Optimizing throughput value through re-examining of 4G LTE infrastructure link budgets: A Case Study in Lubuk Kilangan

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I. INTRODUCTION
The development in telecommunications technology to Broadband Wireless Access technology (Lin et al,2019) (Singh et al, 2020), necessitates that users be able to communicate with high data transfer, high capacity, a larger application range, and high mobility.Improving communication service quality is performed to have more connections and faster access to information, hence fulfilling the growing demand for information access.LTE is one of the standard radio access technologies developed by the third generation (3GPP) (Yang et al, 2020), (Gomez-Barquero, 2020), (Lau et al, 2019).
LTE operates in two modes, namely FDD (Frequency Division Duplex) and TDD (Time Division Duplex).(Mamane et al, 2022), (Chandra et al, 2020).FDD uses different frequencies between downlink and uplink Holma & Toskala, 2011).LTE TDD in Indonesia uses a frequency of 2300 MHz and has balanced features between downlink and uplink (Setyo & Sari, 2019).Overall, according to research conducted by the Association of Indonesian Internet Service Providers (APJII), the number of Internet users in Indonesia increased by 8% to 143.26 million people.Since its introduction in 2014, 4G LTE services have gotten more aggressive.According to information from the Minister of Communication and Information, telecommunications providers built 62,291 4G BTS over three years.This number rises year after year as the population grows.( APJII, 2018).
The problem that often arises in mobile communication systems is the wide range of services (coverage) (Rismawati, 2019).Availability of network capacity (capacity), and level of network service quality (quality).Based on data from the Central Statistics Agency (BPS) in 2021, one example of a case in Lubuk Kilangan Urban Village is that the population in the Lubuk Kilangan region with an area of 85.99 km2 is 57,472 people.However, there is still a lack of research on the effectiveness of optimization techniques in real-world scenarios, especially in the context of Lubuk Kilangan.However, there is still a lack of research on the effectiveness of optimization techniques in real-world scenarios, especially in the context of Lubuk Kilangan.In the Lubuk Kilangan area, the population is rising and must be supported by growth in cellular telecommunications network infrastructure to ensure network quality remains excellent.Ideally, the region has download speeds of 5 Mbps to 100 Mbps or more, while upload speeds range from 2 Mbps to 50 Mbps.As a result of these issues, it is required to examine network quality as well as optimize coverage through antenna tilting and link budget estimates.tilted antennas can be beneficial in optimizing coverage and managing interference for picocells, femtocells, and repeaters, the specific deployment scenario and requirements play a crucial role in determining the most suitable antenna configuration.The reason behind the findings of this study is that the optimal link budget value for 4G LTE infrastructure in Lubuk Kilangan is higher than the current industry standard due to the unique characteristics of the area.It's essential to conduct a site survey, consider the surrounding environment, and take into account the intended coverage area to make informed decisions about antenna tilt angles and configurations.Additionally, consulting with RF (Radio Frequency) engineers and specialists can help ensure optimal performance in specific deployment scenarios.
A link budget is a calculation that takes into account all power gains and losses incurred by communication signals in a telecommunications system.(Akhtaruzzaman, 2020), (Loku Galappaththige et al, 2022), (Zaki et al, 2020).Atoll software is used to simulate link budget optimization in Lubuk Kilangan.Atoll is a radio network planning and optimization program that provides a variety of comprehensive and integrated features that enable users to develop microwave or radio planning projects in a single application.The aim is to determine the occurrence of bad spot areas on the LTE network.Able to optimize LTE FDD coverage to optimize 4G LTE network services.Able to carry out optimization simulations to determine LTE network level signal coverage using Atoll.

Coverage Planning
Coverage Planning is an important network planning process in cellular network transmission to determine areas covered by cellular network services.This stage is determined from several components in the form of an actual propagation model based on terrain area, chaos, and population.The propagation model is very simple in predicting the nature of signal propagation in an accurate form.In LTE the air interface and radio-electronic signals are different from those that are transmitted, modeling and simulation using RF planning for LTE cells provides benefits regarding the coverage performance of a particular grid in a specific area.MAPL is the amount of signal attenuation/weakening transmitted by the eNB.MAPL is divided into two, namely uplink and downlink.It can be determined from calculations using the formula: (2) Apart from using the equation above, MAPL can also be searched by utilizing the propagation model equation used in network planning, because MAPL is the same as the Lp value in the propagation model equation provided that the value of the cell radius to the UE (d) is already known and several components that make up MAPL in the equation above the exact value is unknown (Dikki Chandra et al,2020).
Mechanical tilting is done by physically changing the direction of the antenna tilt.The impact produced by this tilting is a change in the overall coverage area.In mechanical tilting, changing the direction of the antenna is done by changing the tilt angle located on the rear bracket of the antenna.Measurement of the degree of tilt can be done using a tilt meter.So, mechanical tilting is adjusting the direction of the antenna vertically up or down.The greater the degree of mechanical tilt, the more the direction of the antenna will be lowered, which will cause the coverage of the main lobe to decrease, while the side loob will be wider.(Pramono et al., 2020).
Mechanical tilt measurements can be made by referring to Figure 1 and the following formula:

