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公开(公告)号:US20220140961A1
公开(公告)日:2022-05-05
申请号:US17138949
申请日:2020-12-31
Applicant: University of Science and Technology Beijing
Inventor: Haijun ZHANG , Xiangnan LIU , Keping LONG
Abstract: A bandwidth part (BWP) and power scheduling method and apparatus for indoor terahertz are provided. The BWP and power scheduling method uses an intelligent reflecting surface (IRS) and a non-orthogonal multiple access (NOMA) to compensate for a shortcoming, wherein terahertz waves are not suitable for an indoor transmission, convert an indoor environment of an IRS-assisted terahertz propagation into a channel model, and convert an optimal wireless resource scheduling in an indoor IRS-assisted terahertz system into a functional optimization design with random constraints. Policies and corresponding actions are trained by using a proximal policy optimization (PPO) to schedule a power and a BWP. An actor part generates continuous a power scheduling, and a critic part generates a discrete BWP scheduling.
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公开(公告)号:US20220417956A1
公开(公告)日:2022-12-29
申请号:US17537542
申请日:2021-11-30
Applicant: University of Science and Technology Beijing
Inventor: Haijun ZHANG , Wanqing GUAN , Dong WANG , Tongwei LU , Xiangming WEN , Keping LONG
Abstract: An Artificial Intelligence (AI) engine-supporting downlink radio resource scheduling method and apparatus are provided. The AI engine-supporting downlink radio resource scheduling method includes: constructing an AI engine, establishing a Socket connection between an AI engine and an Open Air Interface (OAI) system, and configuring the AI engine into an OAI running environment to utilize the AI engine to replace a Round-Robin scheduling algorithm and a fair Round-Robin scheduling algorithm adopted by a Long Term Evolution (LTE) at a Media Access Control (MAC) layer in the OAI system for resource scheduling to take over a downlink radio resource scheduling process; sending scheduling information to the AI engine through Socket during the downlink radio resource scheduling process of the OAI system; and utilizing the AI engine to carry out resource allocation according to the scheduling information, and returning a resource allocation result to the OAI system.
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