A low-complexity tree search detection algorithm for superposition modulation

Author

Hao, Dapeng ; Hoeher, Peter Adam

Author_Institution

Fac. of Eng., Univ. of Kiel, Kiel, Germany

fYear

2012

Firstpage

145

Lastpage

149

Abstract

We present a novel soft-output detection algorithm for superposition modulation. Using a sequential tree search approach with Gaussian approximation (TS-GA) on the unknown layers, the most significant symbols can be identified and used to approximate the marginal posterior probabilities. The detector has low and fixed computational complexity. Simulation results demonstrate that the optimal a posteriori probability (APP) performance can be approached with a small number of symbol candidates.

Keywords

Gaussian processes; approximation theory; communication complexity; modulation; probability; signal detection; tree searching; Gaussian approximation; TS-GA; a posteriori probability; fixed computational complexity; low-complexity tree search detection algorithm; marginal posterior probability approximation; optimal APP performance; sequential tree search approach; soft-output detection algorithm; superposition modulation; symbol identification; Decoding; Detectors; Gaussian approximation; Iterative decoding; Measurement; Modulation; Receivers; Gaussian approximation; M-algorithm; Superposition modulation (SM); detection; tree search;

fLanguage

English

Publisher

ieee

Conference_Titel

Turbo Codes and Iterative Information Processing (ISTC), 2012 7th International Symposium on

Conference_Location

Gothenburg

ISSN

2165-4700

Print_ISBN

978-1-4577-2114-4

Electronic_ISBN

2165-4700

Type

conf

DOI

10.1109/ISTC.2012.6325216

Filename

6325216