4G LTE Experience: Reference Signal Received Power, Noise Ratio and Quality

2021 ◽  
Author(s):  
Gubtha Mahendra Putra ◽  
Edy Budiman ◽  
Yonatan Malewa ◽  
Dedy Cahyadi ◽  
Medi Taruk ◽  
...  
Keyword(s):  
Reference Signal ◽  
Received Power ◽  
Power Noise ◽  
Noise Ratio ◽  
4G Lte

scholarly journals Analisis Performa Reference Signal Received Power Akibat Rugi-Rugi Propagasi Pada Frekuensi 2300 MHz Dengan Model Okumura

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Sandryones Palinggi ◽  
Aan Saputra
Keyword(s):  
Reference Signal ◽  
Received Power ◽  
4G Lte

Teknologi seluler, terutama 4G-LTE, telah berkembang ke arah yang jauh lebih canggih. Teknologi 4G-LTE merupakan kelanjutan dari teknologi sebelumnya yang disebut 3G. Dalam penelitian ini, perhitungan kekuatan sinyal kemudian digunakan untuk menghitung kerugian yang terjadi pada frekuensi 2300 MHz di sepanjang Jalan Cihampelas Bandung, yang memiliki panjang lintasan 2.7 Km. Metode penelitian yang digunakan adalah metode kuantitatif yang menggunakan data primer hasil pengukuran, kemudian membandingkannya dengan metode empiris dalam bentuk perhitungan ideal. Perhitungan di lingkungan outdoor menggunakan Model Okumura dengan mempertimbangkan topologi maupun rugi-rugi propagasi di sepanjang Jalan Cihampelas Bandung seperti Skywalk Cihampelas dan bangunan bertingkat. Hasil penelitian ini dinyatakan dalam bentuk tabel dan grafik dengan menggunakan Matlab sehingga mudah untuk menarik hasil analisis dari penelitian yang dilakukan, yang mana diketahui bahwa rugi-rugi propagasi yang terjadi mempengaruhi Reference Signal Received Power dari jaringan komunikasi seluler berbasis teknologi 4G-LTE.

scholarly journals Analisis Coverage Planning dan Coverage Prediction di Existing Network eNodeB Jaringan 4G di Daerah Operasional Yogyakarta dan Magelang

2018 ◽  
Vol 17 (02) ◽  
pp. 69-80
Author(s):  
Pilar Tiara Lelepadang ◽  
Eva Yovita Dwi Utami ◽  
Andreas Ardian Febrianto
Keyword(s):  
Radio Frequency ◽  
Reference Signal ◽  
Cell Identity ◽  
Interference Noise ◽  
Received Power ◽  
Planning Tools ◽  
Noise Ratio ◽  
Coverage Prediction ◽  
Physical Cell Identity ◽  
Coverage Planning

Untuk meningkatkan kinerja jaringan 4G yang merupakan jaringan uji coba di Yogyakarta dan Magelang  maka harus dilakukan coverage planning pada daerah yang kurang optimal. Kurang optimalnya daerah ini dikarenakan cakupan dan kualitas Radio Frequency (RF) masih belum memenuhi standar yang sudah ditetapkan oleh perusahaan. Hal ini terlihat pada hasil drive test daerah operasional. Solusi yang permanen, yakni pembangunan site baru dapat mengoptimalkan RF yang belum memenuhi standar perusahaan. Selain itu, untuk menjaga kualitas site baru agar tidak terjadi interferensi maka perlu dilakukan perencanaan Physical Cell Identity (PCI). PCI merupakan identitas site yang berbentuk kode angka 0 sampai 503. Parameter RF yang diteliti ialah Reference Signal Received Power (RSRP) dan Signal to Interference Noise Ratio (SINR). Analisis hasil drive test menurut parameter RF akan menghasilkan rekomendasi pembangunan site baru. Rekomendasi tersebut disimulasikan cakupan areanya dalam bentuk coverage prediction yang merupakan simulasi dengan planning tools U-Net. Dari hasil simulasi ini, didapatkan 50% cakupan area pada Yogyakarta memiliki RSRP  yang semula -99,17 dBm menjadi -98,78 dBm dan untuk Magelang yang semula -96,51 dBm menjadi -95 dBm. Sementara , SINR pada Yogyakarta meningkat rata-ratanya dari 1,03 dB menjadi 1,18 dB dan pada Magelang meningkat rata-ratanya dari 2,23 dB menjadi 2,55 dB.

