Learned Conjugate Gradient Descent Network for Massive MIMO Detection

Understand

In this work, we consider the use of model-driven deep learning techniques for massive multiple-input multiple-output (MIMO) detection.

• Compared with conventional MIMO systems, massive MIMO promises improved spectral efficiency, coverage and range.
• Unfortunately, these benefits are coming at the cost of significantly increased computational complexity.
• To reduce the complexity of signal detection and guarantee the performance, we present a learned conjugate gradient descent network (LcgNet), which is constructed by unfolding the iterative conjugate gradient descent (CG) detector.