Performance of Soft Decision Metrics and Diversity Combining with Imperfect Channel Estimation

Author

Gidlund, Mikael ; Wang, Gang

Author_Institution

Nera Networks AS, Bergen

fYear

2008

fDate

21-24 Sept. 2008

Firstpage

1

Lastpage

5

Abstract

In this paper, we derived two new decision metrics for the non-coherent maximum a posteriori (N-MAP) detector and the generalized-likelihood ratio (GLR) detector. The proposed detectors are optimally designed to make use of the available estimated channel. The obtained results show that the proposed detectors can outperform a system using classical training-based maximum-likelihood (TBML) detector. The performance is evaluated by means of computer simulations with both convolutional coded and LDPC-coded systems.

Keywords

channel estimation; diversity reception; parity check codes; LDPC-coded systems; channel estimation; classical training-based maximum-likelihood detector; computer simulations; diversity combining; generalized-likelihood ratio detector; noncoherent maximum a posteriori detector; soft decision metrics; Binary phase shift keying; Bit error rate; Channel estimation; Convolutional codes; Detectors; Diversity reception; Fading; Maximum likelihood detection; Maximum likelihood estimation; Parity check codes;

fLanguage

English

Publisher

ieee

Conference_Titel

Vehicular Technology Conference, 2008. VTC 2008-Fall. IEEE 68th

Conference_Location

Calgary, BC

ISSN

1090-3038

Print_ISBN

978-1-4244-1721-6

Electronic_ISBN

1090-3038

Type

conf

DOI

10.1109/VETECF.2008.209

Filename

4657041