Name
Title | ||
|---|---|---|
Parallel Data Reduction Method for an Industrial Massive MIMO Detector using "Tall Skinny QR" Decomposition |
Abstract | ||
|---|---|---|
We propose an efficient approach for massive MIMO uplink detection using a tree of QR decomposition modules. The receive data is split onto the input modules and reduced during processing. The data rate does not increase while baseband data is combined and forwarded towards the root node of the tree. For the uplink baseband processing of a 128x8 MIMO system a 1.46 speedup is achieved. Our approach improves the applicability and scalability of massive MIMO for wireless industrial communication while requiring very low-latency and jitter. |
Year | Venue | Field |
|---|---|---|
2019 | WSA 2019; 23rd International ITG Workshop on Smart Antennas | Mimo detector,Computer science,Computational science,QR decomposition,Data reduction |
DocType | ISBN | Citations |
Conference | 978-3-8007-4939-3 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel Gregorek | 1 | 5 | 3.50 |
| Pascal Seidel | 2 | 0 | 1.35 |
| Steffen Paul | 3 | 142 | 40.96 |
| Jochen Rust | 4 | 32 | 12.51 |