A method for scheduling LTE resources

Abstract

The invention discloses an LTE resource scheduling method, which maintains a neighbor node list with a radius of R for each UE in the network. The neighbor node list is composed of two fields, which are UE_ID and UE_RS-SINR respectively, and UE_ID is the neighbor UE identifier. UE_RS‑SINR is the reference signal-to-noise ratio of the neighbor UE; when the reference signal-to-noise ratio of a target UE is lower than the threshold value, select the neighbor UE with the largest reference signal-to-noise ratio as the relay UE, and transfer the relay UE's The UE_ID is encapsulated in the MAC layer and reported to the base station and forwards the downlink data of the base station. The data is forwarded through the IEEE 802.11 link. When the base station performs scheduling, the data will be forwarded by the relay UE to the target UE.

Description

technical field [0001] The invention relates to the technical field of communication, in particular to an IEEE 802.11 technology-assisted LTE resource scheduling method. Background technique [0002] The LTE network can provide a downlink rate of more than 100M, and can meet the requirements of various services. With the increasing demand of mobile users for high-speed data services, LTE networks have begun large-scale construction and application. Currently common LTE scheduling algorithms include maximum carrier-to-interference ratio scheduling algorithm (MAX C / I), round robin scheduling algorithm (RR), proportional fair scheduling algorithm (RF), and dynamic scheduling algorithm. [0003] Various factors such as capacity, fairness and inter-cell interference need to be considered comprehensively in the above scheduling algorithms. The capacity of LTE is related to the channel quality between eNodeB (base station) and UE (user equipment). If the channel quality is good, ...

AI Technical Summary

Problems solved by technology

The capacity of LTE is related to the channel quality between eNodeB (base station) and UE (user equipment). If the channel quality is good, the transmission rate will be high, otherwise, the transmission rate will be low.

The maximum load-to-interference ratio scheduling algorithm fully considers the correlation between network capacity and channel quality; the round-robin scheduling algorithm focuses on the fairness of user scheduling; proportional fairness takes into account the advantages of both, but it still cannot make full use of high-quality channels to improve the overall network quality

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