  Fronthaul quantization causes a significant distortion in cell-free massive
MIMO networks. Due to the limited capacity of fronthaul links, information
exchange among access points (APs) must be quantized significantly.
Furthermore, the complexity of the multiplication operation in the base-band
processing unit increases with the number of bits of the operands. Thus,
quantizing the APs' signal vector reduces the complexity of signal estimation
in the base-band processing unit. Most recent works consider the direct
quantization of the received signal vectors at each AP without any
pre-processing. However, the signal vectors received at different APs are
correlated mutually (inter-AP correlation) and also have correlated dimensions
(intra-AP correlation). Hence, cooperative quantization of APs fronthaul can
help to efficiently use the quantization bits at each AP and further reduce the
distortion imposed on the quantized vector at the APs. This paper considers a
daisy chain fronthaul and three different processing sequences at each AP. We
show that 1) de-correlating the received signal vector at each AP from the
corresponding vectors of the previous APs (inter-AP de-correlation) and 2)
de-correlating the dimensions of the received signal vector at each AP
(intra-AP de-correlation) before quantization helps to use the quantization
bits at each AP more efficiently than directly quantizing the received signal
vector without any pre-processing and consequently, improves the bit error rate
(BER) and normalized mean square error (NMSE) of users signal estimation.
