Performance analysis method in wireless mobile communication

Abstract

The invention discloses a performance analysis method in wireless mobile communication, comprising the steps: adopting the cross-layer thought, considering a time varying fading channel in a wireless network in a combined manner, a forward error correction of a physical layer and a stop waiting ARQ (Automatic Response Query) protocol of a data link layer, and solving the service rate and the probability of stability of different states of the Markov chain with limited state on the basis of considering different level characteristics of the wireless network comprehensively. Known by comparisonof data analysis results, the model number is reduced compared with the state number of the Markov chain model with limited state constructed by the invention, the complexity of analysis is reduced, and the calculated service rate and the probability of stability of each state in the Markov chain model with limited state are very important variations in network performance.

Description

technical field [0001] The invention belongs to the wireless mobile communication technology, relates to the performance analysis problem in the wireless mobile communication, can be directly applied to the wireless mobile communication, and analyzes the service quality problem in the wireless mobile communication conveniently and accurately. Background technique [0002] With the diversification of data services in wireless mobile communications, different data services have different service quality guarantee requirements, and are more and more sensitive to performance such as delay backlog. The development of modern means of transportation, such as the popularization of high-speed means of transportation such as light rail and high-speed rail, has led to the acceleration of the mobile speed of communication terminals, which makes the fading of channels faster and faster. It's getting worse. The performance analysis framework of wireless mobile communication must be accur...

AI Technical Summary

Problems solved by technology

That is, for a channel subject to a certain fading characteristic, from the perspective of bit error rate measurement, the SNR of the channel is divided into a series of continuous SNR intervals (Γ 1 , Γ 2 ), [Γ 2 , Γ 3 )...[Γ N , Γ N+1 ), each SNR interval represents a channel state, so as to determine the corresponding finite-state Markov chain model, the numerical analysis results show that the number of states of the finite-state Markov chain calculated by this method is large, that is, the Many redundant states will increase the complexity of analysis

At the same time, this modeling method only considers the characteristics of the wireless channel in the network. However, the different layers of the network are a whole, and they control the network performance cooperatively. It is one-sided to only consider the performance impact of the wireless channel, and the bit error rate has a great impact on the network performance. The reference value of the upper-layer performance measurement is small, and the performance of the entire network cannot be analyzed well

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