Invention Grant
US09537556B2 Systems and methods for optimized beamforming and compression for uplink MIMO cloud radio access networks
有权
用于上行链路MIMO云无线电接入网络的优化波束成形和压缩的系统和方法
- Patent Title: Systems and methods for optimized beamforming and compression for uplink MIMO cloud radio access networks
- Patent Title (中): 用于上行链路MIMO云无线电接入网络的优化波束成形和压缩的系统和方法
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Application No.: US14794684Application Date: 2015-07-08
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Publication No.: US09537556B2Publication Date: 2017-01-03
- Inventor: Yuhan Zhou , Wei Yu , Mohammadhadi Baligh
- Applicant: Huawei Technologies Canada Co., Ltd. , The Governing Council of the University of Toronto
- Applicant Address: CA Kanata, ON CA Toronto
- Assignee: Huawei Technologies Canada Co., Ltd.,The Governing Council of the University of Toronto
- Current Assignee: Huawei Technologies Canada Co., Ltd.,The Governing Council of the University of Toronto
- Current Assignee Address: CA Kanata, ON CA Toronto
- Agency: Slater Matsil, LLP
- Main IPC: H04B7/02
- IPC: H04B7/02 ; H04B7/06 ; H04B7/04 ; H04W84/04

Abstract:
System and method embodiments are provided to optimize uplink multiple-input-multiple-output (MIMO) beamforming for uplink and compression for fronthaul links transmission in cloud radio access network (C-RANs). In an embodiment, cloud-computing based central processor (CP) obtains channel state information for a mobile device (MD) being served by a plurality of access points (APs) in a C-RAN, and generates a channel gain matrix in accordance with the channel state information. A weighted sum-rate maximization model is then established using the channel gain matrix in accordance with power constraints of transmission from the MD to the APs and capacity constraints of fronthaul links connecting the APs to the CP. The CP calculates a transmit beamforming vector for the MD and a quantization noise covariance matrix for the APs jointly by applying a weighted minimum-mean-square-error successive convex approximation algorithm, or separately by applying an approximation algorithm, to solve the weighted sum-rate maximization model.
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