Name
Abstract | ||
|---|---|---|
Motivated by large linear inverse problems where the complexity of the Maximum A-Posteriori (MAP) detector grows exponentially with system dimensions, e.g., large MIMO, we introduce a method to relax a discrete MAP problem into a continuous one. The relaxation is inspired by recent ML research and offers many favorable properties reflecting its quality. Hereby, we derive an iterative detection algorithm based on gradient descent optimization: Concrete MAP Detection (CMD). We show numerical results of application in large MIMO systems that demonstrate superior performance w.r.t. all considered State of the Art approaches. |
Year | Venue | DocType |
|---|---|---|
2020 | WSA 2020; 24th International ITG Workshop on Smart Antennas | Conference |
ISBN | Citations | PageRank |
978-3-8007-5200-3 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Edgar Beck | 1 | 0 | 0.68 |
| Carsten Bockelmann | 2 | 279 | 24.67 |
| Armin Dekorsy | 3 | 513 | 57.91 |