LTE downlink resource scheduling method for minimizing compression loss

Abstract

The invention provides an LTE downlink resource scheduling method for minimizing compression loss. The problem that the resource block compression is unconsidered when performing resource scheduling in the prior art is mainly solved. The scheme is as follows: 1, numbering a user and expanding to be same as the resource block number; 2, initializing transition probability of an algorithm; 3, completing allocation process from all resource blocks to the user; 4, updating the current maximum throughput and the optimal allocation scheme; 5, performing the transition probability update on the algorithm based on the optimal allocation scheme; and 6, iterating the algorithm until achieving the maximum iteration time, and mapping the expanded user serial number back to an original user number, thereby obtaining the optimal allocation scheme. In the sub-band channel quality allocation, the user fairness is guaranteed, and the compression efficiency of the resource block is improved, the improvement of the throughput is maximally guaranteed, and the method can be used for the multiuser scheduling in a long term evolution system.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and in particular relates to an LTE downlink dynamic resource allocation method, which can be used for resource access requirements of multi-user scheduling in the long-term evolution system LTE. Background technique [0002] For wireless communication, wireless resources, such as frequency spectrum and time slot, are very precious. How to improve spectrum utilization has become a technical issue that people are very concerned about. Many users compete for wireless resources, so that the allocation strategy needs to consider the fairness of users. While making each user can be scheduled fairly as much as possible, the throughput of the system must also be taken into consideration. The factors that determine the system throughput include: transmit power, time-frequency resources, channel quality, and resource allocation algorithm, and user fairness depends on the downlink schedulin...

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Problems solved by technology

[0006] The polling algorithm is the fairest algorithm for users. It allocates resource blocks to different users in turn, but because it does not consider channel quality and resource block compression, it sacrifices system throughput and resource block compression efficiency in exchange for users. Absolutely fair algorithm for

[0007] The maximum throughput algorithm is to allocate all resource blocks in each TTI to the user with the best channel quality. However, since resource block compression is not considered during allocation, the compressed CQI of a certain user may appear relatively low after the algorithm scheduling ends. A large degree of decline will make the compressed CQI of users with good channel quality at a relatively low level, resulting in a loss of system throughput. Moreover, this algorithm may cause uneven resource allocation, and users with good channel quality will appear More resources can be allocated, and edge users with poor channel quality cannot be scheduled

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