Abstract: In ultra-dense networks (UDNs), the inter-cell interference (ICI) severely limits the performance experience of cell edge users and the network throughput. The rapid development of wireless big data analysis, makes it possible to predict the future state of the channel to allocate resources, achieving considerable gain in the interference-free network. However, in the interference network, how to allocate resources and coordinate the interference with predictive information is still an open problem. This paper analyzes the difficulties and issues of designing predictive resource allocation, and proposes the solving methods. By formulating the resource allocation as a convex optimization problem, we obtain the optimal resource allocation method. Simulation results indicates that, compared with the existing methods maximizing the network throughput without prediction information, the proposed method can effectively improve users’ transmission success rate, average transmission progress and the network throughput. When the users’ data demands are high, the proposed method can provide considerable network performance gain.