Lower Inclination Orbit Concept for Direct-Communication-To-Satellite Internet-Of-Things Using Lean Satellite Standard in Near-Equatorial Regions

Abstract

This research proposes a low-inclined orbit concept and design for the Internet-of-Things (IoT) using lean satellite standards in near-equatorial regions. The study aims to evaluate the coverage of various inclination angles at various latitudes and inclination angles in order to determine the most suitable satellite design for providing IoT coverage in these regions. The main methods applied in the study included analyzing the coverage performance of different inclination angles, the link budget analysis using simulations and the definition of the mission criteria. The results of the study show that the overall coverage performance decreases with an increase in the inclination angle. Satellites with lower inclination angles have ground tracks that are more closely aligned with the equator, while satellites with higher inclination angles have ground tracks that are inclined further toward the poles. In addition, the results show that the fraction of orbits with coverage (expressed as a percentage) declines with increasing latitude. Based on these findings, a low-inclined orbit of 24° provides the best coverage for IoT in near-equatorial regions within ±20 and 26° latitude, with a peak coverage of 27% at 24° latitude and a minimum coverage of 10% in the region spanning from 0° to ±27° latitude. This design offers more coverage time and a shorter revisit time to the selected regions for communication missions.

1. Introduction

Low Earth orbit (LEO) satellites are considered a huge qualitative leap in the field of communication. With the rapid advancement of technology, nanosatellites have become a very powerful tool for communication across the world [1]. IoT communication satellites are the new revolution in the space industry. Due to their crucial advantages, and since LEO satellites provide an attractive platform, the demand for IoT communication satellites increased significantly [2]. In locations, such as the oceans, deserts, wilderness or earth poles that are not serviced by cellular or phone networks, LEO satellites will enable wireless communication. There are many different communication protocols and methodologies used in the IoT, depending on the specific requirements of the devices and applications being developed. Some of the most commonly used protocols include Bluetooth [3], Zigbee [4] and Z-Wave [5], which are all designed for low-power, low-bandwidth devices. More recently, the development of 5G networks has paved the way for the use of cellular networks for IoT communication, allowing for higher speeds and greater capabilities.

One promising technology for IoT communications on LEO satellites is LoRa (long range) technology, which is well suited to the constraints of satellite operations. LoRa [6] is a wireless communication technology that is designed for long-range, low-power communications. Nowadays, LoRa is used in a wide range of applications, from smart cities and agriculture to industrial IoT and asset tracking. LoRa is often used in combination with other technologies, such as cellular networks or satellite communication, to provide a flexible and reliable communication solution. There are two main methods used in LoRa communication: chirp spread spectrum (CSS) and frequency-hopping spread spectrum (FHSS). CSS uses a continuously varying frequency signal to transmit data, which allows for long-range communication and high resistance to interference [7]. FHSS, on the other hand, uses a series of frequency hops to transmit data, which provides greater security and resistance to jamming [8]. Both CSS and FHSS have their own strengths and weaknesses, and the best approach for a given application will depend on the specific requirements and constraints of the system.

Some examples of where the necessity of IoT and satellites is needed are in harsh industrial environments, such as the oil and gas industry. The oil and gas industry has been moving towards “Data-centric Operations” by collecting huge amounts of data, but often via independent equipment and systems, each with its own data and interfaces. The upcoming 5th generation (5G) mobile networks can enhance the Industrial Internet of Things (IIoT) to improve safety and optimize performance. A platform is proposed to continuously collect critical information from multiple nearshore assets and transmit it through a 5G network [9].

Another paper by Xu, Bingyu et al. investigates dual-stream transmission and downlink power control for multiple low Earth orbit (LEO) satellite-assisted Internet of Things (IoT) networks. The dynamic characteristics of LEO satellites can seriously decrease the data rate and make it fluctuate. To mitigate the effects of the frequency offset caused by different LEO satellites, a multisatellites synchronization scheme is proposed. Different power control schemes are also given to resist data rate fluctuation during transmission. Simulation results show that the proposed schemes can effectively compensate for the varied frequency offset and keep the data rate stable [10].

Some recent work from Zhi Lin et al. focuses on joint beamforming design and optimization for reconfigurable intelligent surface (RIS)-aided hybrid satellite-terrestrial relay networks where links from the satellite and base station to multiple users are blocked. A refracting RIS cooperates with a base station operating as a half-duplex relay to strengthen desired satellite signals for blocked users. The objective is to minimize the total transmit power of both satellites and base stations, while guaranteeing user rate requirements. An alternating optimization scheme is proposed to optimize beamforming weight vectors and phase shifters at the RIS iteratively, using singular value decomposition, uplink-downlink duality, Taylor expansion, and penalty function methods. Simulation results demonstrate the superiority of the proposed scheme over benchmark schemes [11].

