For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
Reduced-Complexity Near-ML Detector for a Coded DSTTD-OFDM System
Hyounkuk KIM Hyuncheol PARK
IEICE TRANSACTIONS on Communications
Publication Date: 2008/11/01
Online ISSN: 1745-1345
Print ISSN: 0916-8516
Type of Manuscript: LETTER
Category: Wireless Communication Technologies
double space-time transmit diversity (DSTTD), maximum-likelihood (ML) detector,
Full Text: PDF(134.8KB)>>
This letter introduces an efficient near-maximum likelihood (ML) detector for a coded double space-time transmit diversity-orthogonal frequency division multiplexing (DSTTD-OFDM) system. The proposed near-ML detector constructs a candidate vector set through a relaxed minimization method. It reduces computational loads from O(2|A|2) to O(|A|2), where |A| is the modulation order. Numerical results indicate that the proposed near-ML detector provides both almost ML performance and considerable complexity savings.