Wireless communication systems can be enhanced at the link level, in medium access, and at the network level when transceivers are equipped with fullduplex 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 millimeterwave 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.