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摘要
Driven by the demand for supporting the rapidly increasing wireless traffic, the next-generation communication system, i.e., the 5G system, needs to accommodate a massive number of users and judiciously manage the interference. One promising candidate, the time reversal (TR) system, uses a large bandwidth and designs transmitting waveforms, such that the environment acts as a matched filter and the transmitted signal adds up coherently at the intended users. Therefore, the energy is focused only at the intended users with reduced interference to others. The other candidate, massive MIMO system, utilizes a large number of antennas to focus on the energy to the users and reduce the mutual interference. However, the massive number of users poses a limit on system performance due to increasing interuser interference, and the system has to make a judicial selection of transmitting users. In this paper, we propose a scheduler that maximizes the system weighted sum rate while satisfying the minimum rate requirements of the transmitting users. The optimization problem is transformed into a mixed integer quadratically constrained quadratic programming with linear time complexity. We also investigate the impact of imperfect channel information on the proposed scheduler algorithm and reveal similar channel estimation error distribution between the TR and massive MIMO system. We evaluate the performance of the proposed scheduler in different scenarios and the results show that the proposed scheduler has several desirable characteristics, including low time complexity, suitable on versatile system structure, and robustness against imperfect channel information.
- 出版日期2017-6
- 单位清华大学
