A method for phased array multi-beam scheduling optimization based on sea area communication

Abstract

The present invention discloses a method for optimizing phased array multi-beam scheduling based on maritime communications. Based on the location information reported by user devices, the method merges the beams of similarly located users and dynamically and intelligently controls the phased array antenna to output a smaller number of beams with different widths within a scheduling cycle. Based on the location information reported by user devices, the method dynamically and intelligently controls the phased array antenna to output a smaller number of beams with different widths within a scheduling cycle, effectively reducing scheduling frequency and minimizing resource waste and performance loss caused by beam switching.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a method for optimizing phased array multi-beam scheduling based on sea area communication. Background Art

[0002] In existing technical solutions, phased array antennas mostly use fixed-width beam pointing, and each online remote user will occupy a beam pointing. Since the TD-LTE (Time Division-Long Term Evolution) system adopts time division multiplexing scheduling logic, only one beam pointing output at the same time. Therefore, when the number of users is large, adopting the above solution will lead to frequent beam scheduling, resulting in resource waste and increased performance loss. Summary of the Invention

[0003] The purpose of the present invention is to address the defects and shortcomings of the existing technology and provide a method for optimizing phased array multi-beam scheduling based on sea area communication, which can reduce the switching frequency and reduce performance loss.

[0004] To achieve the above objectives, the present invention adopts a technical solution: a method for optimizing phased array multi-beam scheduling based on maritime communications. Its innovation lies in: merging the beams of users with similar locations based on the location information reported by user devices, and dynamically and intelligently controlling the phased array antenna to output a smaller number of beams with different widths within a scheduling cycle. The specific process includes:

[0005] S1. Summarize the location information of current online users, including distance and azimuth, and divide them into different levels of user groups based on distance;

[0006] S2. Beam merging is performed on users from far to near. Specifically, the number of users that can be covered by each beam at the current level is first counted. The beam with the largest number of users is then selected. All users covered by this beam are removed from the user group and excluded from subsequent counting. This process is repeated until all users are covered by the beam.

[0007] S3. The beam pointing generated in the above process is integrated to form the final beam output control signal, which controls the phased array antenna beam. The final output beam is obtained according to the principle of from far to near and the beam number calculation formula "beam number = starting number + azimuth - 1".

[0008] Furthermore, corresponding to the beamforming of different widths of the phased array antenna, a more appropriate beam width can be selected according to the different distances of user distribution to achieve better signal coverage quality.

[0009] The beneficial effects of the present invention are:

[0010] The present invention can dynamically and intelligently control the phased array antenna to output beam directions of different widths and numbers within a scheduling cycle based on the location information reported by the user equipment, which can effectively reduce the scheduling frequency and minimize resource waste and performance loss caused by beam switching. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 This is a schematic diagram of the applicable scenario architecture of Example 1;

[0012] Figure 2 This is the algorithm flow chart of Example 2;

[0013] Figure 3 This is a schematic diagram of the effect of scheduling optimization in Example 3. DETAILED DESCRIPTION

[0014] The present invention will be further described below with reference to the accompanying drawings.

[0015] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0016] Example 1

[0017] See Figure 1 , a method for optimizing phased array multi-beam scheduling based on marine communication, applicable to scenarios such as Figure 1 It is mainly aimed at maritime communication systems that include phased array beam tracking. The maritime base station equipment supports long-distance dynamic coverage capabilities, reaching a coverage radius of 100 kilometers. Among them, S01 achieves static and dense coverage of close-range users through wide beams, S02 provides long-range broadband access services, and at the same time provides user business enhancement services through S03 phased array antenna dynamic beam tracking.

[0018] The method proposed in the present invention can, based on the above-mentioned system, merge the beams of users with similar locations according to the location information reported by the user devices, and dynamically and intelligently control the phased array antenna to output a smaller number of beam directions with different widths within a scheduling cycle, thereby achieving the scheduling optimization purpose of reducing the switching frequency and reducing performance loss.

