Measurements and Analyses of 4G/5G Mobile Broadband Networks: An Overview and a Case Study

Abstract

Mobile data has become an integral part of everyday life, making Internet trends more and more profound and deeply embedded in life and the future. Mobile broadband (MBB) is one of the main aims of fifth-generation (5G) networks due to unprecedented growth in data demand. However, 5G networks are not yet deployed in many countries, whereas existing MBB networks, such as third generation (3G) and fourth generation (4G), are available in most world countries. As a result, there is a need to monitor and troubleshoot end-to-end network performance and ensure a better user experience. This paper provides an overview of MBB networks in terms of deployment environments, performance metrics, and implementation scenarios. It highlights the most important criteria for assessing MBB performance and the applications and measurement methods utilized, such as external and internal measurements and the classification of geographical areas. In addition, it provides measurement-based performance analyses of two existing mobile network operators (MNOs) (Omantel and Ooredoo) in the Sultanate of Oman. This performance analysis uses data measurements in various indoor and outdoor environments in five cities (Muscat, Ibra, Sur, Bahla, and Al kamil Wal Wafi). Several performance metrics are considered, such as signal level and quality, throughput, ping rate, and handover. Experimental results demonstrate that the 4G networks were the dominant networks in all measured locations for indoor and outdoor scenarios. Moreover, 5G data measurements are also recorded in the capital city of Oman, Muscat. The results of the 5G measurements show that both MNOs achieved a higher data rate with a lower ping rate.

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1. Introduction

Mobile networks have become a strategic infrastructure for the economy in many countries, so the increasing reliance of community members on mobile broadband (MBB) networks has posed significant challenges for service providers in terms of security and compliance. The challenges may include ensuring the provision of high-quality communication services, providing coverage, and increasing customer satisfaction experience in rural and urban areas [1, 2]. Mobile broadband networks provide deep-within buildings with high-speed and extremely responsive access throughout towns, cities, and villages. Customers expect high-speed access wherever they go, including at work, home, in their cars, and when travelling. This is because entertainment, communication, and information services are becoming more and more bandwidth-hungry. Meeting that demand presents operators with both difficulty and opportunity. MBB networks are perhaps the most significant component of the global communication infrastructure, supporting several crucial functions of contemporary society. Enhanced mobile broadband (eMBB) means to further improve the performance of user experience on the basis of the existing mobile broadband business scenarios, which is also the application scenario closest to our daily life. The user experience is transforming quicker and more responsive mobile broadband connections. A gigabit (4.5G or 5G) wireless link that can send data at 1 Gbps will be available to 2.5 billion people by 2025 [3]. A high-quality stream of high-definition video is expected to be delivered over MBB networks by 2025. As a result of enhanced network planning techniques, mobile video services will have similar coverage or even better coverage than phone services.

Applications and services based on the Internet have become an essential part of life; thus, broadband subscribers have sharply increased over the past years. Globally, the total number of mobile devices is predicted to reach 17.72 billion by 2024, up 3.7 billion from 2020 [4]. Internet users are increasing at a rate of 7.6% annually, equivalent to an average of 900,000 new users per day [5]. In contrast, with the increased number of users and mobile devices worldwide, the activities and jobs connected to the Internet will also increase. Therefore, performance and quality monitoring are becoming increasingly important for all stakeholders as the demand on current networks grows and users take Internet access for granted. A range of user devices, physical disabilities, mobility, and accessibility settings are all real impact measures of MBB performance [6]. Recently, MBB networks, such as third-generation (3G) and fourth-generation (4G) wireless technologies, are frequently used to access the Internet for various services, such as web browsing, video streaming, and gaming. These technologies enable customers to access mobile data with different Internet connection speeds. However, 4G networks are considered the most quickly growing networks that offer high-data rate for end-user consumers. Meanwhile, in terms of the current technology, fifth-generation (5G) cellular networks are the latest iteration of cellular networks and are expected to be one of the greatest dramatic emerging networks yet developed. The 5G technology promises to provide high-speed data, high-quality live streaming, and low latency compared to 4G networks. However, deployment of a large number of small cells increases interference and the number of handovers in heterogeneous networks (HetNets). Thus, mobility management strategies become critical to ensuring seamless communication as the user moves between cells [7–9].

In this regard, the existing 3G and the 4G (as MBB networks) still need improvements and optimization to satisfy the user’s experience. Thus, MBB providers should regularly monitor their networks’ performance to meet user satisfaction. Providing a good quality of service (QoS) to end-users also requires the deployment of cutting-edge technologies which support different types of services. However, the quality of experience (QoE) does not directly rely on radio technology, but it considers a user’s expectation in which higher performance increases expectation.

Most of the MBB research studies in the literature are carried out in certain countries, cities, and metropolitan areas (as we will see in the next section). Even though the performance of MBB services in many countries is less researched due to the lack of such research studies, research in this field can provide basic knowledge of network coverage within the country and quality in each region, which will be a reference for different communities and service operators. In addition, monitoring MBB networks improves user experience and service satisfaction. It strengthens the oversight role of telecommunication services, creating and enhancing competition among service providers within a country.

The work in this paper is divided into two parts: an overview of MBB and a case study. In the first part, we provide an overview of MBB networks in terms of deployment environments, performance metrics, and implementation scenarios. Several previous studies that were implemented in different counties are analyzed and discussed. However, the second part presents a case study that provides performance analyses of existing MBB networks in the Sultanate of Oman. Data measurements are collected from various indoor and outdoor environments in five cities in Oman. Several performance metrics, such as signal level and quality, throughput, ping rate, and handover, are discussed. It is worth noting that the findings of this study can mainly benefit researchers and service providers and regulatory bodies as follows: (i) will aid researchers and service providers in better understanding the complaints about MBB services in different countries and (ii) will aid regulatory bodies in each country to develop strategies, programs, and policies that will address the MBB industry’s potential needs in a particular place. The contribution of this paper can be summarized as follows:

(1) Based on the literature, this study provides a comprehensive overview of MBB networks in terms of deployment environments, performance metrics, and implementation scenarios. It highlights the most significant criteria for assessing MBB performance. In addition, it discusses several studies related to the performance evaluation of MBB networks in different countries worldwide

(2) The paper is based on field measurements that make it technically sound. It will assist regulatory bodies in developing strategies and assist researchers and service providers in better understanding complaints about MBB services in different countries

(3) Based on the findings from this study, the paper suggests several areas for future research work

(4) In addition, this work provides valuable information to customers to make the right decisions regarding purchasing MBB service

The remainder of this paper is organized as follows: Section 2 discusses several related studies of MBB networks in various countries. Measurement environments and network performance metrics are presented in Section 3. Section 4 provides a case study on the performance evaluation of Oman’s 4G and 5G networks. Section 5 concludes this work.

