NOMA Channel Estimation and Signal Detection using Rotational Invariant Codes and Machine Learning

This paper studies the joint channel estimation and signal detection for the uplink power domain non-orthogonal multiple access. The proposed technique performs both detection and estimation without the need of pilot symbols by using a clustering technique. To remove the effect of channel fading, we apply rotational invariant coding to assist signal detection at receiver without sending pilots. We utilize Gaussian mixture model (GMM) to automatically cluster the received signals without supervision and optimize decision boundaries to improve the bit error rate (BER) performance.