scholarly journals Applications of Extreme Gradient Boosting for Intelligent Handovers from 4G To 5G (mm Waves) Technology with Partial Radio Contact

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 545
Author(s):  
Saad Ijaz Majid ◽  
Syed Waqar Shah ◽  
Safdar Nawaz Khan Marwat
Keyword(s):  
Success Rate ◽  
Research Work ◽  
Reference Signal ◽  
Base Stations ◽  
Gradient Boosting ◽  
Received Power ◽  
Extreme Gradient Boosting ◽  
4G Lte ◽  
Radio Contact ◽  
Mm Waves

In a network topology, where 5G (mm Waves) have better coverage footprint compared to 4G (LTE or LTE-A) technology, mobile devices would generally be handed over from 4G to 5G. In this work, a supervised intelligent prediction technique for improved handover success rate (HSR) from 4G to 5G technology is proposed. The technique is applicable for base stations enabled with sub-6-GHz and mm-wave bands. This technique is novel since it can predict HSR even before switching to 5G radio circuitry or initiating its measurement gap for acquisition of mm-wave reference signal received power (RSRP) unlike conventional algorithms. Thus, preempting all handovers which are likely to fail will provide improvements in latency, delay, and handover success rate, as well as decrease call drops. Therefore, this research work answers previous research shortcomings and can unleash applications of supervised intelligent algorithms for predicting the HSR from 4G to 5G. The proposed algorithm is validated by showing improvements obtained through simulation results performed using Python-based framework. The proposed algorithm is tested for reliability with increasing parameters such as the intensity number of UEs and simulation time. Improvements in standard handover algorithm are also proposed.

scholarly journals Eficiencia de sistemas multiantena MU–MIMO por simulaciones de radiopropagación

2017 ◽  
Vol 11 (1) ◽  
pp. 55-62
Author(s):  
Javier Enrique Arévalo Peña
Keyword(s):  
Reference Signal ◽  
Long Term Evolution ◽  
Signal To Noise ◽  
3Gpp Lte ◽  
Term Evolution ◽  
Received Power ◽  
La Red

El presente artículo tiene como propósito realizar la descripción de los resultados de simulación de radiopropagación con una antena MU{MIMO (4x4) en una red LTE (del inglés Long Term Evolution), con el fin de establecer su eciencia respecto a una antena estándar. En esta vía, se emplea la herramienta de diseño de redes inalámbricas ICS Designer en la cartografía digital de alta resolución en un escenario urbano de la ciudad de Bogotá D.C., Colombia. Se utiliza el modelo 3GPP LTE en la simulación de la red LTE y se analizan los parametros RSRP (del inglés, Reference Signal Received Power), RSRQ (del inglés, Reference Signal Recieved Quality), SNIR (del inglés, Signal to Noise and Interference Ratio) rendimiento (Throughput) y QCI (del inglés, QoS Class Identier). Se evidencian, como consecuencia de los resultados, ventajas de las antenas MU-MIMO.

scholarly journals Analisa Kinerja Pada Perencanaan TD-LTE ADVANCED Studi Kasus Kota Bandung

AVITEC ◽  
2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Purusadi Hastruman ◽  
Arfianto Fahmi ◽  
Uke Kurniawan Usman
Keyword(s):  
Reference Signal ◽  
Signal Strength ◽  
Advanced Technology ◽  
Frequency Division ◽  
Bit Rate ◽  
Received Power ◽  
Lte Advanced ◽  
Advanced Planning ◽  
The Mean ◽  
Time Division

In LTE Advanced technology there are two methods used in the duplexing process, there are frequency division duplex (FDD) wherein this duplexing concept communication is divided based on the frequency and the other is time division duplex (TDD) where communication is divided based on the time. Duplexing using the TDD method has advantages of handling data-based services that the majority have Non-Guarantee Bit Rate (N-GBR) characteristics because most of these services do not require a minimum bit rate to be able to work and this is an advantages because nowadays people like to use data-based services. So in this LTE Advanced network planning using the TDD method,  frequency 2300 MHz for TD-LTE advanced, and parameters that to be the main focus are throughputs, reference signal received power (RSRP), reference signal strength indicator (RSSI), carrier to interference noise ratio (CINR), and block error rate (BLER). And the result of the simulations from TD-LTE Advanced planning are the mean of throughput value is 3,5 Mbps, mean of RSRP value is -110,8 dBm, mean of RSSI value is -72,36 dBm, mean of CINR value is 4,81 dB, and mean of BLER value is 0,07%.

