Learning Optimal Codes for MIMO Communications

Laia Amoros Carafi, Mikko Pitkänen

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


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.
Original languageEnglish
Title of host publication2021 IEEE International Conference on Acoustics, Speech and Signal Processing
Number of pages5
Publication statusAccepted/In press - 30 Jan 2021
MoE publication typeA4 Article in a conference publication

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