Huawei Technologies Co., Limited

Jini Wen

Xin Tang

Kun Wang

Xia Xiong

This application provides a signal transmission method and apparatus. The method includes: A collaboration device receives a synchronization trigger frame delivered by a central device; the collaboration device obtains information about a time domain offset and/or information about a frequency domain offset; and the collaboration device sends a signal based on the synchronization trigger frame and the information about the time domain offset and/or the information about the frequency domain offset by using a corresponding time domain resource and a corresponding frequency domain resource. In this way, a plurality of collaboration devices send different time domain resources and/or frequency domain resources to a same terminal, and an interfering signal in channel estimation can be removed. This improves precision of the channel estimation and noise estimation at a receiving end, and improves demodulation performance at the receiving end and entire-network throughput.

Frequency domain offset method and apparatus

Embodiments of the present invention provide a joint scheduling method and apparatus. The method of the present invention is as follows: judging whether a CoMP user equipment exists in user equipments that wait to be scheduled in a sector that participates in joint scheduling; scheduling, if a CoMP user equipment exists in user equipments that wait to be scheduled, the CoMP user equipment that waits to be scheduled and assigning CoMP frequency band resources to the scheduled CoMP user equipment according to a size of frequency band resources required by the scheduled CoMP user equipment, where the CoMP frequency band resources are partial frequency band resources allocated from frequency band resources of the sector that participates in joint scheduling and are preferentially used by the CoMP user equipment. Embodiments of the present invention mainly apply to a joint scheduling process in a wireless communications system.

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Shanghai, China

Jini Wen