structure allows for customized slot design, for examples, adding a longer or shorter cyclic prefix, changing the data frame length, or providing extra guard space. Another innovation is spectrum sharing. In contrast to static database-aided spectrum sharing, which detects secondary users' interference and only allows them to access bands in an opportunistic way, current spectrum sharing is more dynamic, enabled by advanced machine learning-based approach, hence is more efficient and accurate. 1.2.2 Mobile Edge Computing (MEC) Due to the size, battery, and cost limitations, mobile devices can experience performance bottleneck when computation-intensive tasks are added. More than one decade ago, people solved this problem by introducing the concept of cloud computing. Mobile devices do not perform large-scale computation locally; instead, they send these tasks to remote servers for faster and more secure processing, storage, and sharing. The centralized nature of cloud-based computing can reduce the expenditure cost while providing easier deployment process. However, cloud servers may be located in remote areas, which causes inevitably longer end-to-end transmission and processing delay. MEC is a new alternative paradigm for the upcoming 5G systems. Instead of transmitting data to the remote servers for processing, MEC provides certain computation capacities locally, for example within the base station in the wireless cellular networks. This paradigm shift can effectively reduce long backhaul latency and energy consumption, as well as support a more flexible infrastructure in a cost-effective way. MEC has attracted extensive research interests recently, not only in the architectural level, but also in specific tasks such as cooperative computation offloading. Computation offloading, which leverages the powerful MEC servers in proximity and sends the computation-intensive tasks for further processing, is a desirable scheme to overcome the physical limitations of user devices (Figure 1.3). We see this paradigm shift