Name
Abstract | ||
|---|---|---|
A multi-stage blind clustering algorithm is pro- posed for equalisation of multi-level quadrature amplitute modulation (M-$AM) channels. A hierarchical decomposi- tion divides the task of equalising a high-order QAM chan- nel into much simpler sub-tasks. Each sub-task can be ac- complished fast and reliably using a blind clustering algo- rithm derived originally for 4-QAM signals. The constant modulus algorithm (CMA) is used as a benchmark to assess this multi-stage blind equaliser. It is demonstrated that the new blind algorithm achieves much faster convergence and is very robust when input symbols are not sufficiently white. This multi-stage clustering equaliser only requires slightly more computations than the CMA and, like the latter, its computational complexity does not increase as the levels of digital symbols increase. |
Year | DOI | Venue |
|---|---|---|
1995 | 10.1109/26.380093 | IEEE Transactions on Communications |
Keywords | Field | DocType |
adaptive equalisers,computational complexity,digital communication,hierarchical systems,pattern recognition,quadrature amplitude modulation,telecommunication channels,blind clustering algorithm,computational complexity,constant modulus algorithm,convergence,digital symbols,hierarchical decomposition,high-order QAM channel,input symbols,multi-level quadrature amplitude modulation channel,multi-stage blind clustering equaliser,sub-task | Quadrature modulation,Signal processing,Quadrature amplitude modulation,Equalization (audio),Control theory,Computer science,QAM,Electronic engineering,Cluster analysis,Equaliser,Computational complexity theory | Journal |
Volume | Issue | ISSN |
43 | 2 | 0090-6778 |
Citations | PageRank | References |
16 | 1.05 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sheng Chen | 1 | 1813 | 230.12 |
| Stephen McLaughlin | 2 | 168 | 16.62 |
| Peter M. Grant | 3 | 1994 | 278.19 |
| Bernard Mulgrew | 4 | 724 | 85.23 |