  Intelligent reflecting surfaces (IRSs) are being widely investigated as a
potential low-cost and energy-efficient alternative to active relays for
improving coverage in next-generation cellular networks. However, technical
constraints in the configuration of IRSs should be taken into account in the
design of scheduling solutions and the assessment of their performance. To this
end, we examine an IRS-assisted time division multiple access (TDMA) cellular
network where the reconfiguration of the IRS incurs a communication cost; thus,
we aim at limiting the number of reconfigurations over time. Along these lines,
we propose a clustering-based heuristic scheduling scheme that maximizes the
cell sum capacity, subject to a fixed number of reconfigurations within a TDMA
frame. First, the best configuration of each user equipment (UE), in terms of
joint beamforming and optimal IRS configuration, is determined using an
iterative algorithm. Then, we propose different clustering techniques to divide
the UEs into subsets sharing the same sub-optimal IRS configuration, derived
through distance- and capacity-based algorithms. Finally, UEs within the same
cluster are scheduled accordingly. We provide extensive numerical results for
different propagation scenarios, IRS sizes, and phase shifters quantization
constraints, showing the effectiveness of our approach in supporting multi-user
IRS systems with practical constraints.