2. Related Studies and Contribution

In this section, several research works related to MBB services have been presented. In [10], in Taiwan, due to its low-cost MBB connectivity, the enhanced wireless technology of code division multiple access (WCDMA), which is known as high-speed downlink packet access (HSDPA) or 3.5G access, is widely used. It is a wireless network that uses HSDPA, a cell communication protocol that allows for downlink speeds of up to 14.4 Mbps. The findings displayed that the structure, information, and service quality of 3.5G MBB networks substantially impact customer loyalty and use. The most important aspect was determined to be the system’s efficiency. In [11], the authors conducted MBB measurements over a three-week period in Vienna, Austria. They used two MBB services, online browsing and file downloads, which were exploited in the background via traffic shaping. The measurement results showed that both approach and setup produce consistent results if carried out with caution. Other measurements for the MBB, in [12], were conducted by utilizing NoRNet for connecting to up to five separate 3G Internet service providers (ISPs). Regarding NoRNet, it is the world’s first open, large-scale Internet testbed for multihomed systems and applications funded by the Research Council of Norway. The measurement focused on QoS characteristics, such as bandwidth, loss, and delay. The findings shed light on what a multipath transport endpoint should expect—and how to deal with it effectively by using today’s MBB networks as transport routes. The authors focused on implementations in code division multiple access (CDMA) networks that have various QoS criteria. They looked at various transmission control protocol (TCP) efficiency metrics including throughput, round-trip times, and error rates, as well as the possibility of using bandwidth prediction to achieve server QoS. On the other hand, the paper focused on detailed measurements in operational 3G networks to determine temporal and spatial network characteristics as well as the effect of TCP efficiency on the application layer.

In another work, a pilot study was conducted to assess and evaluate user quality for cell phone applications in Pakistan [13]. It is being pumped into determining how unequal Internet service providers are delivered to end-users. A quality performance measurement was performed for an operator in Pakistan, where end-user performance and service quality of users were analyzed. In addition, bottlenecks in performance and the reasons that could lead to this were identified. This study has adopted several criteria, such as throughput, throughput variance, latency, loss rate, jitter, signal strength, measurement server, contextual data, and frequency measurements. The results showed the best performance for 3G and 4G networks, followed by Mobilink. In [14], the authors focused on mapping broadband infrastructure, an essential component of broadband growth strategies. A comparative study was conducted by carrying out measurements for all mobile operator networks under the same conditions. Several considered performance metrics included upload speed, packet loss ratio, latency, and jitter. After that, all the data were processed and checked. As a result, data from measurements that are considered implausible has been discarded. The work in [15] described the QoE concerning MBB network customers in Indonesia. Various criteria were identified for determining the level of operation and the QoE. The field data were collected at five different times: morning, daylight, afternoon, night, and midnight. The QoS was evaluated by several metrics, such as download and upload speeds, latency, jitter, packet loss, and network availability. The measurement evaluation results concluded that the development of MBB in Indonesia still needs more improvement. In [16], the authors presented field experiments with measurement instruments that recorded both broadcast and broadband transmission efficiency. The experiments were carried out in a setting that replicated real-life scenarios to ensure that the results were accurate for the proposed platform. According to the collected data, the platform will raise overall viewable time while lowering broadband data reception. As a result, it was reported that by mixing broadcast and broadband, the proposed platform would increase the viewing service rate while reducing the amount of broadband data reception. In [17], an enhanced security QoS module with a vertical multihoming and multistreaming framework for 5G mobile terminals is proposed. It can manage multiple tasks at the same time. Multiple radio networks safeguard connections and speed up multimedia services by delivering each object in a separate stream. This research paper introduced a security and QoS system that can provide high levels of security for various applications across high-speed MBB networks with guaranteed QoS provisioning. It proposed a new 5G multiple radio access architecture to exploit future security and QoS in the 5G and next-generation mobile broadband multiradio access technology (NGMB multi-RAT) networks. Advanced security and QoS provisioning and radio technology access (RAT) aggregation with vertical RAT aggregation are used to provide networks and multimedia facilities. Further, a short-term user activity prediction with massive MBB data in America is investigated in [18]. The authors used large MBB data to forecast short-term consumer behavior over two days. The results of the experiments illustrated some materials and time functions.

Additionally, in [19], a QoE assessment model has been developed for the upcoming 5G mobile technology. The model links the technical concern of QoS to the relevant 5G applications, such as enhanced MBB, ultrareliable and low-latency communications, and massive machine-style communications. Three deployment trials were used to define 5G scenarios. The model links technological interest in QoS to viable 5G applications, which refers to 5G infrastructure applications that support an enhanced multimedia broadband scenario. In [20], the authors analyzed the performance of 4G networks in Nigeria. Various performance indicators were evaluated, including signal-to-interference plus noise ratio (SINR), reference signal received power (RSRP), received signal strength indicator (RSSI), reference signal received quality (RSRQ), packet data convergence protocol (PDCP), and productivity. Data measurements were taken from three base stations allocated around the University of Lagos. It was taken into account that measurements have considered a constant altitude of about 1.5 meters at a distance of 1 km with a reference distance of 0.1 km. Analysis of using preemptive scheduling for MBB was presented in [21]. Impact on MBB performance was measured at the TCP level, with the throughput penalty and TCP round-trip time. The results demonstrated that 5G technology can multiply low latency communication (LLC) traffic and eMBB without needing to pre-reserve wireless resources for transient LLC data bursts.

In [22], the authors evaluated the performance of three mobile network operators (MNOs) across 4G and 3G mobile networks in an indoor environment. There are two types of MBB services used to evaluate the network performance: web browsing and video streaming. The data measurements were collected in three states in Malaysia: Klang Valley, Selangor, and Johor Bahru. In the same country, the authors in [23] studied the performance evaluation of MBB cellular networks in indoor and outdoor environments in a populated city. A new performance metric, handover, is added, which measures the number of handovers between 3G-To-3G, 3G-To-4G, 4G-To-3G, and 4G-To-4G. In [24], it used Kingston Transit to undertake a network survey in Kingston, Canada. A dataset of several client-side wireless network quality characteristics was collected using Android network monitoring the application of G-NetTrack Pro. The dataset comprises 30 one-hour public transport bus journeys taken at three different periods throughout the day. Then, the acquired data was analyzed and looked into the impacts of time and place on the network’s observed throughput and signal strength in this study. It was noted that the mean signal strength and throughput measurements were affected due to the increased traffic on the road and the increased number of active people on the bus.

Moreover, the work in [25] performed measurements and assessments of long-term evolution (LTE) networks in Nigeria. The network performance was evaluated by various indicators such as RSRP, RSRQ, RSSI, SINR, and throughput. These measurements covered three base stations with average heights of 25 meters. The test vehicle was driven to consider the actual road traffic conditions at a relatively medium speed of up to 30 km/h with uniformity, thereby reducing possible Doppler effects. In [26], the performance of MBB for nine mobile networks in Europe during the COVID-19 epidemic was investigated. The mobile performance was evaluated in terms of web QoE, TCP throughput, round-trip time (RTT), and RSRQ for 4G signal coverage. In [27], researchers confirmed that throughput in static circumstances is sensitive to the relative location of the measuring equipment owing to small-scale fading during driving tests using several measurements in a live LTE network. Measurement results have revealed that throughput disparities between close places may reach tens of Mbit/s. At the same time, small-scale fading patterns can remain constant over long periods, even in an outside setting, lasting up to 100 seconds. As a result, the static samples skew the overall distribution significantly article.

