  We investigate the energy efficiency performance of cell-free Massive
multiple-input multiple-output (MIMO), where the access points (APs) are
connected to a central processing unit (CPU) via limited-capacity links. Thanks
to the distributed maximum ratio combining (MRC) weighting at the APs, we
propose that only the quantized version of the weighted signals are sent back
to the CPU. Considering the effects of channel estimation errors and using the
Bussgang theorem to model the quantization errors, an energy efficiency
maximization problem is formulated with per-user power and backhaul capacity
constraints as well as with throughput requirement constraints. To handle this
non-convex optimization problem, we decompose the original problem into two
sub-problems and exploit a successive convex approximation (SCA) to solve
original energy efficiency maximization problem. Numerical results confirm the
superiority of the proposed optimization scheme.
