  One main goal of 5G-and-beyond systems is to simultaneously serve many users,
each having a requested spectral efficiency (SE), in an energy-efficient way.
The network capacity cannot always satisfy all the SE requirements, for
example, when some users have bad channel conditions, especially happening in a
cellular topology, and therefore congestion can happen. By considering both the
pilot and data powers in the uplink transmission as optimization variables,
this paper formulates and solves an energy-efficiency problem for cellular
Massive MIMO (Multiple Input Multiple Output) systems that can handle the
congestion issue. New algorithms based on the alternating optimization approach
are proposed to obtain a fixed-point solution. Numerical results manifest that
the proposed algorithms can provide the demanded SEs to many users even when
the congestion happens.
