| Paper ID | MLSP-8.6 |
| Paper Title |
LEARNING OPTIMAL LATTICE CODES FOR MIMO COMMUNICATIONS |
| Authors |
Laia Amorós, Mikko Pitkänen, Aalto University, Finland |
| Session | MLSP-8: Learning |
| Location | Gather.Town |
| Session Time: | Tuesday, 08 June, 16:30 - 17:15 |
| Presentation Time: | Tuesday, 08 June, 16:30 - 17:15 |
| Presentation |
Poster
|
| Topic |
Machine Learning for Signal Processing: [MLR-REI] Reinforcement learning |
| IEEE Xplore Open Preview |
Click here to view in IEEE Xplore |
| Virtual Presentation |
Click here to watch in the Virtual Conference |
| Abstract |
We propose a novel reinforcement learning approach to learning lattice codes for MIMO channels. We use the block error rate as a loss function to be minimized and compare the learnt lattices with those obtained from algebraic design methods for different SNR ranges. Our results indicate that our learnt lattices achieve close to optimal performance in some cases. |
