  Multiuser multiple-input multiple-output (MIMO) systems are a prime candidate
for use in massive connection density in machine-type communication (MTC)
networks. One of the key challenges of MTC networks is to obtain accurate
channel state information (CSI) at the access point (AP) so that the spectral
efficiency can be improved by enabling enhanced MIMO techniques. However,
current communication mechanisms relying upon frequency division duplexing
(FDD) might not fully support an enormous number of devices due to the
rate-constrained limited feedback and the time-consuming scheduling
architectures. In this paper, we propose a user cooperation-based limited
feedback strategy to support high connection density in massive MTC networks.
In the proposed algorithm, two close-in users share the quantized version of
channel information in order to improve channel feedback accuracy. The
cooperation process is performed without any transmitter interventions (i.e.,
in a grant-free manner) to satisfy the low-latency requirement that is vital
for MTC services. Moreover, based on the sum-rate throughput analysis, we
develop an adaptive cooperation algorithm with a view to
activating/deactivating the user cooperation mode according to channel and
network conditions.