Furthermore, data measurements have been conducted in [1] to analyze the performance of 3G/4G MBB networks in rural areas in Malaysia. Measurement data were collected using MBB explorer for web browsing and SpeedVideo for video streaming. Four performance criteria were used, latency, speed, satisfaction, and coverage, to evaluate two types of services: web browsing and streaming video. According to the findings, the 4G networks delivered better coverage, reduced latency, more user satisfaction, and faster speeds. The research work in [28] performed measurement evaluation for certain MBB networks in Nigeria. Two cities were chosen as pilot measurements, and the measurements were carried out using a mobile phone application from a user-centric approach. The download and upload throughput were measured and evaluated for each MBB network. The measurement results showed that actual broadband speeds are lower than theoretical levels. More extensive measurements using remotely accessible Raspberry Pi-based modules would reveal the existing gaps in MBB utilization.

Also, the research in [29] analyzed and comprehended the MBB performance of national MNOs in Oman that supports 3G and 4G networks. A driving test was conducted in all urban and suburban areas of Muscat, Ibra, Sur, and Bahla. Several performance indicators were used to assess the network’s performance, including signal strength and quality, DL/UL throughput, ping rate, and handover number. The measurement results revealed that the MNOs in all cities had nearly identical signal and quality levels. The 4G networks were the dominating networks during the driving test. During the driving test, all MNOs operated well and maintained enough coverage and capacity. In [30], extensive work on MNO performance evaluation has been conducted in eight countries: the United States of America, the United Kingdom, France, Germany, South Korea, Japan, Singapore, and Australia. Most countries relied on MNO statistics on coverage and services or conducted public polls. Each country has its unique framework for measuring the performance of MBB services. The aforementioned related studies are summarized in Table 1.

Table 1

Summary of related studies.

Ref.	Country/cities	Type of study field	Type of measurement	Performance metrics	Name of application/SW-HW used	Number of operators	Technology
[10]	Taiwan	Urban	NA	(i) Net benefits.(ii) System quality.(iii) Information quality.(iv) Service quality.(v) Intention to use.(vi) Customer satisfaction.(vii) Customer net benefits.	D & M IS success model	(i) Chunghwa Telecom (CHT)(ii) FarEasTone (FET((iii) Taiwan Mobile and Vibo Telecom	3.5G access (HSDPA)
[11]	Vienna, Austria.	Urban	Dynamic	(i) Latency.(ii) Waiting times.	Application (VoIP, web surfing, e-mail, etc.)	FTW	3G
[12]	Norway (Oslo region of Norway)	Urban	Dynamic	(i) Throughput.(ii) One-way delays and RTT.(iii) Packet losses.	The NorNet Edge platform.NorNet Edge testbed	Four 3G-UMTS operators using identical USB 3G	3G
[13]	Pakistan (Islamabad, Lahore, Karachi, and Peshawar)	Urban	Dynamic	(i) Throughput.(ii) Latency.(iii) Loss rate.(iv) Jitter.(v) Signal strength.(vi) Measurement server.(vii) Contextual data.(viii) Measurement frequency.	Developed an Android application My Speed Test PK	Ufone, Telenor, Zong, Warid Mobilink	3G/4G
[14]	Russia (Latvia)	Rural	Static	(i) Upload and download speed.(ii) Latency.(iii) Jitter.(iv) Packet loss ratio.	Measurement location is marked in GPS (WGS84 coordinate reference system)	TwoOperatorsLMTTet	3G-4G-5G
[15]	Indonesia (Samarinda)	Urban	Dynamic	(i) Jitter.(ii) Download and upload speed.(iii) RTT.(iv) Packet loss and network.(v) Availability.	QOSE measurements through a variety of methods and techniques	Smart phones, iPhones, iPads, Android devices and Windows Phone	4G
[16]	Japan (Tokyo)	Rural	Dynamic	(i) Broadband BW by downloading.(ii) Reception quality.(iii) Broadband data reception.	Proposed a media unifying platform	NA	5G
[17]	Republic of Macedonia	Rural	Static	(i) Latency.(ii) Power.(iii) Reliability.	SecAQUA module	Two5G and NGMB networks	5G
[18]	America	Rural	Dynamic	(i) Location information.(ii) Type of user equipment.(iii) Type of subscription of the users.	(i) By visiting a website like the one of Ookla speedtest1(ii) Or by running a special measurement application	MMB networks	4G-5G
[19]	Indonesia	Rural	Dynamic	(i) Traffic volume density.(ii) Availability.(iii) Experienced user throughput.(iv) Reliability.(v) Energy consumption.(vi) Latency.(vii) Security.	Quality of service (QoS)	TwoAccording to ETSI, they are network operators	5G
[20]	Nigeria (Lagos)	Urban	StaticDynamic	(i) RSRP.(ii) RSRQ.(iii) RSSI.(iv) SINR.(v) Throughput.	MapInfo tool and analyzed in MATLABUsing Huawei technology drive test (DT) equipment	NA	4G LTE
[21]	Denmark (Aalborg)	Urban	Dynamic	(i) Penalty on throughput and smoothened TCP round-trip time to assess how preemptive scheduling affects the end-to-end performance of other traffic.(ii) Broadband (eMBB) and (LLC).	NR system	Telenor DenmarkTeliaTele DanmarkSonofon	5G3GPP
[22]	Malaysia (Selangor and Johor Bahru)	Urban	Static	(i) Cellular signal strength (CSS).(ii) Provided coverage performance.	MBB explorer application and speed video application	(i) Maxis(ii) Celcom(iii) DiGi	3G4G
[24]	Canada (Kingston, Ontario)	Urban	Dynamic	(i) Throughput.(ii) Signal strength.	G-NetTrack Pro	NA	NA
[25]	Nigeria (Lagos, smart city)	Urban	Dynamic	(i) Signal quality.(ii) Download throughput.(iii) RSRP, RSSI, RSRQ, SINR, throughput.	Software version-Genex prove V16 and Genex Assistance V16	Network operators in Nigeria	4G
[27]	Austria (Sankt Polten and Melk)	Urban and rural	Static and dynamic	(i) Throughput.	NA	NA	LTE800LTE2600
[1]	Malaysia	Rural	Dynamic	(i) Coverage.(ii) Latency.(iii) Satisfaction.(iv) Speed.	Using a software called Nemo Handy	(i) Maxis(ii) Celcom(iii) DiGi	3G4G
[26]	Italy, Sweden, Norway, and Spain	Rural, urban, and suburban	Dynamic and static	(i) Web QoE.(ii) Signal coverage.(iii) Throughput.(iv) RTT.	MONROE platform	9 mobile networks in Europe	4G
[2]	Malaysia (Klang Valley/Selangor, Johor, Sarawak, and Sabah)	Urban	Dynamic	(i) Coverage.(ii) Latency.(iii) Satisfaction.(iv) Speed.	MBB explorer application	(i) Maxis(ii) Celcom(iii) DiGi	3G4G
[28]	Nigeria (Eket and Uyo)	Rural and suburban	Dynamic	(i) Download and upload throughput.(ii) RSSI.(iii) RSRP.(iv) RSRQ.	Raspberry Pi-based	MTN, Globacom, Airtel, and 9Mobile	LTE4GHSPA+3G
[29]	Oman (Muscat, Ibra, Sur, and Bahla)	Urban and suburban	Dynamic	(i) Signal quality.(ii) Throughput.(iii) Ping.(iv) Handover.	G-NetTrack Pro	(i) Omantel(ii) Ooredoo	3G4G
[30]	(i) Australia(ii) France(iii) Germany(iv) Korea(v) Japan(vi) Singapore(vii) UK(viii) US	Rural and urban	Static and dynamic	(i) Coverage.(ii) Download/upload speed.(iii) Number of subscribers.(iv) Received signal strength.(v) Call success rate.	Coverage and services data provided by MNOsSurveyed the publicField survey by professional evaluators	(i) Australia: Telstra, Vodafone, and Optus(ii) France: Bouygues, Free, Orange, and SFR(iii) Germany: Deutsche Telekom AG (DTAG), Vodafone, and Telefonica Germany(iv) Korea: SK, KT, LG U+(v) Japan: NTT DOCOMO, KDDI, and SoftBank(vi) Singapore: Singtel, M1, and StarHub(vii) UK: EE, O2, Three, and Vodafone(viii) US: Verizon, T-Mobile, AT & T, and Sprint	(i) Australia: Comb.(ii) France: 3G, 4G, Comb.(iii) Germany: Comb., 4G(iv) Korea: 2G, 3G, 4G, Comb.(v) Japan: 3G, 4G, Comb.(vi) Singapore: 3G, 4G(vii) UK: 2G, 3G, 4G, Comb.(viii) US: 4G
This paper	(i) Oman (Muscat, Ibra, Sur, Bahla, and Alkamil & Alwafi)	Urban/suburban	Dynamic	(i) Signal level and quality.(ii) Throughput.(iii) Ping rate.(iv) Handover.	Gyokov Solutions “G-NetTrack” installed on two Samsung Galaxy smartphones	(i) Omantel(ii) Ooredoo	3G-4G-5G

