  Massive MIMO is a leading technology to connect very large numbers of energy
constrained nodes, as it offers both extensive spatial multiplexing and large
array gain. A challenge resides in partitioning the many nodes into groups that
can communicate simultaneously such that the mutual interference is minimized.
We here propose node partitioning strategies that do not require full channel
state information, but rather are based on nodes' respective directional
channel properties. In our considered scenarios, these typically have a time
constant that is far larger than the coherence time of the channel. We
developed both an optimal and an approximation algorithm to partition users
based on directional channel properties, and evaluated them numerically. Our
results show that both algorithms, despite using only these directional channel
properties, achieve similar performance in terms of the minimum
signal-to-interference-plus-noise ratio for any user, compared with a reference
method using full channel knowledge. In particular, we demonstrate that
grouping nodes with related directional properties is to be avoided. We hence
realise a simple partitioning method requiring minimal information to be
collected from the nodes, and where this information typically remains stable
over a long term, thus promoting their autonomy and energy efficiency.
