling (CS) based multiple symbol differential detector is proposed, using the principle of a generalized likelihood ratio test (GLRT). The proposed detector works on the compressed samples directly, thereby avoiding the reconstruction step and thus resulting in a reduced implementation complexity along with a reduced sampling rate (much below the Nyquist rate). We also propose the compressed sphere decoder (CSD) to resolve the detection of multiple symbols. Our proposed detector is valid for scenarios where the measurement matrices are the same as well as where they are different for each received symbol.
Keywords :
matrix algebra; signal detection; signal reconstruction; signal sampling; ultra wideband technology; CS based multiple symbol differential detector; CSD; GLRT; Nyquist rate; UWB IR signals; compressed samples; compressed sphere decoder; compressive sampling; generalized likelihood ratio test; implementation complexity; measurement matrices; multiple symbol detection; multiple symbol differential detection; reconstruction step; reduced sampling rate; Bit error rate; Correlation; Cost function; Decoding; Detectors; Ultra wideband technology; Vectors; compressive sampling; multiple symbol differential detection; ultra-wideband;
Conference_Titel :
Ultra-Wideband (ICUWB), 2012 IEEE International Conference on
Conference_Location :
Syracuse, NY
Print_ISBN :
978-1-4577-2031-4
DOI :
10.1109/ICUWB.2012.6340501