Kang An et al.’s paper focuses on the physical layer security of a satellite network sharing its downlink spectral resource with a terrestrial cellular network. The proposed solution employs a multi-antenna base station as a source of green interference to enhance secure transmission in the satellite network. The mutual interference between the two networks is considered, and a constrained optimization problem is formulated to maximize the instantaneous rate of the terrestrial user while satisfying the interference probability constraint of the satellite user. Two beamforming schemes, hybrid zero-forcing and partial zero-forcing, are presented to solve the optimization problem and obtain the beamforming weight vectors. The secrecy performance of the primary satellite network is analyzed considering two practical scenarios, with analytical expressions derived for secrecy outage probability and average secrecy rate. Numerical results demonstrate the superiority of the proposed beamforming schemes and validate the performance analysis [12].

For each mission, it is important to design and select an orbit that meets the requirements of the mission [13,14,15]. Since there are various subtypes of LEO orbits, there are several parameters that need to be taken into account while designing a satellite orbit. Sun-synchronous orbit (SSO) is the most common orbit that CubeSats with various missions are launched into. Satellites in the SSO have an inclination angle of 98° and cross the polar regions of the Earth, and because their orbital plane is synchronized with the sun, they will continuously view a specific region on Earth at the same time of the day [16]. This phenomenon is useful for earth observation and remote sensing. However, for an IoT communication mission, the time is not a constraint, but it is more about the number of passes that the satellite makes over the ground station to downlink the data. Therefore, a lower inclination orbit seems to be more effective for LoRa-IoT communication satellites.

In related works, there are several missions with different selections of orbits. Some missions utilized a propulsion system that continuously maneuver the satellite between the targets to ensure that the entire regions are covered and get a higher resolution measurement [17]. However, this technique has restrictions since a propulsion system is needed. Other remote sensing missions, such as the Indian remote sensing satellite use, SSO so that the satellite’s orbit is phased to pass repeatedly over a targeted location every specific period [18]. Moreover, for earth observation missions, it is useful to use a repeat ground track orbit since one of the mission’s requirements is ground track repeatability [19,20]. In addition, the satellite pass’s position in relation to the ground stations remains constant. Though, a maneuver correction is necessary to keep the repeatability of the ground track [21].

The overall system configuration and operational costs are influenced by the number of orbits, the number of satellites in each orbit, the types of orbits, and the altitude of the orbits [22]. According to Nadoushan and Assadian [20], revisit time and repeat cycle are the most important parameters that need to be considered while designing the orbit.

To build and develop a nanosatellite, it is essential to follow a certain standard. The Lean Satellite Standard [23], also known as the Cho Standard, is a set of guidelines for designing and building small satellites, such as CubeSats. The main objective of the Lean Satellite Standard is to provide a simple and cost-effective approach to building small satellites within a short time. Unlike traditional satellite design, which often involves complex and expensive systems, the Lean Satellite Standard emphasizes simplicity and modularity. This approach allows for the rapid and inexpensive development of small satellites, making it an attractive option for researchers and organizations with limited budgets and resources. Each satellite in the Lean Satellite Standard is made up of a handful of standardized modules, which are then merged and modified with ease. Depending on the unique needs of the mission, this enables the quick and low-cost production of satellites with a variety of capabilities. To achieve low-cost and fast delivery, the satellite’s architecture depends on using non-space-qualified Commercial Off the Shelf (COTS) components, so the satellite’s size eventually decreases. Additionally, using COTS parts means that the Lean Satellite Standard recognizes that there is some risk involved.

Moreover, Lean satellite has established testing standards [24]. The test level and test method are established by the environmental standard for lean satellite. Acceptance test (AT) and qualification test (QT) are two test levels frequently used for satellites and their components. Vibration, shock, thermal vacuum, thermal cycling and radiation are the methods used for testing [25]. A new concept of “Unit QT” was added to the standard, stating that “For unit level qualification tests, the standard is meant to provide the minimum guarantee that a given unit sold as “a satellite unit” has a certain level of tolerance against the space environment.” [25].

