Joint antenna allocation and rate adaption for video transmission in massive MIMO systems

Massive multi-input-multi-output (MIMO) networks could achieve higher data transmission rate benefited from the advantages of space diversity and multiplexing. In recent years, large amounts of research about different service adopted in massive MIMO network have been proposed. In this paper, we investigate instant video communication services requested by users in massive MIMO networks. After defining a detailed system model for video streaming in massive MIMO networks, we jointly consider the problem of antenna allocation and time-average video streaming scheduling. Since the problem is NP-hard, we reformulate it by decomposing the problem into two sub-problems that are antennas allocation and video packets queuing so that some fast common algorithms can be employed. To solve the two sub-problems, Enhanced Hungarian algorithm (EHA) and Enhanced Kuhn-Munkras algorithm (EKM) are designed for antenna allocation, and High Quality Fair Queuing (HQFQ) algorithm is proposed for video streaming scheduling. Consequently, numerical solution can be calculated in the time scale of real-life video streaming sessions. Various results demonstrate that our approach performs well in balance of quality of service and fairness to video streaming users.