Abstract
In this work we consider the user scheduling problem in the massive multiple-input multiple-output (MIMO) wireless multicast system with heterogeneous structures. The dynamic programming (DP) method and Markov decision process (MDP) model is utilized to describe the system behavior. We use asymptotic results for massive MIMO multicast beamforming to estimate the system capacity for the MDP model. The value iteration (VI) method is adopted to solve the MDP problems. The proposed model can enhance the system performance by solving the optimal MDP policy for user scheduling in an off-line manner with maximized average reward. The numerical results show the behavior of the algorithm and evaluate its performance.
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Acknowledgement
This work is funded by project 61471066 supported by National Natural Science Foundation of China (NSFC).
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Zhang, X., Sun, S. (2018). Dynamic User Scheduling Algorithms for Massive MIMO Multicast System. In: Sun, S., Chen, N., Tian, T. (eds) Signal and Information Processing, Networking and Computers. ICSINC 2017. Lecture Notes in Electrical Engineering, vol 473. Springer, Singapore. https://doi.org/10.1007/978-981-10-7521-6_15
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DOI: https://doi.org/10.1007/978-981-10-7521-6_15
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