Title :
Improved long-range prediction with data-aided noise reduction for adaptive modulation systems
Author :
Jia, Tao ; Duel-Hallen, A. ; Hallen, Alexandra Duel
Author_Institution :
Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC
Abstract :
A novel data-aided noise reduction (DANR) method is proposed to enhance the accuracy of long-range prediction (LRP) for wireless fading channels, thereby improving the spectral efficiency (SE) of adaptive modulation (AM) system enabled by the LRP. This method includes an adaptive pilot transmission mechanism, robust noise reduction and decision-directed channel estimation. An improved practical AM scheme is used to test the proposed DANR method. Since this method maintains low pilot rates, it results in higher SE than previously proposed noise reduction (NR) techniques, which rely on oversampled pilots. These conclusions are confirmed for practical prediction ranges using the standard Jakes model and our realistic physical model.
Keywords :
adaptive modulation; channel estimation; fading channels; interference suppression; adaptive modulation systems; adaptive pilot transmission; data-aided noise reduction; decision-directed channel estimation; long-range prediction; robust noise reduction; spectral efficiency; wireless fading channels; Accuracy; Adaptive systems; Bandwidth; Channel estimation; Fading; Noise reduction; Noise robustness; Predictive models; Signal to noise ratio; Testing;
Conference_Titel :
Information Sciences and Systems, 2008. CISS 2008. 42nd Annual Conference on
Conference_Location :
Princeton, NJ
Print_ISBN :
978-1-4244-2246-3
Electronic_ISBN :
978-1-4244-2247-0
DOI :
10.1109/CISS.2008.4558694