An example of a LoRa-IoT communication satellite is DEWASAT-1, which is the first utility nanosatellite developed by Dubai Electricity and Water Authority (DEWA). It was launched into orbit in January 2022 with the goal of providing advanced communication capabilities for DEWA and other organizations in the UAE. The primary mission of DEWASAT-1 is to provide connectivity using IoT as a primary or backup system for electric and water network devices and increase flexibility in monitoring the network. DEWASAT-1 implements a novel method using the direct-communication-to-satellite (DCTS) technique to eliminate the necessity to include LoRa gateways [26].

DEWASAT-1 is a 3-unit CubeSat at an orbital altitude of 530 km, orbiting the sun-synchronous orbit where the SSO is considered as a high-inclined orbit since the inclination angle is approximately 98°. The payload of DEWASAT-1 is a radio receiver (Satlab Polaris RX) that receives the IoT-LoRa message, stores it and then, forwards the housekeeping data to the ground station. The data is then shared with the end-users to be employed for different use-cases. The access times of DEWASAT-1 in the targeted area of Dubai, United Arab Emirates (UAE), are shown in Figure 1 where the total number of passes per day is four. Figure 2 below shows the single access orbit path of DEWASAT-1.

The duration of each pass is short and there are significant gaps between each pass. This is not useful for missions that require frequent passes daily, so by decreasing the inclination angle, the contact times and the number of passes could increase.

Since UAE is one of the areas that are close to the equator, where the surface of the Earth is closest to the sun, it is desirable to include them in our consideration. These areas, also known as near equatorial regions, which include nations in Central and South America, Africa, and Southeast Asia, are typified by high temperatures and high humidity levels.

Greater access to the internet and other communication technologies is one way that the influence of IoT and LEO satellites might help nations in the near-equatorial regions. The deployment of LEO satellites can offer an alternate method of connecting individuals and companies to the internet due to insufficient infrastructure for terrestrial broadband and cellular networks. In rural and distant places, where it could be challenging or expensive to develop standard broadband infrastructure, this might be extremely crucial. The agriculture sector is where this technology might increase the effectiveness and productivity of their operations, and farmers can benefit from using sensors, drones, and other IoT technology.

For instance, the use of IoT and LEO satellites can aid in the development of new markets and commercial prospects for organizations that offer these products and services. By generating jobs and boosting local firms’ competitiveness, it can also contribute to economic development and growth in these areas. Furthermore, facilitating access to important services, such as healthcare, education, and other necessities, the usage of these technologies can also assist in raising the quality of life for those who live in these areas.

This paper investigates the possible benefits of having satellites with lower inclination orbits because there is a need to utilize more suitable orbit regimes for the Middle East and North Africa (MENA) and near-equatorial regions. For these regions, many countries do not have the ability to launch a satellite constellation, so it is important to receive telemetry data from the satellite as frequently as possible. In other words, we are aiming to minimize the number of satellites in the constellation by decreasing the revisit time and increasing the number of passes to the ground station. Additionally, since various missions concern a specified region not global coverage, it is not necessary to launch the satellite in the SSO. Moreover, emphasizing the new technology of LoRa-IoT implemented in satellites will help to reduce the power and complexity of IoT equipment, utilize DCTS IoT terminals in order to automate the entire measurement-to-ground station, and to launch new satellites using the same technology but with the right inclination angle.

The key point of this paper is to design, build and test an IoT terminal and use simulation to prove that a low inclination orbit for an IoT communication satellite mission is better than SSO for the specified area of interest in terms of area coverage, coverage time, revisit time, and number of passes to the ground station. As a result, future satellites will be launched into lower-inclination orbits depending on the area of interest to maximize the benefits. Finally, the concept also looks at utilizing IoT for government and utility companies to provide orbital data as a service. The choice of a lower-inclination orbit provides more data for various business units.

The contributions of this paper are as follows:

• This paper clarifies and demonstrates the IoT-LoRa concept using nanosatellite technology.
• This paper explores the implementation of CSS modulation using store and forward approach where SDR receiver payload was installed in DEWASAT-1.
• This paper studies the link margin assessment for IoT-LoRa mission.
• This paper investigates and simulates the advantages of having lower inclination orbit in terms of coverage, access times, and revisit time.
• This paper validates the IoT terminal design by displaying the real-time DEWASAT-1 satellite data for some of the use-cases.

The rest of this paper is structured as follows: Section 2 focuses on the selection of orbit and the IoT terminal design. Section 3 presents and discusses the simulation results. Finally, Section 4 concludes the paper.

