Millimeter-waves’ propagation characteristics create opportunities for spatio-temporal spectrum sharing in a variety of contexts, including cognitive spectrum sharing (CSS). However, CSS with omnidirectional sensing is not efficient at mmWave frequencies due to their directional transmission, as this limits secondary networks’ ability to access the spectrum. This inspired us to create an analytical approach using stochastic geometry to examine the implications of directional sensing in millimeter-wave (mmWave) CSS. We explore a cognitive network where multiple secondary transmitter-receiver pairs coexist with multiple primary transmitter-receiver pairs. The positions of the secondary transmitters are modelled using a Poisson point process with corresponding secondary receivers located around them. A threshold on directional transmission is imposed on each secondary transmitter to limit its interference at the primary receiver. We derive the medium-access-probability of a secondary user along with the fraction of the secondary transmitters active at a time-instant. To understand cognition’s feasibility, we derive the primary and secondary links’ coverage probabilities. We provide various design insights. For example, we investigate the interference-threshold’s optimal value while ensuring both link’s coverage and its dependence on various parameters. We find that directionality improves both links’ performance. Further, allowing location-aware secondary-directionality can help achieve similar coverage for all secondary links.

This work is focused on the system-level performance of a broadcast network. Since all transmitters in a broadcast network transmit identical signals, received signals from multiple transmitters can be combined to improve system performance. We develop a stochastic geometry-based analytical framework to derive the coverage of a typical receiver. We show that there may exist an optimal connectivity radius that maximizes the rate coverage. Our analysis includes the fact that users may have their individual content/advertisement preferences. We assume that there are multiple classes of users with each user class preferring a particular type of content/advertisements and the users will pay the network only when they can see content aligned with their interest. The operator may choose to transmit multiple contents simultaneously to cater to more users’ interests to increase its revenue. We present revenue models to study the impact of the number of contents on the operator revenue. We consider two scenarios for users’ distribution- one where users’ interest depends on their geographical location and the other where it doesn’t. With the help of numerical results and analysis, we show the impact of various parameters including content granularity, connectivity radius, and rate threshold and present important design insights.