Light-wireless signal mutually assisting beamforming method and apparatus

Abstract

In an existing millimeter wave MIMO system, beamforming transmitting and receiving usually require estimation of space parameters of a channel which a radio wave passes. When antennas of a receiving party and a transmitting party or one of the two parties are increased, and the receiving party and the transmitting party have strong mobility, the overhead of channel measurement and feedback is very high if high accuracy beam tracking is performed, consequently, the system capacity and resource allocation flexibility are undermined, and signal processing is more complex. To solve the above problems, the present invention provides a light-wireless signal mutually assisting beamforming method and apparatus. A camera apparatus is controlled to capture a position of a potential user or change of the position and a gesture, so as to perform beamforming or beam change and gain adjustment, so that the beamforming performance is improved. According to the method and apparatus, conversely, the wireless signal is used for assisting the light signal to perform beam alignment.

Description

[0001] 1. Technical field [0002] The present invention relates to the field of communication technology, in particular to a beamforming method and device in wireless communication. [0003] 2. Technical background [0004] Existing beamforming schemes, whether transmit beamforming or receive beamforming, typically require estimation of the spatial parameters of the channel experienced by the radio waves. Without loss of generality, taking the communication between the base station and the mobile station in cellular mobile communication as an example, the downlink beamforming either requires the mobile station to measure the reference signal of the base station and then feedback it, or uses channel reciprocity to measure the emission of the mobile station by the base station. Then estimate the downlink channel. The uplink beamforming also has a similar solution. Either way, it is necessary to send overhead information to assist the receiving side in estimating channel spatia...

AI Technical Summary

Problems solved by technology

[0006] 1) With the increase of the number of antennas on both sides or one side, when the mobility between the two sides is strong, if high-precision beam tracking is to be achieved, the overhead of channel measurement and feedback will be very large, which will affect the system capacity and resources The flexibility of allocation, which is especially prominent for the reference signal design of massive MIMO;

[0007] 2) Increased measurement and feedback complicate signal processing, increase power consumption, and challenge real-time beam tracking. For example, the increase in the number of codebooks for spatial precoding will make the corresponding codebook search process more complicated;

[0008] 3) Before the two-way communication is established between the mobile station and the base station, for example, in the paging or access phase, when the two parties use the control channel to communicate, since the spatial dimension parameters of the wireless channel of both parties cannot be predicted, it is difficult to use the beamforming brought by this phase. The benefits of paging or access signals cannot be concentrated in space, wasting power, increasing interference, and reducing the capacity of the control channel;

[0009] 4) The existing beamforming schemes are mainly aimed at lower wireless frequency bands, such as around 2GHz. When the frequency band of cellular mobile communication adopts higher frequency bands such as 5GHz or 60GHz, the system is more dependent on line-of-sight propagation and beam diffraction capabilities. Poor, the above-mentioned shortcomings of the existing beamforming method will be more obvious in mobile scenarios, and at the same time, it is difficult to bring out the advantages of large bandwidth in higher frequency bands

[0010] 5) As the base station density continues to increase, the potential interference between wireless devices adjacent to each other will become increasingly serious. In such a dense network deployment scenario, line-of-sight propagation will also become more common. How to suppress interference in line-of-sight scenarios will also presents a challenge to system design

Images