Abstract
Millimeter-wave (mmWave) communication is a promising technology to cope with the expected exponential increase in
data traffic in 5G networks. mmWave networks typically require a very dense deployment of mmWave base stations
(mmBS). To reduce cost and increase flexibility, wireless backhauling is needed to connect the mmBSs. The
characteristics of mmWave communication, and specifically its high directionality, imply new requirements for
efficient routing and scheduling paradigms. We propose an efficient scheduling method, so-called schedule-oriented
optimization, based on matching theory that optimizes QoS metrics jointly with routing. It is capable of solving any
scheduling problem that can be formulated as a linear program whose variables are link times and QoS metrics. As an
example of the schedule-oriented optimization, we show the optimal solution of the maximum throughput fair scheduling
(MTFS). Practically, the optimal scheduling can be obtained even for networks with over 200 mmBSs. To further increase
the runtime performance, we propose an efficient edge-coloring based approximation algorithm with provable performance
bound. It achieves over 80% of the optimal max-min throughput and runs 5 to 100 times faster than the optimal
algorithm in practice. Finally, we extend the optimal and approximation algorithms for the cases of multi-RF-chain
mmBSs and integrated backhaul and access networks.