Ai Bo

Novel statistical processing methods for wireless field strength prediction

This paper mainly deals with the statistical processing methods in wireless filed strength prediction process after sampling data are collected. The conventional standard for data collection and statistical processing in the prediction of wireless filed strength is Lees criteria. It utilizes linear averaging to process sampling data, as many other related papers discussed. However, the accuracy of such first order moment estimation is low, especially under serious Rayleigh fading channels. As regards to the defects of the method, we propose four novel statistical processing methods to process the collected data for wireless field strength. Computer simulations and corresponding analysis verify its much better prediction results with small estimation variances.

Interference Assessment in the High-Speed Railway Wireless Communication Networks by AHP-GRAP

Interference is a critical problem in the wireless communication networks, and interference performance assessment is of great sensibility necessity. This paper proposes a new comprehensive interference assessment method, AHP-GRAP (Analytic Hierarchy Process - Grey Relational Analysis Process, AHP-GRAP) method. And the AHP-GRAP is applied to a real case to resolve the interference assessment problem in the high-speed railway wireless communication networks in this paper. In the proposed AHP-GRAP method, the relative weights of QoS (Quality of Service, QoS) criteria in the high-speed railway wireless communication networks are determined by AHP, and then these weights are used as coefficients of GRAP model. Based on the optimal value of the QoS in the high-speed railway wireless communication networks, GRAP is then used to perform the evaluation of interference. The results show that AHP-GRAP is a more comprehensive method to reflect the interference state of the systems than existing single criteria interference assessment algorithms.