  In next-generation networks, cells will be replaced by a collection of
points-of-access (PoAs), with overlapping coverage areas and/or different
technologies. Along with a promise for greater performance and flexibility,
this creates further pressure on network management algorithms, which must make
joint decisions on (i) PoA-to-user association and (ii) PoA management. We
solve this challenging problem through an efficient and effective solution
concept called Cluster-then-Match (CtM). Importantly, CtM makes human-centric
decisions, where pure network performance is balanced against metrics like
energy consumption and electromagnetic field exposure, which concern all humans
in the network area -- including those who are not network users. Through our
performance evaluation, which leverages detailed models for EMF exposure
estimation and standard-specified signal propagation models, we show that CtM
outperforms state-of-the-art network management schemes, including those
utilizing machine learning, reducing energy consumption by over 80%.