Capacity and Network Service Quality Level
Telecommunications are most important for low-income countries, while transportation and energy are the most relevant for middle-income and high-income economies, respectively.Results about the Asia and Pacific region reveal infrastructure on telecommunications, roads, and energy generation to have been supportive of growth in the region (Yusoff et al., 2021).Mobile network operators are currently preparing the introduction of QoS differentiation mechanisms in their 3G networks, as a means to support servicespecific quality requirements, to enable the offering of distinct subscription forms, and/or to enhance resource efficiency and hence network capacity.Multiple copies of the packet decrease the time to offload the data to the destination, but increase the energy and storage used in the system (Markova et al., 2019)).Achievable performance gains were primarily observed at cell traffic loads exceeding the 'dimensioning load', although for some scenarios capacity gains of up to 8.6 % were found, compared to a case without QoS differentiation (Kassim et al., 2022).

Basic Parameters of 4G LTE Network
Network optimization is an activity carried out to improve cellular network performance.Optimization improves network quality making the best use of existing data.Here are some LTE network performance parameters: a. Reference Signal Received Power (RSRP) RSRP is the power received by the user in a certain frequency, the longer the distance between the site and the user, the smaller the RSRP received by the user.Users who are out of range will not get LTE service.The longer the distance between the site and the user, the smaller the RSRP value received by the user.RSRP KPI parameters are shown in Table 1.(Amanaf, M. A. et al, 2020)   b.Signal to Interference Noise Ratio (SINR) SINR is the ratio of the ratio of signal strength between the main emitted signal with interference compared to background noise that arises (mixed with the main signal).In the sense that the ratio is between the average power received and the average interference and noise.Telecommunications operators use this parameter in determining the relationship between radio frequency access conditions and user throughput.The parameter KPI SINR is shown in Table 2.

c. Throughput
Throughput is the amount of data sent or transmitted from source to destination per unit of time (bits per second/bps).2 types of throughput can be calculated, namely download and upload shown in table 3.

III. RESEARCH METHODS
This 4G LTE FDD network optimization planning research uses quantitative methods, namely by optimizing using link budget calculations.In this study, the technology used was LTE FDD.Data collection is carried out in the morning until noon, and the area is Lubuk Kilangan.This research will optimize Telkomsel operators using Atoll 3.3.0software on network quality sample data generated from drive tests.The flow chart of the stages to be carried out can be seen in Figure 2. The author does the regional route planning used in the case study that the author will examine, here the author takes data in Koto Tangah District, namely the Lubuk Minturun area.Regional planning is carried out using MapInfo Pro software which allows one to travel and learn about the virtual global world and is used as route design in the area to be collected data.Regional design is done by determining the path in the MapInfo Pro software, by activating the Cosmetic Layer then selecting Insert to make it easier to determine the path that will be used as a route to be passed in the data retrieval process.Here's a look at the route that has been designed and will be used in data retrieval as shown in Figure 3.

Figure 3 Route design in MapInfo Pro
After route planning is carried out, the next step is to take data in the case study area that has been determined to examine problems in the area.Data retrieval is done with TEMS Pocket software.TEMS Pocket software serves to capture network performance data both coverage and throughput parameters.The data is in the form of 4G LTE parameters including RSRP (Received Signal Reference Power) and SINR (Signal Interference Noise Ratio) as coverage parameters and Throughput as Integrity parameters.The data retrieval process is carried out using a 4G LTE network.
Drive Test is a data-gathering activity that involves monitoring radio signals received by users' smartphones in real-time, such as uploading and downloading, to assess cellular network performance and enhance network quality (Shakir et al, 2023), (Djomadji et al, 2022).This study employed drive test software, TEMS Pocket, and logfile data analysis tools, TEMS Discovery.LTE FDD with a frequency of 1800 MHz is the technology used.Logfile data is used to analyze the quality of FDD technology download results.The parameter employed is Reference Signal Received Power (RSRP), which is a parameter that indicates the signal strength (Power) received by the user at a given frequency (Bellary et al, 2022), (Rahmawati et al, 2022).There is also a Signal to Interference Noise Ratio (SINR) metric, which compares the signal power received with the interference power or noise generated by the service user (Viana et al, 2022).The Throughput parameter is the bit rate or the amount of data transmitted on a network in a unit of time (Wang et al 2019).Optimization is performed to improve network quality (Jacob and Darney, 2021), (Kato et al, 2019), with Atoll software based on data analysis during the test drive.

