Development of a Model for Forecasting LTE Network Performance during Rainy Seasons
- Citation Author(s):
-
Ngozi Eli-Chukwu
(Alex Ekwueme Federal University Ndufu Alike, Ebonyi State, Nigeria)
Ogwugwam Ezeagwu (Nnamdi Azikiwe University)Isaac Ezenugu (Imo State University)Stella Arinze (Alex Ekwueme Federal University Ndufu Alike, Ebonyi State, Nigeria) - Submitted by:
- Ngozi Eli-Chukwu
- Last updated:
- DOI:
- 10.21227/6xcg-jp45
- Data Format:
- Links:
423 views
Abstract
Abstract— In this research, a model for LTE network performance forecast during the rainy season was developed. During the rainy season, cellular network performance is greatly affected. optimization Engineers find it difficult to ascertain cellular (LTE) network parameters that negatively influences the network performance and make a performance prediction during the rainy season. In achieving this, an experimental approach was used to study network samples collected over the LTE network of MTTN in Lagos during the rainy season for a period of 48weeks. Network parameters that are greatly affected by rainfall were identified and a model was developed for predicting and forecasting the network performance during rainy seasons. From the experimental result, Signal quality parameters such as the Referenced Signal Received Quality (RSRQ) and Signal-to-Interference Noise Ratio (SINR) become bad and negatively affect the network performance during rainy seasons. Optimization activities by cellular network operators should be geared towards improving the signal quality parameters during rainy seasons.
Abstract— In this research, a model for LTE network performance forecast during the rainy season was developed. During the rainy season, cellular network performance is greatly affected. optimization Engineers find it difficult to ascertain cellular (LTE) network parameters that negatively influences the network performance and make a performance prediction during the rainy season. In achieving this, an experimental approach was used to study network samples collected over the LTE network of MTTN in Lagos during the rainy season for a period of 48weeks. Network parameters that are greatly affected by rainfall were identified and a model was developed for predicting and forecasting the network performance during rainy seasons. From the experimental result, Signal quality parameters such as the Referenced Signal Received Quality (RSRQ) and Signal-to-Interference Noise Ratio (SINR) become bad and negatively affect the network performance during rainy seasons. Optimization activities by cellular network operators should be geared towards improving the signal quality parameters during rainy seasons.
Instructions:
The Data Set in figure 1 RSRP was ploted against network performance index (Column 3 against 7)
The RSRQ plotedagainst network performance index for figure 2
RSSI plotedagainst network performance index for figure 3
SNR plotedagainst network perfromance index for figure 4