3. MBB Background

The drive tests are essential for MNOs to assess their coverage and service quality. Therefore, this section provides a background on MBB in terms of measurement environments in which the measurements were taken and some performance metrics were used.

3.1. Measurement Environments

Measurement environment is divided into two types: outdoor and indoor. Figure 1 demonstrates the types of measurement environments.

[figure(s) omitted; refer to PDF]

3.1.1. Outdoor Measurements

These measurements are made in large open spaces such as city streets and require more time. The data collection process is done using driving tests using cars, buses, or trains at a certain speed (dynamic). Outdoor measurement environments are classified into three categories, urban, suburban, and rural, which depend on a group of people living with each other in a certain place where the population density in each area category varies. Also, the number of buildings varies in terms of space, nature, and place.

Urban: an urban community or so-called city with a high population density and continuously built with many buildings where the population in this area is estimated at more than 50,000 people or more

Suburban: a suburban community is an area outside the city with a moderate population density of 2,500 to 50,000 people. It has a good number of houses but few buildings and shops. Specifically, suburban communities are the municipalities and cities in metropolitan regions outside the political limits of the big city center. The vast, low-density land use, and a politically divided local government distinguish suburban towns from city center (urban)

Rural: a rural community is an open area defined by nature with a small population density estimated at less than 2500 people. It has few houses and buildings compared to suburban and urban areas

3.1.2. Indoor Measurements

These types of measurements are made in closed spaces within a particular building and take a shorter time than outdoor ones. There are two types of collecting data: walking on foot inside the place and fixed at a specific point for a certain period (static).

3.2. MBB Performance Metrics

Several performance metrics are used to analyze the performance of MBB networks. These metrics are mostly related to QoS and user experiences, which are explained as follows:

(i) SINR: signal-to-noise plus interference ratio measures the unwanted part of a received signal

(ii) RSSI: received signal strength indicator is a measurement of the power existent in a received radio signal

(iii) RSRP: reference signal received power measures the mean power received from a single reference signal in a specific bandwidth

(iv) RSRQ: reference signal received quality is the ratio of RSRP to RSSI multiplied by the number of resource blocks $\mathit{N}$ that the RSSI is measured on same bandwidth. It can be calculated as $\text{RSRQ}=N\ast \text{RSRP}/\text{RSSI}$

(v) Jitter: the differences in delay between point-to-points in a package in generated broadband connections. Also, it is known as a measure of the deviation from the average

(vi) Latency: also known as ping, it is defined as the time it takes for data to travel from a user’s computer to a server and back (an interval between stimulation and response)

(vii) Download and upload speed: download speed, also known as pick-up speed, is the speed at which the user’s computer receives files from the Internet, while upload speed, also known as transmission speed, is the rate at which a computer’s files are uploaded to the Internet by the user’s computer. Upload speed is usually faster than download speed

(viii) Packet loss: the loss of the package indicates the amount of data (number of packages) that does not reach its intended destination over the Internet

(ix) Network availability: the amount of time spent running a network operation in a given period of time

(x) Throughput: it is the rate of successful data delivery through a communication channel. The closest user to the base station is more productive than the farthest user

(xi) Handover: it is a process of transferring cellular transmission (voice or data) from one base station (cell site) to another without losing connectivity to the cellular transmission

(xii) Bandwidth: it is the amount of data that can be transferred from one point to another within a network in a specific amount of time

(xiii) Information quality: it is a set of qualitative characteristics that the accounting information must have in order to be of benefit to the parties benefiting from it, and these characteristics differ from one institution to another, with unanimity on four characteristics: suitability, reliability, consistency, and comparability

(xiv) Service quality: it is an indicator of how a service meets a customer’s expectations. In order to enhance their services, promptly discover problems, and better gauge customer satisfaction, commercial operators or service providers frequently score the quality of the service they deliver to their consumers

(xv) Security: it is an idea that has been implemented to protect programs from malicious attacks and other piracy risks so that the program continues to work properly in light of these potential risks

(xvi) Reliability: it is the ability of a product or system to perform a specific function, and it is either design reliability or operating reliability. Availability is the ability of a system to remain in working order

(xvii) Loss rate: it is the ratio of the total number of winning trades to the number of losing trades. It does not take into account how much was gained or lost but simply if they were winners or losers

Table 2 shows the common performance metrics used in the related works in Table 1. The most common performance metrics are throughput (download and upload speeds), latency, and signal strength.

Table 2

MBB performance metrics.

Ref.

Performance metrics

Throughput

Latency

Loss rate

Jitter

Signal strength

Coverage

Satisfaction

Handover

RSRQ

RSSI

SNR

Reliability

Availability

Energy consumption

Security

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4. A Case Study of 4G/5G Measurements

4.1. Background

The MBB is important in improving quality of life, increasing productivity, and contributing to the country’s economic growth. Generally, it also enriches the lives of citizens in various educational, health, safety, and other aspects. This contributes to strengthening the investment environment and creating business opportunities. Specifically, the MBB contribution reflects positively on the advancement of economic development in Oman by the goals of the future vision of the Omani economy in 2040. As a result of the increase in the population in the Sultanate and the number of devices connected to the network, two national operators formed the main MBB networks in the Sultanate: Omantel and Ooredoo. This work is an extension of our previous work in [31], where MBB networks were investigated in only one city (Ibra city).

