  Wireless communication systems can be enhanced at the link level, in medium
access, and at the network level when transceivers are equipped with
full-duplex capability: the transformative ability to simultaneously transmit
and receive over the same frequency spectrum. Effective methods to cancel
self-interference are required to facilitate full-duplex operation, which we
overview herein in the context of traditional radios, along with those in
next-generation wireless networks. We highlight advances in self-interference
cancellation that leverage machine learning, and we summarize key
considerations and recent progress in full-duplex millimeter-wave systems and
their application in integrated access and backhaul. We present example design
problems and noteworthy findings from recent experimental research to introduce
and motivate the advancement of full-duplex millimeter-wave systems. We
conclude this chapter by forecasting the future of full-duplex and outlining
important research directions that warrant further study.
