Method for improving network instantaneity and sensitivity by using accumulated link quality

Abstract

The invention relates to a method for improving the network instantaneity and sensitivity by using accumulated link quality. The method for improving the network instantaneity and sensitivity by using the accumulated link quality comprises the following steps of calculating the relationship between a PRR (Packet Reception Rate) and a LQI (Link Quality Indication) value; displaying the link quality through the link quality indication; calculating a partial packet reception rate to correct the numerical fault of the link quality indication from other factors, wherein an accumulation calculation method is used for calculate the PPR, the calculation formula is as the follows PRR(t) is equal to lambda*PRR (t) + (1-lambda)*PRR(t)(1), t is between 0 and n, (lambda is larger than 1 and less than 1). The accumulated calculation method can divide a large amount of packet reception rates and reduce waste of bandwidth. The designed calculation formula can simply and rapidly show the link quality accurately.

Description

technical field [0001] The invention relates to a method for improving the real-time performance and sensitivity of the network, in particular to a method for improving the real-time performance and sensitivity of the network by using accumulated link quality. Background technique [0002] The currently widely used link assessment method is based on statistically obtained packet reception rate, which can intuitively reflect the current link status. Using statistical mathematical means to calculate the packet receiving rate through the collection of a large number of samples, the advantage is that it is highly related to the link quality. But this evaluation method has two disadvantages: ① because the statistical sample is a historical event, its real-time performance is not enough; ② due to the large statistical base, the sensitivity to unexpected network changes is not enough. In addition, it is difficult to choose the size of the statistical base. If it is too small, ...

AI Technical Summary

Problems solved by technology

But this evaluation method has two disadvantages: ① because the statistical sample is a historical event, its real-time performance is not enough; ② due to the large statistical base, the sensitivity to unexpected network changes is not enough. In addition, it is difficult to choose the size of the statistical base. If it is too small, the accuracy will not be enough; if it is too large, it will waste a lot of bandwidth and consume a lot of energy. These are not allowed in resource-constrained WSNs

Relying on hardware detection to complete link quality assessment, less overhead, and quick response to link quality changes. Its disadvantage is that the evaluation of the link is completely dependent on the functions provided by the communication chip itself, the scalability is poor, and the evaluation accuracy is also limited.

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