Interference management and control in the cognitive radio network (CRN) is a necessity if the activities of primary users must be protected from excessive interference resulting from the activities of neighboring users. Hence, interference experienced in wireless communication networks has earlier been characterized using the traditional grid model. Such models, however, lead to non-tractable analyses, which often require unrealistic assumptions, leading to inaccurate results. These limitations of the traditional grid models mean that the adoption of stochastic geometry (SG) continues to receive a lot of attention owing to its ability to capture the distribution of users properly, while producing scalable and tractable analyses for various performance metrics of interest. Despite the importance of CRN to next-generation networks, no survey of the existing literature has been done when it comes to SG-based interference management and control in the domain of CRN. Such a survey is, however, necessary to provide the current state of the art as well as future directions. This paper hence presents a comprehensive survey related to the use of SG to effect interference management and control in CRN. We show that most of the existing approaches in CRN failed to capture the relationship between the spatial location of users and temporal traffic dynamics and are only restricted to interference modeling among non-mobile users with full buffers. This survey hence encourages further research in this area. Finally, this paper provides open problems and future directions to aid in finding more solutions to achieve efficient and effective usage of the scarce spectral resources for wireless communications.The SENTECH Chair in Broadband Wireless Multimedia Communications (BWMC), Department of Electrical, Electronic and Computer Engineering, University of Pretoria, South Africa.http://www.elsevier.com/locate/comcomhj2022Electrical, Electronic and Computer Engineerin