IV. RESULTS AND DISCUSSION a. Data processing of drive test results
The drive test results are in the form of log files produced from the results of data retrieval using the drive test devices and processed using drive test device-specific software (El Yumin, 2020), (Yuliana et al, 2019), (Alfian, 2021).The drive test yielded various parameters, including RSRP, SINR, and Throughput.The signal strength in the Lubuk Kilang area is dominated by yellow, as seen in Table 1.Based on the signal strength with the parameter values above, it can be seen that in the very poor category (RSRP <-110 dBm), 50 samples were obtained with a percentage of 5.72%, the bad category (-110 ≤ RSRP <-100 dBm) obtained 242 samples with a percentage of 27.67%, the quite good category (-100 ≤ RSRP <-85 dBm) receives 413 samples with a percentage of 47.25%, the good category (-85 ≤ RSRP <-75 dBm) receives 132 samples with a percentage of 15.1% and for the very good category (-75 ≤ RSRP <0 dBm) receives 37 samples with a percentage of 4.23%.From the existing KPI targets, as presented in label 4, this target was not achieved because there were only 582 samples and only 66.58% of the existing targets, namely >-100dBm as much as 90%.Table 5 shows that the SINR quality parameters consist of 874 samples.In the very bad category (-15 ≤ SINR <0), 230 data samples are obtained with a percentage of 26.32%, the quite bad category (0 ≤ SINR <13) obtains 511 data samples with a percentage of 58.47%, the good category (13 ≤ SINR <20) obtains 113 data samples with a percentage of 12.93% and the very good category (20 ≤ SINR <30) obtains 20 samples with a percentage of 2.29%.Table 6 shows that the very bad category (THP <512 Kbps) receives 123 data samples with a percentage of 14.14%, the bad category (512 ≤ THP <1,000) receives 12 data samples with a percentage of 1.38%, the quite good category ( 10,000 ≤ THP <7,000) receives 285 data samples with a percentage of 32.76%, the good category (7,000 ≤ THP <14,000) receives 419 data samples with a percentage of 48.16%, and the very good category (14,000 ≤ THP) receives 31 samples data with a percentage of 3.56%.Based on the percentage value of the number of samples, it can be seen that the Throughput value in this area is in the quite good category.
The BTS coverage area can be viewed in the RSRP coverage image, which displays values in blue, green, yellow, orange, and red.To view the received visualization is performed using Atoll software.The farther the range of the signal emitted, the worse the signal strength obtained by the user.

b. Optimization with Link Budget
After analyzing the drive test results, it was found several bad spots where the network quality was poor at several sites in the Lubuk Kilangan area, resulting in the site's performance being less than optimal, in terms of the direction of the beam and the tilt of the antenna had to be by the planning to minimize the occurrence of bad spots and optimize using the antenna tilting method.
Optimization based on this link budget is a stage that is carried out using data collected from the drive test results (Taqwa, 2021).This method of optimization yields good network performance services in terms of network coverage and quality in one location.Typically, network quality is poor, problematic patches occur in heavily populated places, or there are numerous impediments and interference problems.As a result, re-planning is required to alter the tilting of the antenna, as well as the tilt and direction of the antenna that is directly on the target.
In this study, we changed the antenna tilt by 3 degrees which gave increase transmit power.This area is still in bad condition since the transmit power from the RSJ Gadut site is 48.4 dBm, so the transmit power must be increased by 60 dBm to cover the bad spot area.
(5)  According to Table 7, the quality or level of power of fair (orange) category sites increased by 39.21 percent to 3.64%, while poor (red) category sites decreased by 2.58% to 0.29%.As demand for high-speed data continues to increase, optimizing throughput value will remain an important focus for telecommunications operators around the world.By keeping up with technology developments and emerging industry trends, operators can ensure that their networks are ready to handle the increasing demands of the digital era.

Signal to Interference and Noise Ratio (SINR)
Uncover the secrets to optimizing throughput value in 4G LTE infrastructure with lessons learned from an interesting case study in Lubuk Kilangan.By implementing the strategies and best practices outlined in this article, operators can lay the foundation for a future-proof, high-performance network infrastructure.

Figure 7 .
Figure 7. RSRP simulation results on Atoll (a) After Optimization (b) before Optimization

Figure 8 .
Figure 8. SINR simulation results on Atoll (a) After Optimization (b) before OptimizationTable 8. Before and After SINR Optimization with Link Budget

Table 7 .
Before and After RSRP Optimization with Link Budget RSRP (dBm)

Table 8 .
Before and After SINR Optimization with Link Budget study by comparing several types of antenna orientation, including tilt, depending on various factors such as the deployment scenario, coverage requirements, interference considerations, and the specific characteristics of picocells, femtocells, and repeaters.