Fair scheduling method based on mu-mimo for flow allocation ratio

Abstract

The invention discloses a MU-MIMO-based proportional fair scheduling method for flow distribution, which mainly solves the problem of proportional fair scheduling ignoring user service quality in the prior art. The implementation steps are: 1. Set the corresponding parameters according to the actual scheduling problem; 2. Calculate the user weight in the utility function according to the mean value of the emission probability satisfying the normal distribution; 3. Generate the sample value of the emission probability and calculate it according to the user weight The utility function value of the sample; 4. Filter out the sample value with good performance to update the mean value of the normal distribution; 5. Record the change of the mean value and switch the variance of different stages according to the corresponding rules; 6. End the iterative process according to the termination condition, A scheduling result that satisfies proportional fairness is obtained. The present invention can obtain satisfactory dispatching results under both sufficient and insufficient available wireless resources, has low computational complexity and fewer iterations, improves dispatching efficiency of base stations, and can be used in a single base station system using MIMO technology.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and relates to an MU-MIMO-based stream distribution proportional fair method, which can be used in a single base station system adopting MIMO technology. Background technique [0002] With the urgent demand for high data transmission rate systems today, 802.11ac, as a new generation of wireless local area network technology standard following 802.11n, has received widespread attention. 802.11ac consists of several important technologies, including what is known as multi-user multiple-input multiple-output MU-MIMO technology. MU-MIMO means that multiple users communicate with the base station in the same time-frequency resource, where both the base station and the user end have multiple antennas. MU-MIMO not only realizes space division multiplexing in the communication of a single user, but also realizes space division multiple access among multiple users, so MU-MIMO can not only ...

AI Technical Summary

Problems solved by technology

[0005] The above methods only study the situation of average resource allocation, but ignore the impact of each user's service quality requirements on resource allocation, especially when the available resources are insufficient, these average allocations are not the best allocation schemes, because in When resources are insufficient, users with high service quality requirements are allocated relatively less resources, while users with low service quality requirements are allocated relatively more resources, which is unfair

Images