Video streaming,especially hypertext transfer protocol based(HTTP) adaptive streaming(HAS) of video,has been expected to be a dominant application over mobile networks in the near future,which brings huge challenge for the mobile networks.Although some works have been done for video streaming delivery in heterogeneous cellular networks,most of them focus on the video streaming scheduling or the caching strategy design.The problem of joint user association and rate allocation to maximize the system utility while satisfying the requirement of the quality of experience of users is largely ignored.In this paper,the problem of joint user association and rate allocation for HTTP adaptive streaming in heterogeneous cellular networks is studied,we model the optimization problem as a mixed integer programming problem.And to reduce the computational complexity,an optimal rate allocation using the Lagrangian dual method under the assumption of knowing user association for BSs is first solved.Then we use the many-to-one matching model to analyze the user association problem,and the joint user association and rate allocation based on the distributed greedy matching algorithm is proposed.Finally,extensive simulation results are illustrated to demonstrate the performance of the proposed scheme. Video streaming, especially hypertext transfer protocol based (HTTP) adaptive streaming (HAS) of video, has been expected to be a dominant application over mobile networks in the near future, which brings huge challenges for the mobile networks. Though some works have been done for video streaming delivery in heterogeneous cellular networks, most of them focus on the video streaming scheduling or the caching strategy design.The problem of joint user association and rate allocation to maximize the system utility while satisfying the requirement of the quality of experience of users major ignored. In this paper, the problem of joint user association and rate allocation for HTTP adaptive streaming in heterogeneous cellular networks is studied, we model the optimization problem as a mixed integer programming problem. And to reduce the computational complexity, an optimal rate of allocation using the Lagrangian dual method under the assumption of knowing user association for BSs is first solved we use the many-to-one matching model to analyze the user association problem, and the joint user association and rate allocation based on the distributed greedy matching algorithm is proposed. Finally, extensive simulation results are illustrated to demonstrate the performance of the proposed scheme .