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| 1 | Deep learning based user scheduling for massive MIMO downlink system显示文摘In this paper,we investigate a user scheduling algorithm for massive multiple-input multipleoutput(MIMO)systems over more general correlated Rician fading channels.To achieve low latency and high throughput,a new user scheduling algorithm based on deep learning(DL)is proposed,which exploits only statistical channel state information.The proposed scheduling network is trained to grasp the mapping from the statistical signal and interference pattern to the user scheduling decision through supervised learning.It can predict the optimal scheduling scheme from statistical CSI without iterative calculation after offline training.Simulation results demonstrate the superior performance of the proposed algorithm in terms of calculation time,and it achieves almost the same throughput as the optimal scheduling algorithm which is obtained through exhaustive search.Furthermore,with the normalization of the input data,the proposed scheduling network is robust to the change of the channel environment and the number of transmit antennas. | Xiaoxiang YU Jiajia GUO Xiao LI Shi JIN | 2021 | Science China(Information Sciences)2021，64，8： | 1 |
| 2 | Coordinated multicast and unicast transmission in V2V underlay massive MIMO显示文摘This paper investigates coordinated multicast and unicast transmission for vehicle-to-vehicle(V2 V) underlay massive multiple-input multiple-output(MIMO). First, the achievable ergodic multicast rate for the cellular link and the achievable ergodic unicast rate for all the V2 V links are summed with weight to formulate the rate optimization problem, with the assumption that the statistical channel state information(CSI) is known at the base station and the transmitters of the V2 V communication pairs. We then derive the optimal transmitting directions in closed-form for the cellular link and all the V2 V links,respectively, which converts the original optimal problem to a simpler power allocation problem in the beam domain. Via invoking the concave-convex procedure, an efficient iterative algorithm with guaranteed convergence is proposed for the power allocation problem. Furthermore, we replace the objectives which contain high-complex expectation operations with their deterministic equivalents in each iteration of the proposed algorithm to achieve lower algorithm complexity. Simulation results show the fast convergence speed of the proposed power allocation algorithm and the significant performance gains of the proposed transmission design for V2 V underlay massive MIMO. | Xinxin NIU Li YOU Xiqi GAO | 2022 | Science China(Information Sciences)2022，65，3： | 0 |
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