  Link-adaptation (LA) is one of the most important aspects of wireless
communications where the modulation and coding scheme (MCS) used by the
transmitter is adapted to the channel conditions in order to meet a certain
target error-rate. In a single-user SISO (SU-SISO) system with out-of-cell
interference, LA is performed by computing the post-equalization
signal-to-interference-noise ratio (SINR) at the receiver. The same technique
can be employed in multi-user MIMO (MU-MIMO) receivers that use linear
detectors. Another important use of post-equalization SINR is for physical
layer (PHY) abstraction, where several PHY blocks like the channel encoder, the
detector, and the channel decoder are replaced by an abstraction model in order
to speed up system-level simulations. However, for MU-MIMO systems with
non-linear receivers, there is no known equivalent of post-equalization SINR
which makes both LA and PHY abstraction extremely challenging. This important
issue is addressed in this two-part paper. In this part, a metric called the
bit-metric decoding rate (BMDR) of a detector, which is the proposed equivalent
of post-equalization SINR, is presented. Since BMDR does not have a closed form
expression that would enable its instantaneous calculation, a machine-learning
approach to predict it is presented along with extensive simulation results.