4.1.1. Omantel

Oman Telecom (Omantel) is the first country’s telecommunication provider in the Sultanate. It aims to cover the various regions of Oman by its geographical nature and population density. Also, it covers busy areas such as major cities by fiber optic cables and 4G technology for consumers at very high speeds, while rural areas are covered by satellites and towers to strengthen operator networks in providing broadband services in those areas. Omantel is seeking to expand 4G and 3G communication networks, with a total of about 4,398 stations in various provinces of Oman. In 1996, the business developed 2G GSM over 900 MHz. In March 2009, it debuted 3G (Universal Mobile Telecommunications Service (UMTS)) services over Band-1 (2100 MHz). In 2011, Omantel’s 3G network was upgraded to HSPA+. In December 2013, Band-8 (900 MHz) was introduced in some regions. The first 4G LTE service was launched in July 2012, with a TDD Band-40 (2300 MHz) service. The network was expanded in December of the same year with a Band-3 (1800 MHz) carrier. Omantel announced the commercial debut of LTE-Advanced in April 2015, with theoretical peak downlink speeds of up to 200 Mbps. In August 2015, the corporation obtained an additional Band-7 (2600 MHz) and Band-20 (800 MHz) spectra. It increased the coverage rate in Oman to make it among the highest in the world. The coverage of the 2G, 3G, and 4G networks in populated areas is 96.40%, 99.38%, and 94.76%, respectively. Figure 2(a) displays the Omantel coverage map for different areas in Oman [32]. According to the newest assessment by “Open Signal” to cover mobile communication networks worldwide and assess network performance, Oman has the fastest 4G network in the Arab world. As the country’s largest and most dependable national network, Omantel is also trying to reach the greatest level of subscriber satisfaction.

[figure(s) omitted; refer to PDF]

4.1.2. Ooredoo

Ooredoo started, in Oman, by providing fixed and MBB services in various areas in 2010. According to 2020 statistics, it serves roughly 2.6 million consumers as an integrated service communication operator [33]. Figure 2(b) shows the Ooredoo coverage map for different areas in Oman [32]. Ooredoo has received several accolades, including the Best Telecommunications Company at the Arab Achievement Awards 2016 and the Best Network Operator at Telecoms World Middle East [34]. In March 2005, Ooredoo Oman began offering 2G GSM services on the 900 MHz frequency. The network was updated to enable HSPA in July 2008 and DC-HSPA+ in March 2013, while 3G UMTS services commenced in December 2007 with the deployment of Band-1 (2100 MHz). Ooredoo deployed a second 3G carrier shortly after, providing a Band-8 (900 MHz) HSPA+ network for better coverage. In February 2013, Ooredoo Oman received an 1800 MHz spectrum and launched its first commercial LTE service utilizing Band-3 (1800 MHz). Also, Band-40 (2300 MHz) has rearmed its WiMAX deployment. The business reported in May 2015 that the network had been upgraded to LTE-Advanced (4.5G) with peak data speeds of up to 200 Mbps.

The key goal from this background is to explore the nation’s coverage in Oman by the various generations of mobile communication technologies to deliver MBB services. Accordingly, measurement campaigns were conducted to analyze the performance of MBB services in indoor and outdoor environments. Again, the main aims of the measurements and their analyses are to provide a deep understanding of policymakers and enhance competition among MBB providers in Oman, particularly on factors that can increase service efficiency, improve quality, and increase user satisfaction [2]. It also strengthens the oversight role of telecommunication services to improve the telecommunication services provided in Oman.

4.2. Methodology

In this study, measurement campaigns were conducted by the drive and walk tests for outdoor and indoor environments, respectively, in five cities: Ibra, Muscat, Sur, Bahla, and Al kamil Wal Wafi. The data collection was carried out by using two smartphones with the model “Samsung Galaxy A32 5G” powered by Android with identical specifications and settings used for data collection. Figure 3 displays the methodology of data collection. The smartphones collected the data measurements from base stations and then stored them in a log file. The tested networks were simultaneously measured at each testing city to ensure a fair comparison of the two MNOs. The same amount of data was collected for MNOs in each city. Table 3 displays the collected samples for indoor and outdoor scenarios. The data measurements were carried out on a commercial android application developed by Gyokov Solutions called “G-NetTrack” installed on two mobile devices with the Samsung Galaxy brand [35].

[figure(s) omitted; refer to PDF]

Table 3

Collected samples during measurements.

City	Indoor	Outdoor
Muscat	6471	12038
Ibra	4372	8810
Sur	6318	12280
Bahla	7398	11868
Al kamil Wal Wafi	7631	12286

In this case study and for the sake of protecting the identity of the service providers of Oman and associated results, the names of these providers are coded as OP1 and OP2. For the drive test, the smartphones were fixed in a car using a mobile phone holder. The car’s speed was limited to 70 km/h for all outdoor tests in areas selected to minimize the fast-fading effect due to the Doppler shift. Figure 4 displays the outdoor drive test route and indoor measurements in August 2021. The orange color represents the measurement tracks of the drive test, whereas the black circles indicate the walk test in indoor environments. After completing data measurements, general information about a serving network was saved in the log file during the drive test. Table 4 summarizes performance metrics used in the G-NetTrack application and the units of measurement used in general and in the application.

[figure(s) omitted; refer to PDF]

Table 4

Performance metric record.

No.	General			G-NetTrack
	Performance metric	Definition	Unit	Performance metric	Definition/remarks	Unit
1	Reference signal received power (RSRP)	Measurement of the mean power received from a single reference signal in a specific bandwidth.	dBm	Level	Level–the current signal strength in dBm	dBm
2	Quality	The amount of good data received and delivered by the low-noise block-down converter. As a result, high signal quality entails a clear picture and sound with no interruptions.	dB	Quality	Quality–the signal quality of the network	dB
3	Channel quality indicator	Metric that indicates how excellent or terrible a communication channel’s quality is. The CQI value ranges from 0 to 15. This reflects the UE’s modulation and coding capabilities.	Unitless	CQI	CQI–channel quality indicator. It is measured on 4G only	Unitless
4	Received signal strength indicator	Is a measurement of the power existent in a received radio signal	dBm	RSSI	RSSI–received signal strength indicator	dBm
5	Ping	The amount of time it takes for data to travel from a user’s computer to a server and back.	ms	Ping	Ping–ping time is measured in milliseconds	ms
6	Throughput	UL: the speed at which the user’s computer receives files from the Internet.	Bits/second	UL	UL–the current uplink data transfer speed	kbps
		DL: the rate at which a computer’s files are uploaded to the Internet by the user’s computer.	Bits/second	DL	DL–the current downlink data transfer speed	kbps

4.3. Results and Discussion

The results given in this study are based on the time and cities where data measurements were obtained. The performance of MBB is evaluated by analyzing the six performance metrics mentioned in Table 4.

