Abstract
Existing interference protection systems lack automatic evaluation methods to provide scientific, objective and accurate assessment results. To address this issue, this paper develops a layout scheme by geometrically modeling the actual scene, so that the hand-held full-band spectrum analyzer would be able to collect signal field strength values for indoor complex scenes. An improved prediction algorithm based on the K-nearest neighbor non-parametric kernel regression was proposed to predict the signal field strengths for the whole plane before and after being shield. Then the highest accuracy set of data could be picked out by comparison. The experimental results show that the improved prediction algorithm based on the K-nearest neighbor non-parametric kernel regression can scientifically and objectively predict the indoor complex scenes’ signal strength and evaluate the interference protection with high accuracy.
This article is supported in part by the National Natural Science Foundation of China under projects 61772150 and 61862012, the Guangxi Key R&D Program under project AB17195025, the Guangxi Natural Science Foundation under grants 2018GXNSFDA281054 and 2018GXNSFAA281232, the National Cryptography Development Fund of China under project MMJJ20170217, the Guangxi Science and Technology Base and Special Talents Program AD18281044, the Innovation Project of GUET Graduate Education under project 2017YJCX46, the Guangxi Young Teachers’ Basic Ability Improvement Program under Grant 2018KY0194, and the open program of Guangxi Key Laboratory of Cryptography and Information Security under projects GCIS201621 and GCIS201702.
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Chen, Z. et al. (2019). Wireless Communication Signal Strength Prediction Method Based on the K-nearest Neighbor Algorithm. In: Cheng, X., Jing, W., Song, X., Lu, Z. (eds) Data Science. ICPCSEE 2019. Communications in Computer and Information Science, vol 1058. Springer, Singapore. https://doi.org/10.1007/978-981-15-0118-0_18
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