scholarly journals Modeling the Distribution of Radiofrequency Intensities from the Digital Terrestrial Television (DTTV) Broadcasting Transmitter in Kampala Metropolitan; Uganda

2020 ◽  
pp. 65-78
Author(s):  
Peter Opio ◽  
Akisophel Kisolo ◽  
Tumps W. Ireeta ◽  
Willy Okullo
Keyword(s):  
Prediction Models ◽  
Reference Signal ◽  
Path Loss ◽  
Analysis Software ◽  
Propagation Models ◽  
Received Power ◽  
Loss Prediction ◽  
Path Loss Prediction ◽  
Digital Terrestrial Television ◽  
The One

This study presents the modeling of the distribution of RF intensities from the Digital Terrestrial Television (DTTV) broadcasting transmitter in Kampala metropolitan. To  achieve this, the performance evaluation of the different path loss propagation models and envisaging the one most suitable for Kampala metropolitan was done by comparing the path loss model values with the measured field Reference Signal Received  Power (RSRP) values. The RSRP of the DTTV broadcasting transmitter were measured at operating frequencies of 526 MHz, 638 MHz, 730 MHz and 766 MHz using the Aaronia  Spectran HF-6065 V4 spectrum analyzer, Aaronia AG HyperLOG 4025 Antenna at 1.5 m and 2.5 m heights, Aaronia GPS Logger, real time Aaronia MCS spectrum-analysis-software and   a T430s Lenovo Laptop. On comparing the measured path loss values with the various  path loss prediction model values, results showed that Egli and Davidson models are the  most accurate and reliable path loss prediction models for the distribution of DTTV RF  intensities in Kampala metropolitan, since their Root Mean Square Error values were the least for both routes.

scholarly journals Multilevel diode clamped D-Statcom for power quality improvement in distribution systems

2021 ◽  
Vol 12 (1) ◽  
pp. 217
Author(s):  
Jasti Venkata Ramesh Babu ◽  
Malligunta Kiran Kumar
Keyword(s):  
Power Quality ◽  
Power Distribution ◽  
Distribution System ◽  
Distribution Systems ◽  
Electrical Power ◽  
Reference Signal ◽  
Power Distribution System ◽  
Received Power ◽  
Multi Level ◽  
Result Analysis

Power quality is one big issue in power system and a big challenge for power engineers today. Electrical consumers (or otherwise load devices) expect electrical power received power should be of first-class. Bad quality in electrical power directs to fuse blowing, machine overheating, increase in distribution losses, damage to sensitive load devices and many more. DSTATCOM is one of the FACTS controllers designed to improve the quality in electrical power and thus improving the performance of distribution system. This paper presents a multilevel DSTATCOM topology to enhance power quality in power distribution system delivering high-quality power to the customer load devices. Diode-clamped structure is employed for multi-level DSTATCOM structure. ‘PQ’ based control strategy generates reference signal which is further processed through level-shifted multi-carrier PWM strategy for the generation of gate pulses to multi-level DSTATCOM structure. Simulation work of proposed system is developed and the result analysis is presented using MATLAB/SIMULINK software. Performance of multi-level DSTATCOM topology is verified with fixed and variable loads.

scholarly journals Optimal Power Allocation Between Beam Tracking and Symbol Detection Channels in a Free-Space Optical Communications Receiver

2020 ◽  
Author(s):  
Muhammad Salman Bashir ◽  
Mohamed-Slim Alouini
Keyword(s):  
Power Allocation ◽  
Free Space ◽  
Signal To Noise Ratio ◽  
Optimal Power Allocation ◽  
Free Space Optical ◽  
Signal To Noise ◽  
Pointing Error ◽  
Optimal Power ◽  
Received Power ◽  
Noise Ratio

Free-space optical (FSO) communications will play an important role in the backhaul of future generation of wireless networks in order to support high data rates. Because of narrow beamwidth inherent to an optical signal, acquisition and tracking form an important component of any FSO communication system. In this study, we have analyzed the optimization of received power allocation between tracking and data channels in an FSO receiver. The objective function that is optimized (minimized) are the probability of error and the probability of outage, and the optimization of power allocation is carried out as a function of parameters such as noise power, pointing error variance, pointing error correlation coefficient, and the threshold of outage. We have analyzed the optimization concerning the lognormal and exponentiated Weibull fading scenarios as well. We learn that the optimal power allocation is a function of the received signal-to-noise ratio: a lower signal-to-noise ratio dictates that a higher fraction of received power should be diverted to the tracking channel and vice versa.

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