4.3.1. Signal Level

Figure 5 shows the MBB measurement results of the received signal level in indoor and outdoor environments for the five cities. The received signal level is presented in negative values, where the lowest value is the better. Also, it is observed that the MBB measurements of some technologies for both operators were not obtainable. For instance, it is noticed that the OP2 3G was not captured in Muscat and Bahla. For the outdoor measurements, the 4G signal level for OP1 in Ibra achieved about -84.89 dBm is slightly better than all the other cities. As well as, in terms of average signal level, Bahla is the best for OP1 3G, and Sur is the best for OP2 3G. In indoor measurements, both OP1 and OP2 in 4G achieved the best signal level of -74.41 dBm and -89.87 dBm in Muscat, respectively. However, the 3G in OP2 in Sur city achieved the best signal levels of -73.4 dBm.

[figure(s) omitted; refer to PDF]

4.3.2. Signal Quality

Figure 6 illustrates the signal quality in indoor and outdoor environments for all five cities. It is observed that the MBB measurements of some technologies for both operators were not obtainable. For instance, it is noticed that the OP2 3G is not captured in all cities except Al kamil Wal Wafi for the indoor scenario. Similarly, the OP1 3G is not captured in all cities except Sur city for the indoor scenario. For 4G outdoor measurements, the MBB services delivered in Muscat achieved the best signal quality in all five cities at about -9.28 dB and -10.03 dB in terms of OP1 and OP2, respectively. For 4G indoor measurements, the signal quality in Bahla outperforms other cities at about -2.74 dB and -6.11 dB in OP2 and OP1, respectively.

[figure(s) omitted; refer to PDF]

4.3.3. CQI

As shown in Figure 7, the MBB measurement results of the performance metric CQI for all five cities are integrated and jointly presented. It is observed that the MBB measurements of some technologies for both operators were not obtainable. For instance, it is noticed that the OP2 3G is not captured in all cities except Al kamil Wal Wafi, and the OP1 3G also is not captured in all cities except Sur. Also, OP2 3G is not captured in Alkami & Alwafi outdoors. For the 4G outdoor measurements, the CQI level is higher in Ibra for OP1, which is 10.79, whereas in OP2, in Al kamil Wal Wafi, it achieved about 11.39 better than other cities. However, in 4G indoor measurements of the CQI values, the highest value for OP1 was in Sur at about 9, while in OP2, Muscat is the best and gets approximately 12.19.

[figure(s) omitted; refer to PDF]

4.3.4. RSSI

Similarly, Figure 8 shows the RSSI for all five measured cities for indoor and outdoor scenarios. The lower negative values indicate better RSSI. It is observed that only 4G networks were captured in all cities for the outdoor scenario, and 3G networks were only captured in Sur and Al kamil Wal Wafi for the indoor scenario. And OP2 3G is not captured in Al kamil Wal Wafi outdoor. For 4G outdoor measurements, the RSSI of both OP1 and OP2 is almost similar in all cities. For 4G indoor measurements, OP1 achieved better RSSI with a value of -68.53 dBm in Muscat, whereas OP2 achieved much better RSSI with a value of -52.39 dBm in Bahla.

[figure(s) omitted; refer to PDF]

4.3.5. Ping

The average ping with a confidence interval for all five cities is shown in Figure 9. The ping is represented in milliseconds (ms), where a lower value indicates better performance. It is observed that both operators recorded the ping for 4G networks in indoor and outdoor scenarios. However, in indoor measurements, it is noticed that the 3G networks are captured for both operators only in Sur city and Al kamil Wal Wafi city, whereas only 3G network OP2 is captured in the city of Ibra. For 4G outdoor measurements, OP2 achieved the shortest ping time in all measured cities compared to OP1. The OP1 recorded the longest ping of 316.12 ms for outdoor measurements in Al kamil Wal Wafi. Regarding 4G indoor measurements, OP1 obtained the shortest ping of 29.28 ms in Muscat, whereas both operators, OP1 and OP2, achieved a longer ping of 836.18 and 351.25 ms in Sur and Al kamil Wal Wafi, respectively.

[figure(s) omitted; refer to PDF]

The 95% confidence interval estimates the degree of certainty or uncertainty regarding the estimated difference between the variables. For instance, indoor measurements produced a wider confidence interval for both operators in Sur and Al kamil Wal Wafi. The indoor measurements obtained a confidence interval of (376.3, 1273.8) and (1003.7, 2284.0) for OP1 and OP2 in Sur Al kamil Wal Wafi, respectively. In contrast, outdoor measurements produced the narrowest confidence interval in most of the tested cities. It can be noted that there is a difference in the confidence intervals between the two operators, despite the fact that the same sample size was collected for both operators in each city. Table 5 shows the CI of ping for all measurement scenarios.

Table 5

Confidence interval of ping for indoor and outdoor 4G measurements.

City	OP1				OP2
	Outdoor		Indoor		Outdoor		Indoor
	Lower CI	Upper CI	Lower CI	Upper CI	Lower CI	Upper CI	Lower CI	Upper CI
Ibra	46.0	50.4	111.1	164.7	38.9	44.5	53.4	111.2
Muscat	37.8	56.1	27.2	31.4	32.9	38.8	115.1	233.5
Bahla	108.8	148.9	59.8	63.9	37.5	41.3	42.7	68.3
Sur	48.4	51.0	376.3	1273.8	26.3	50.0	95.4	277.9
Alkamil & Alwafi	251.9	380.3	1003.7	2284.0	36.1	99.4	339.6	897.6

4.3.6. Throughput

Figure 10 illustrates the throughput with a confidence interval for all five cities in indoor and outdoor environments. It was also noticed that MBB measurements were not obtained for some mobile technologies for both operators. For example, it is noticed that OP2 3G did not pick up at all cities except in Ibra, Sur, and Al kamil Wal Wafi for indoor measurement. Also, OP1 3G is not captured in all cities except Sur and Al kamil Wal Wafi. It is observed for outdoor measurements of 4G that the maximum DL and UL speeds recorded at OP1 in Sur are slightly better than that in the other cities, but the average DL and UL speeds in Ibra are the best. For OP2 4G outdoor measurements, in terms of DL, Ibra gets about 20900 kbps, which is the best average value, and it also gets a maximum speed.

[figure(s) omitted; refer to PDF]

Regarding UL, the best average speed is in Muscat, and the maximum speed obtained is in Bahla. In indoor measurements in OP1, Muscat outperforms other cities in the 4G network with a value of approximately 15630 kbps, and Al kamil Wal Wafi is much better than Sur in the 3G network performance. Regarding OP2, it was noted that DL speed is the best in Muscat, and UL speed is the best in Bahla by 4G network. Still, in general, Al kamil Wal Wafi is almost the best in terms of maximum DL and UP achieved, which are 8333 kbps and 4000 kbps by the 3G network, respectively.

The 95% confidence interval for indoor measurements for both operators produced a wider confidence interval in Ibra and Muscat. Muscat and Ibra obtained a wider confidence interval for DL with (11009.5, 21770.2) and (2449.7, 6797.9) for OP1 and OP2, respectively. In contrast, the narrowest confidence interval was obtained by DL outdoor measurements for OP1 (865.6, 988.9) in Muscat. Table 6 demonstrates the CI of throughput (DL/UL) for all measurement scenarios.