[0019] Example 2

[0020] See Figure 2Since beam scheduling in the prior art adopts a one-to-one allocation scheme, that is, each user is assigned a beam direction, a large number of beam directions will be generated when the number of users is large. This will result in an excessively high scheduling frequency within a scheduling cycle, affecting the system service performance. To avoid the above problems, and based on the application scenarios of the maritime communication system and the performance of the phased array antenna, the method proposed in the present invention can dynamically and intelligently merge users with relatively concentrated directions into a group, sharing a beam direction, effectively reducing the system scheduling pressure. In this embodiment, the distance is divided into three levels: far, medium and near, corresponding to the beamforming of different widths of the phased array antenna. According to the different distances of the user distribution, a more appropriate beam width can be selected to achieve a better signal coverage quality.

[0021] The specific algorithm flow chart of the method proposed by the present invention is as follows Figure 2 , corresponding to:

[0022] S11, summarizing the location information of current online users, including distance and azimuth, and dividing them into different levels of user groups based on distance;

[0023] S12, performing beam combining processing on users from far to near in sequence;

[0024] Specifically, the system first counts the number of users that can be covered by each beam at the current level. Then, it selects the beam with the largest number of users. At the same time, all users covered by this beam are removed from the user group and excluded from subsequent statistics. The process is repeated until all users are covered by the beam.

[0025] S13, combining the beam pointing directions generated in the above process to form a final beam output control signal to control the phased array antenna beam;

[0026] The following is a detailed description of the algorithm processing flow with examples:

[0027] The data shown in Table 1 simulates a set of online user location information, and Table 2 gives the beamforming capabilities and beam output numbers supported by a set of phased array antennas;

[0028] Table 1:

[0029] User Number User distance User azimuth 1 86 25 2 53 26 3 75 3 4 34 63 5 30 62 6 18 61

[0030] Table 2:

[0031] Beam level Maximum coverage distance Beam number start Beam number end Beamwidth 0 10 0 0 91 1 40 1 91 30 2 70 92 183 15 3 100 184 275 5

[0032] The processing process combined with the above algorithm is as follows:

[0033] 1. According to the distance division in Table 2, the users in Table 1 can be divided into three groups: (1, 3), (2), and (4, 5, 6);

[0034] 2. Counting the number of users that can be covered in the beam direction, we find that the 25-degree direction covers two users (1, 2), the 3-degree direction covers one user (3), and the 62-degree direction covers three users (4, 5, 6). Therefore, according to the principle of starting from far to near and the beam number calculation formula:

[0035] Beam number = starting number + azimuth - 1

[0036] It is concluded that the final output beams are 208, 186 and 62.

[0037] Example 3

[0038] See Figure 3 , the effect diagram of scheduling optimization is as follows Figure 3 That is, the original scheduling within the sector will generate 6 beams pointing to 6 users. After optimization by the solution proposed by the present invention, users with relatively concentrated directions are merged and grouped, and beamforming that meets the conditions is preferred. Ultimately, only 3 beams are needed to achieve full coverage of 6 users, effectively reducing the number of beams participating in switching within a scheduling cycle, thereby reducing resource waste and performance loss caused by frequent switching in the system.

[0039] The above description is only used to illustrate the technical solution of the present invention and is not intended to limit it. Other modifications or equivalent substitutions made to the technical solution of the present invention by ordinary technicians in this field should be included in the scope of the claims of the present invention as long as they do not depart from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for optimizing phased array multi-beam scheduling based on maritime communications, characterized by: Based on the location information reported by user devices, the beams of users with similar locations are merged, and the phased array antenna is dynamically and intelligently controlled to output a smaller number of beams with different widths within a scheduling cycle. The specific process includes: S1. Summarize the location information of current online users, including distance and azimuth, and divide them into different levels of user groups based on distance; S2. Beam merging is performed on users from far to near. Specifically, the number of users covered by each beam at the current level is first counted. The beam with the largest number of users is then selected. All users covered by this beam are removed from the user group and excluded from subsequent counting. This process is repeated until all users are covered by the beam. S3. The beam pointing patterns generated in the above process are combined to form the final beam output control signal, which controls the phased array antenna beam. The final output beam is calculated based on the principle of moving from far to near and the beam number calculation formula (beam number = starting number + azimuth - 1).

2. The method for optimizing phased array multi-beam scheduling based on maritime communications according to claim 1, characterized in that: Corresponding to the different widths of beamforming of the phased array antenna, the appropriate beam width is selected according to the different distances of user distribution to achieve good signal coverage quality.

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