Name
Abstract | ||
|---|---|---|
In this paper, we propose a near maximum likelihood (ML) scheme for the decoding of multiple input multiple output systems. Based on the metric-first search method and by employing Schnorr-Euchner enumeration and branch length thresholds, the proposed scheme provides a higher efficiency than other conventional near ML decoding schemes. From simulation results, it is confirmed that the proposed scheme has lower computational complexity than other near ML decoders while maintaining the bit error rate very close to the ML performance. The proposed scheme in addition possesses the capability of allowing flexible tradeoffs between the computational complexity and BER performance. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1109/VETECF.2008.95 | VTC Fall |
Keywords | Field | DocType |
mimo signal decoding,schnorr-euchner enumeration,maximum likelihood estimation,multiple input multiple output systems,communication complexity,metric-first scheme,search problems,metric-first search method,computational complexity,mimo communication,branch length threshold,ml decoding scheme,decoding,near maximum likelihood scheme,bit error rate,mimo,matrix decomposition,lattices | Mathematical optimization,Lattice (order),Computer science,Enumeration,Matrix decomposition,Algorithm,MIMO,Communication complexity,Electronic engineering,Decoding methods,Bit error rate,Computational complexity theory | Conference |
ISSN | ISBN | Citations |
1090-3038 E-ISBN : 978-1-4244-1722-3 | 978-1-4244-1722-3 | 0 |
PageRank | References | Authors |
0.34 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seong Ro Lee | 1 | 152 | 26.32 |
| Taehun An | 2 | 8 | 2.51 |
| Hyun Gu Kang | 3 | 43 | 4.39 |
| Iickho Song | 4 | 558 | 85.31 |