Name
Abstract | ||
|---|---|---|
Fixed-complexity sphere decoder (FSD), which consists of ordering stage and tree-search stage, achieves a quasiML performance while requiring a fixed computational effort independent of the noise power and channel conditioning. Nevertheless, it requires a specific signal ordering using the VBLAST algorithm which has a high complexity due to the iterative pseudo-inversion of the channel matrix. In this paper, we propose two schemes to reduce the complexity of FSD algorithm in the ordering and tree-search stages, respectively, while achieving quasi-ML performance. In the ordering stage, we propose QR-decomposition-based FSD signal ordering (FSDSQRD) that requires only a few number of additional complex flops compared to the unsorted QRD. In the tree-search stage, we introduce a threshold-based complexity reduction approach for FSD depending on the reliability of the signal with the lowest received SNR. Numerical results show that in a 4Ã4 system, the proposed FSD-SQRD requires only 17.2% of the computational efforts required by a reduced-complexity VBLAST approach. Moreover, using 16-QAM, simulation results show that when the proposed threshold-based approach is employed, FSD requires only 69.5% of its full complexity. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/VETECF.2009.5378999 | VTC Fall |
Keywords | Field | DocType |
threshold-based complexity reduction approach,vblast algorithm,maximum likelihood decoding,fixed-complexity sphere decoder,matrix algebra,iterative channel matrix pseudoinversion,16-qam,tree-search stages,signal reliability,numerical results,computational complexity,qr-decomposition-based fsd signal ordering,quadrature amplitude modulation,channel conditioning,quasiml performance,signal detection,iterative methods,modulation,signal to noise ratio,complexity reduction,bit error rate,qr decomposition,16 qam,mimo | Quadrature amplitude modulation,Noise power,Iterative method,Computer science,Signal-to-noise ratio,MIMO,Electronic engineering,Reduction (complexity),Computational complexity theory,Bit error rate | Conference |
ISSN | ISBN | Citations |
1090-3038 E-ISBN : 978-1-4244-2515-0 | 978-1-4244-2515-0 | 3 |
PageRank | References | Authors |
0.40 | 6 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Manar Mohaisen | 1 | 97 | 28.83 |
| Kyunghi Chang | 2 | 202 | 41.07 |