Table 6

Confidence interval of throughput for indoor and outdoor measurements.

		OP1				OP2
		DL		UL		DL		UL
		Lower CI	Upper CI	Lower CI	Upper CI	Lower CI	Upper CI	Lower CI	Upper CI
Ibra	Outdoor	7278.5	11245.1	14999.1	16083.3	17738.7	24061.8	13379.4	14215.8
	Indoor	2449.7	6797.9	2871.7	4881.7	9059.8	17630.1	10182.7	12136.5
Muscat	Outdoor	865.6	988.9	12437.9	13095.2	6979.6	7981.7	14794.8	15484.4
	Indoor	11009.5	21770.2	15021.0	16239.5	9733.9	17021.0	9502.1	10786.8
Bahla	Outdoor	3450.4	4091.7	6704.0	8213.5	5880.6	6577.8	14767.3	15317.4
	Indoor	5314.3	7626.2	12224.6	13317.4	6211.3	9113.7	13465.0	14721.2
Sur	Outdoor	6027.4	9476.8	13106.0	14210.2	9830.7	13233.5	13347.7	14080.1
	Indoor	3058.0	5997.6	3901.3	5413.9	3575.9	6659.0	7493.2	9090.5
Alkamil & Alwafi	Outdoor	3835.5	6140.5	2276.7	3186.7	6223.1	8529.3	12436.3	13513.8
	Indoor	6288.8	8623.7	765.4	3097.4	3568.4	5318.3	4416.1	5413.7

4.3.7. Summary of Measurement Results

As a result of the outdoor measurements of the five cities for all performance metrics, Table 7 is tabulated. The OP1 with the 4G network was the best for four performance metrics (signal level, CQI, and throughput (DL and UL)) in Ibra. However, in Muscat, OP2 performed well for three performance metrics (signal quality, ping, and UL speed).

Table 7

Summary of the best-performed metrics in the outdoor measurements.

KPI

Ibra

Muscat

Bahla

Sur

Alkamil & Alwafi

OP1

OP2

OP1

OP2

OP1

OP2

OP1

OP2

OP1

OP2

3G

4G

3G

4G

3G

4G

3G

4G

3G

4G

3G

4G

3G

4G

3G

4G

3G

4G

3G

4G

Level

✓

✓

✓

Quality

✓

✓

CQI

✓

✓

RSSI

✓

✓

Ping

✓

✓

Throughput

DLUL

DL

UL

Table 8 summarizes the best performance metrics for indoor measurements in all measured cities. It shows that OP2 performed well in Muscat and Bahla, whereas OP1 is the best in the four metrics in Muscat. However, both operators experienced poor performance for all metrics in Ibra city.

Table 8

Summary of the best-performed metrics in the indoor measurements.

KPI

Ibra

Muscat

Bahla

Sur

Alkamil & Alwafi

OP1

OP2

OP1

OP2

OP1

OP2

OP1

OP2

OP1

OP2

3G

4G

3G

4G

3G

4G

3G

4G

3G

4G

3G

4G

3G

4G

3G

4G

3G

4G

3G

4G

Level

✓

✓

✓

✓

Quality

✓

✓

CQI

✓

√

RSSI

✓

✓

Ping

✓

✓

Throughput

DLUL

DL

UL

4.4. 5G Technology in Oman

The Sultanate of Oman began commercially providing telecommunication services to the 5G network in December 2019. During the years 2020 and 2021, the mobile Internet service for the 5G network was launched, but the subscriber’s access to the service depends on the type of the subscriber’s device and the package to which he was subscribed, as the network cannot be used in all devices, even if the device supports the 5G technology. Oman Telecommunications Regulatory Authority (TRA) allocates frequency band 3400-3700 MHz to the licensed MNOs to be used for 5G networks with a bandwidth of 100 MHz for each MNO. Omantel and Ooredoo are allocated with frequency bands of 3400-3500 MHz and 3500-3600 MHz, respectively. Recently, both operators have deployed their 5G networks at the nonstandalone stage. Also, tests to measure the number of connections between the server and the client showed that speeds reached 765.37 Mbps over 5G in Oman during the first quarter of 2020 [36]. The Omani capital, Muscat, ranked eighth globally with a speed of 318.95 Mbps with 5G technology during the first to second quarter of 2021 using the Speedtest Intelligence [37]. This is according to a report issued by Ookla, which specializes in measuring Internet speeds. The 5G networks were added on a larger scale in the Governorate of Muscat, central Oman. We carried out an experimental outdoor measurement to evaluate the performance of the 5G network on a long path that includes different places in the Governorate of Muscat, as shown in Figure 11. The network performance was evaluated by four performance metrics: signal quality, handover, ping, and throughput. The amount of collected data during the measurements is 14231 samples in May 2022, where 5084 samples were recorded for 5G networks.

[figure(s) omitted; refer to PDF]

4.4.1. Signal Quality

Figure 12 shows that the average signal quality for OP1 is slightly better than OP2, but both operators achieved maximum and minimum values of -3 dBm and -20 dBm, respectively. The signal quality and level are the key metrics for cellular systems used by mobile operators to determine the relationship between radio link conditions and throughput.

[figure(s) omitted; refer to PDF]

4.4.2. Handover Rate

Handover rate is an important key concern in the implementation of mobile-cellular networks. A higher handover rate may cause degradation in network performance. These factors directly impact communication quality in terms of extended interruption times and throughput deterioration [38–40]. There are two types of handovers between radio access technologies: intrafrequency and interfrequency. Intrafrequency handover occurs when the radio link is handed over to a target base station that operates with the same technologies, whereas interfrequency handover occurs when the radio link hands over to a target base station that operates with different technologies. Figure 13 illustrates the handover number over 4G and 5G networks for the two operators. The intrahandover for 4G-4G and 5G-5G in OP1 recorded a high handover number compared to OP2. In addition, OP2 achieved fewer handovers than OP1 in interhandover 4G-5G and 5G-4G.

[figure(s) omitted; refer to PDF]

4.4.3. Ping

Ping measures the reaction time of speed connection and is recorded as ping count. It is usually measured by sending a small amount of data (from an end-user to an application server) and receiving a response (from an application server to an end-user), where a lower ping rate is better than a higher rate. The ping time for 4G and 5G networks is practically below 100 ms and 30 ms, respectively. Figure 14 shows the average ping for the two operators. Both mobile operators achieved an average ping rate lower than 50 ms. The 95% confidence intervals for both operators are very close, with a CI of (33.4, 37.4) and (16.8, 19.8) for OP1 and OP2, respectively, due to the evenness data size of the sample that was taken.

