Sea area large-scale antenna planar array beam selection and user scheduling method

Abstract

The invention provides a sea area large-scale antenna planar array beam selection and user scheduling method, and relates to the technical field of sea area scheduling. The method comprises the stepsas follows: R1, a shipborne AIS system performs information interaction with a shore-based base station equipped with a large-scale antenna planar array, and acquires position information of each user; and then height information of the shore-based base station and height information of a ship terminal are acquired via a height indicator; R2, a sea area range covered by beams corresponding to thelarge-scale antenna planar array is divided according to the user position information, and the height information of the shore-based base station and the ship terminal acquired in the step R1, and each user is divided into each corresponding beam; R3, the user with the highest priority is selected from each beam, and sequentially put into the set of users to be served; and R4, in each schedulingperiod, the user in the set of users to be served is scheduled according to a system weight and rate maximization criterion for service, and the unused beams are closed. According to the method provided by the invention, the beam selection and user scheduling speed is fast, and the algorithm complexity is low.

Description

technical field [0001] The present application relates to the technical field of sea area scheduling, and in particular to a beam selection and user scheduling method of a large-scale antenna planar array in the sea area. Background technique [0002] With the rapid development of the marine industry, marine tourism, offshore aquaculture and marine mineral exploration, marine multimedia services are becoming more and more important. In order to improve the transmission rate of the maritime communication system, we considered using a massive multiple-input multiple-output system (MMIMO) in the base station. First, MMIMO can deeply mine spatial dimension resources, so that multiple users can communicate with the base station on the same time-frequency resource. Communicate at the same time, thereby greatly increasing spectrum resources; second, MMIMO can greatly reduce uplink and downlink transmission power, thereby improving power efficiency; third, MMIMO concentrates beams i...

AI Technical Summary

Problems solved by technology

[0003] The overall user distribution in the sea scene is sparse, but it is crowded in the local area so that it is impossible to distinguish these users in the angle domain

Therefore, we need to schedule some users to serve to ensure the maximum weighted sum rate. The traditional scheduling method is based on the exhaustive method, scheduling the user combination with the largest sum rate for service, although this algorithm can schedule the best combination of users to be served , but it cannot adapt to the time-varying channel in the actual system, and the calculation complexity is high

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