  Cell-Free Massive MIMO (CF mMIMO) has emerged as a potential enabler for
future networks. It has been shown that these networks are much more
energy-efficient than classical cellular systems when they are serving users at
peak capacity. However, these CF mMIMO networks are designed for peak traffic
loads, and when this is not the case, they are significantly over-dimensioned
and not at all energy efficient. To this end, Adaptive Access Point (AP) ON/OFF
Switching (ASO) strategies have been developed to save energy when the network
is not at peak traffic loads by putting unnecessary APs to sleep.
Unfortunately, the existing strategies rely on measuring channel state
information between every user and every access point, resulting in significant
measurement energy consumption overheads. Furthermore, the current state-of-art
approach has a computational complexity that scales exponentially with the
number of APs. In this work, we present a novel convex feasibility testing
method that allows checking per-user Quality-of-Service (QoS) requirements
without necessarily considering all possible access point activations. We then
propose an iterative algorithm for activating access points until all users'
requirements are fulfilled. We show that our method has comparable performance
to the optimal solution whilst avoiding solving costly mixed-integer problems
and measuring channel state information on only a limited subset of APs.
