Analysis of the impact of network architecture on signal quality in LTE technology

Stojanović, Ivana; Koprivica, Mladen; Stojanović, Nenad; Nešković, Aleksandar N.

doi:10.2298/sjee2001095s

Cited by 5 publications

(3 citation statements)

References 8 publications

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“…As the table indicates, the CQI and spectral efficiency values improve as the SINR value increases. Table 2 shows the evaluations of connection quality in the LTE-A network based on the RSRP, RSRQ, and SINR values [22]. Higher efficiency is obtained if the SINR is excellent for a measurement range; on average, RSRP and SINR are related, and the smaller the difference between RSSI and RSRP, the better the RSRQ.…”

Section: Lte-a Technologymentioning

confidence: 99%

Performance analysis and modeling based on LTE-A field measurements: a city center example

Kurnaz

Kola

Esenalp

2023

Int. j. inf. tecnol.

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The wireless communication channel is the critical parameter that affects the throughput in the LTE-A network. The user equipment measures the quality of the wireless channel as the channel quality indicator (CQI) value and transmits it to eNodeB. The eNodeB uses the CQI value to select the adaptive modulation and coding method to achieve the highest throughput. This study analyzes the LTE-A network based on actual field measurements. Measurements were taken at 80 different locations in Samsun (Turkey) city center using TEMS Investigation software. RSRP, RSRQ, SINR, CQI, and throughput values were recorded for each measurement in a stationary position while downloading 500 MB of data. Then, the averages of these recorded data were calculated, and detailed analyses were performed. At the end of the study, the effects of RSRP, RSRQ, SINR, and CQI on the throughput value in the LTE-A network were examined, and a novel mathematical model was proposed that gives the relationship between them with 88.85% accuracy. It has also been observed that the accuracy of the proposed model can be increased by 4% with GRNN. In the last stage of the study, a new CQI mapping method based on real-field measurements for the LTE-A system was developed.

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Section: Lte-a Technologymentioning

confidence: 99%

Performance analysis and modeling based on LTE-A field measurements: a city center example

Kurnaz

Kola

Esenalp

2023

Int. j. inf. tecnol.

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“…Es pertinente mencionar que los valores de los parámetros RSSI y RSRQ, obtenidos en los dos escenarios, se acercan a los valores teóricos planteados en [7] y [9] para las tres categorías (excelente, regular y mala), lo que confirma la consistencia de los resultados obtenidos. Sin embargo, se puede añadir que las diferencias entre los valores y las categorías establecidas en las referencias y los obtenidos en este estudio práctico se pueden deber a varios factores, como, por ejemplo: la cantidad de datos recolectados, la técnica aplicada, la exactitud de la herramienta para recolectar datos, entre otros.…”

Section: Análisis Y Comparación De Los Escenariosunclassified

Modelo de aprendizaje automático para la predicción de calidad en modo estático-inactivo y modo móvil-conectado en redes LTE

Curipallo¹,

Pozo²,

Lupera-Morillo³

et al. 2022

RITI

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In this paper, the main aims are to obtain a quality of signal prediction model in idle-static mode and a quality of connection prediction model in connected-mobile mode, for this, we apply machine learning technique to a real dataset collected from a LTE network deployed at Quito, Ecuador. The proposed models are capable to predict the conditions of low received signal strength and low data rate which is important to select the appropriate method that will most likely offer the highest quality of service. The proposed schemes based on decision tree improves in the idle-static mode and present an accuracy of 67% approximately when compared to the connected-mobile mode, and finally, we propose future works.

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“…All LTE network nodes are often classified into two types: the radio access network is tied to the nodes, and the nodes form the core network [3]. The algorithms and procedures utilized to transport data between base stations (eNB) and mobile user terminals (UE) are critical components that define the efficacy of any radio network [4].…”

Section: Introductionmentioning

confidence: 99%

Automatic Cell Planning Method for Radio Network Optimization

Putri,

Ahmad,

Hikmaturokhman

et al. 2024

JOIV : Int. J. Inform. Visualization

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As the first step in building a wireless communication network, wireless network optimization is crucial since it determines how the network will be built scientifically. Numerous challenges remain in the way of the Radio Network's deployment in Indonesia, not the least of which is the still-uneven coverage region. The Kiaracondong region in Bandung is one of the numerous areas in Indonesia that are still considered to be "bad spot areas" as a result. Based on the findings of the driving test conducted in the Kiaracondong sub-district, the KPI target was not fulfilled for the RSRP, SINR, and Throughput parameters. Therefore, this study primarily focuses on the physical tuning optimization using the Automatic Cell Planning (ACP) method for the LTE wireless network optimization. To assess the quality of the LTE network before and after optimization, the results of the ACP optimization simulation will be compared with the results of the existing or non-ACP site simulation and the results of the operator's ACP implementation. As a result, Area 1 has an average RSRP of -72.79 dBm, area 2 -73.17 dBm, and area 3 -68.22 dBm. Additionally, the average SINR in areas 1,2 and 3 is 8 dB, 6.58 dB, and 8.17 dB, respectively. The average downlink throughput in area 1 is 42652.66 Kbps, area 2 is 34420.88 Kbps, and area 3 is 43882.92 Kbps. Finally, the average throughput uplink for areas 1 to 3 is 51651.24 Kbps, 47895.99 Kbps, and 49648.84 Kbps, respectively.

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Analysis of the impact of network architecture on signal quality in LTE technology

Cited by 5 publications

References 8 publications

Performance analysis and modeling based on LTE-A field measurements: a city center example

Performance analysis and modeling based on LTE-A field measurements: a city center example

Modelo de aprendizaje automático para la predicción de calidad en modo estático-inactivo y modo móvil-conectado en redes LTE

Automatic Cell Planning Method for Radio Network Optimization

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