[figure(s) omitted; refer to PDF]

4.4.4. Throughput

The most important performance metric is the data rate which evaluates the Internet speed of cellular networks. Figure 15 illustrates the overall average speed for operators OP1 and OP2. It can be observed that OP2 recorded an average throughput of approximately 17913.2 kbps, whereas OP1 achieved a data rate of 8309.2 kbps. The confidence intervals for OP1 and OP2 are (17262.8, 18563.5) and (4645.5, 11972.8) for OP1 and OP2, respectively. It is observed that the 95% confidence interval for OP1 is narrower than OP2. Table 9 demonstrates the CI and confidence level of ping and throughput for 5G measurements.

[figure(s) omitted; refer to PDF]

Table 9

Confidence interval of ping and throughput for 5G measurements.

	OP1		OP2
	Ping	Throughput	Ping	Throughput
Lower CI	33.4	17262.8	16.8	4645.5
Confidence level	1.9	650.3	1.5	3663.6
Upper CI	37.4	18563.5	19.8	11972.8

The throughput also depends on the usage of spectrum efficiency of mobile networks. The spectrum efficiency is increasing as mobile technology advances from 3G to 4G, 4.5G, and 5G [41]. Thus, the network transmission rates may be increased by many times using multiantenna technology. Technologies using multiple antennas, such as $4\times 4$ multiple input, multiple outputs (MIMO), and even higher-order massive MIMO, are already mature and have produced extremely high-throughput rates. In contrast to mobile phones, customer premise equipment (CPE) has no size or power consumption restrictions and is not required to offer display or call features; hence, advanced technologies may often be implemented on CPE at an early stage of development. End-to-end commercial solutions are now possible because of the availability of $4\times 4$ MIMO CPEs with the introduction of $4\times 4$ MIMO commercial processors.

4.5. Discussion and Limitations

4.5.1. Future Insight

Oman has established a strategy for its economic growth, similar to many of its neighbours in the Gulf Cooperation Council (GCC), as it seeks to diversify its economy from its dependence on oil and achieve sustainable growth. As part of the Oman 2030 plan, high-speed, high-density 5G network infrastructure is key in enabling digital literacy and skills, e-government adoption, and digital transformation of Omani industry. Commercial consumer-based 5G networks are already operational across Oman. The next wave of 5G deployment will enable individuals and businesses to realize the benefits of increased flexibility mobility, security, and reliability. As sophisticated ICT markets, such as Oman, boost their demand for new use cases enabled by expanded MBB capabilities enabled by the power of 5G, Ericsson forecasts that 5G mobile subscribers in the GCC will approach 62 million by the end of 2026. With almost 73% of total mobile subscribers, the GCC will have the second-highest 5G penetration. With a particular emphasis on artificial intelligence (AI), Oman’s Oman Digital 2030 plan strives to prepare its workforce, both in the private and public sectors, for the consequences of technology and the digital revolution [42]. With extremely low latency and high throughput, users can enjoy immersive gaming, augmented reality, virtual reality, cloud gaming, and much more. eMBB will be one of the first 5G applications to target customers, particularly with new services and experiences. 5G will open up new chances for operators to embrace new business models and create new services, apps, and income streams. These new 5G applications and services are projected to have a significant influence on the digitization of consumers, organizations, and industries. In addition to enabling remote management of large machines, 5G delivers the low latency and high reliability needed to manage vital services and infrastructure. All things considered, 5G technology will increase business potential by enabling monitoring, tracking, and automation on a massive scale, from linked farms and agribusiness to smart cities and buildings.

The business to business (B2B) and business to customer (B2C) experiences must be greatly improved as part of the transformation [43]. With the maturation of technologies such as Big Data and AI, telecom operators now have a significant potential to revolutionize how their consumers experience their goods and services by designing richer, simpler, immersive, and contextualized user experiences. In this setting, firms must manage and provide “digital experiences” across tools, devices, and places in order to meet and exceed their consumers’ expectations.

The research will be helpful to anybody who wants to comprehend the possibilities and changes that 4G and 5G technologies will bring about in a variety of industries in Oman. It benefits several sectors, including Internet and telecommunications, commercial entities, investors, governmental bodies, and research institutes. This study will assist these organizations in developing a thorough grasp of the subject throughout Oman.

4.5.2. Limitations

A number of limitations have not been covered in this study, and those limitations can be taken into account in future studies as follows:

(i) Field measurements were limited to specific areas and a short period. The performance was not representative of all morphologies; for expanding the scope of research and measurement, it is possible to measure in other different regions, including rural, suburban, and urban areas, and increase the period of each region

(ii) The measurements were taken in one period of time and most during peak hours, and the network performance was not assessed with diverse climatic conditions. Thus, the driving test can be performed during peak hours and out of peak and can be extended further to multiple, longer drive tests for each area

(iii) The data was collected using a car that travels at a speed of less than 70 km/h. As a result, many mobility scenarios can be made, such as high, medium, and low speeds. This may lead to more information about the network performance in terms of the user’s transfer

(iv) This case study focused on the current MB networks (3G and 4G) due to the lack of 5G at the time of taking measurements which is only measured in one city. Therefore, it is useful for the current case study to be expanded the 5G measurements in several cities

(v) MBB services and performance metrics were analyzed in this study using the most common performance metrics used by MNOs. However, several MBB services, such as video streaming and web browsing speeds, can be considered for further investigation. A number of factors related to mobile subscribers are absent from this study, including traffic management policies, customer service, data allowances, billing, and price

(vi) More studies should investigate the fair usage policy, which refers to the agreement between MNO and customers (subscribers). The policy ensures that all customers have a good experience; however, it can affect the user experiences regarding sharing bandwidth. The number of subscribers sharing a connection is called the “contention ratio,” which measures the subscribers’ ratio per unit of bandwidth, where a lower ratio indicates high QoS. Thus, the user experiences slow connection when sharing connections with other users simultaneously

(vii) Third MNO Vodafone is already in operation, which assists and improves MBB for all Oman regions. Adding work that includes measurements for all three main service operators in Oman is useful

5. Conclusion

This study provided an overview of MBB networks in terms of deployment environments, performance metrics, and implementation scenarios. It also highlighted the most significant criteria for assessing MBB performance. In addition, a case study of performance analyses of two existing MNOs in the Sultanate of Oman is presented. In the case study, data measurements were carried out in indoor and outdoor environments in five cities for two MNOs. It also discussed several studies related to the performance evaluation of MBB networks in different countries. Several performance metrics have been employed to evaluate the performance networks: signal quality, ping, data rate, and handover rate. Also, the recent implementation of 5G networks has been analyzed in the capital city of Oman in terms of signal quality, data rate, and handover rate. The measurement results demonstrated that most of the measured cities experienced 4G network coverage. The 3G networks are mostly presented in indoor and outdoor environments in Al kamil Wal Wafi. Furthermore, 5G networks have been evaluated for the outdoor environment in Muscat city. The 5G throughput achieved a high data rate with a lower ping rate. Finally, several future insights and limitations have been discussed for future work. In addition, this work provided useful information to consumers to make the right decision for purchasing MBB service.

Acknowledgments

The research leading to these results has received funding from The Research Council (TRC) of the Sultanate of Oman under the Block Funding Program with agreement no. TRC/BFP/ASU/01/2019. This study was also sponsored by the Universiti Teknologi Malaysia through the Professional Development Research University Grant (No. 05E92).

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