Name
Abstract | ||
|---|---|---|
We present an algorithm that efficiently performs blind decoding of MIMO signals. That is, given no CSI at either the transmitter or receiver, our algorithm takes a block of samples and returns an estimate of the underlying data symbols. In prior work, the problem of blind decoding was formulated as a non-convex optimization problem. In this work, we present an algorithm that efficiently solves this non-convex problem. This algorithm leverages concepts of linear and mixed-integer linear programming. Empirically, we show that our technique has an error performance close to that of zero-forcing with perfect CSI at the receiver. Initial estimates of the runtime of the algorithm presented in this work suggest that the real-time blind decoding of MIMO signals is possible for even modest sized MIMO systems. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/ACSSC.2018.8645173 | 2018 52nd Asilomar Conference on Signals, Systems, and Computers |
Keywords | Field | DocType |
MIMO communication,Maximum likelihood decoding,Receivers,Optimization,Wireless communication,Signal to noise ratio | Transmitter,Wireless,Vertex (geometry),Computer science,Signal-to-noise ratio,Algorithm,MIMO,Electronic engineering,Linear programming,Decoding methods,Optimization problem | Conference |
ISSN | ISBN | Citations |
1058-6393 | 978-1-5386-9218-9 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jonathan Perlstein | 1 | 0 | 0.34 |
| Thomas R. Dean | 2 | 11 | 3.45 |
| Mary Wootters | 3 | 172 | 25.99 |
| Andrea Goldsmith | 4 | 0 | 0.34 |