Learning to Detect

Understand

In this paper we consider Multiple-Input-Multiple-Output (MIMO) detection using deep neural networks.

• We introduce two different deep architectures: a standard fully connected multi-layer network, and a Detection Network (DetNet) which is specifically designed for the task.
• The structure of DetNet is obtained by unfolding the iterations of a projected gradient descent algorithm into a network.
• We compare the accuracy and runtime complexity of the purposed approaches and achieve state-of-the-art performance while maintaining low computational requirements.