  In network MIMO cellular systems, subsets of base stations (BSs), or remote
radio heads, are connected via backhaul links to central units (CUs) that
perform joint encoding in the downlink and joint decoding in the uplink.
Focusing on the uplink, an effective solution for the communication between BSs
and the corresponding CU on the backhaul links is based on compressing and
forwarding the baseband received signal from each BS. In the presence of
ergodic fading, communicating the channel state information (CSI) from the BSs
to the CU may require a sizable part of the backhaul capacity. In a prior work,
this aspect was studied by assuming a Compress-Forward-Estimate (CFE) approach,
whereby the BSs compress the training signal and CSI estimation takes place at
the CU. In this work, instead, an Estimate-Compress-Forward (ECF) approach is
investigated, whereby the BSs perform CSI estimation and forward a compressed
version of the CSI to the CU. This choice is motivated by the information
theoretic optimality of separate estimation and compression. Various ECF
strategies are proposed that perform either separate or joint compression of
estimated CSI and received signal. Moreover, the proposed strategies are
combined with distributed source coding when considering multiple BSs.
"Semi-coherent" strategies are also proposed that do not convey any CSI or
training information on the backhaul links. Via numerical results, it is shown
that a proper design of ECF strategies based on joint received signal and
estimated CSI compression or of semi-coherent schemes leads to substantial
performance gains compared to more conventional approaches based on
non-coherent transmission or the CFE approach.