2. Methodology

This section presents the key elements of the satellite’s design and its intended operating environment and demonstrates the feasibility of using a lower inclination orbit for the satellite’s mission as follows:

• Orbital Parameters: This section describes the parameters that define the orbit of the satellite. This information is crucial for determining the satellite’s position and movement in space.
• Comparison between SSO and Lower Inclination Orbit: This section presents the advantages and disadvantages of both orbits which at the end demonstrates the feasibility of using a lower inclination orbit for the satellite.
• Lower Inclination Orbit Mission Definition: This section defines the mission scenario used for analysis and verification with all the necessary parameters defined.
• LoRa-IoT Design Requirements: This section lists the design requirements of both the IoT ground terminal and the satellite payload receiver.
• IoT terminal design: This section describes the design of the IoT terminal. The terminal is responsible for transmitting data to the satellite, as well as communicating with ground-based sensors and other IoT devices.
• Link Budget Analysis: This section lists the requirements for the link budget and calculates the minimum power required for a successful link margin of transmission.

2.1. Orbital Parameters

Classical Orbital elements are a set of parameters that are used to describe the shape, size, and orientation of a satellite’s orbit. These variables are crucial for satellite operation and design as they offer vital details of a satellite’s orbit. A total of six Degrees of Freedom (DoF) is typically required for any physical object to define its location in three-dimensional space including three translational motions along X, Y, and Z and three rotational motions around them, commonly named roll, pitch, and yaw. Therefore, Kepler [27] defined a set of six classical orbital elements, sometimes called the Keplerian elements, to define an orbit. These six independent constants include the satellite’s semi-major axis, eccentricity, inclination, right ascension of ascending node, argument of perigee, and true anomaly.

2.1.1. Semi-Major Axis (a)

The semi-major axis is a measure of the size of the satellite’s orbit. For elliptical orbits, it is defined as the distance from the center of the Earth to the point in the orbit where the satellite is farthest from the Earth, known as the apogee. However, the semi-major axis is the radius of the orbit for circular orbits. The semimajor axis is related to the orbital period of the satellite, with longer periods corresponding to larger semimajor axes [27].

2.1.2. Eccentricity (e)

The eccentricity (e) of an orbit describes how far away from a perfect circle the orbit is, so it is a measure of the orbit’s shape. Equation (1) defines eccentricity as the ratio of the distance between the center of the Earth and the satellite at its closest point (perigee) to the distance between the center of the Earth and the satellite at its farthest point (apogee).

$$e=\frac{c}{a}$$

(1)

where c is the center-focus distance of the ellipse and a is the semi-major axis. Additionally, an orbit that is very eccentric is closer to one, while a circular orbit has an eccentricity of zero [13]. Moreover, not the center of the ellipse, but one of its focal points, is where a satellite in an eccentric orbit moves. Figure 3 shows orbits with different eccentricity values.

2.1.3. Inclination (i)

The orbit’s inclination angle is measured in reference to the equator of the planet as shown in Figure 4. It is defined as the angle between the satellite’s orbital plane and the Earth’s equatorial plane. Inclination values range from 0 degrees to 180 degrees [27].

When i = 0° or 180°, it is considered as an equatorial orbit. Inclination with angles 0° < i < 90° are knows as prograde orbits that move in the direction of earth’s rotation. When i = 90° this means it is a polar orbit. Lastly, when the inclination angle is 90° < i < 180°, this means that it is in a retrograde orbit which moves in the opposite direction of earth’s rotation [29].

2.2. Comparison between SSO and Lower Inclination Orbit

As defined previously, the inclination of a satellite refers to the angle that the satellite’s orbital plane has with the Earth’s Equator. This angle can be tuned depending on the desired latitude coverage of a satellite orbit.

In polar orbits (with inclination between 96 and 98 deg) the satellite passes over the Earth’s poles as it orbits the earth, providing a wide-ranging view at all latitudes of the Earth. Polar sun synchronous orbits are well-suited for applications that require a global coverage of the Earth, such as weather monitoring. Additionally, despite seasonal variations, the angle between the orbital plane and the sun (Beta angle) is kept near constant throughout the year. Due to this stability, scientists may compare photos taken during the same season across several years without having to worry too much about the appearance of change due to significant variations in lighting and shadows [30].

In contrast, satellites with lower inclination (less than 90 deg) orbits spend their time within a confined range of equatorial bands and therefore have a narrower coverage region with more persistent contacts within that band. Additionally, the target area will be passed over by the satellite in a lower inclination orbit at various times throughout the day while the satellite in SSO will pass at the same time range daily because it is oriented constantly with respect to the sun illumination [1]. Lower inclination orbits are well-suited for missions that require frequent passes and longer coverage time on certain regions of the Earth such as communication, and remote sensing. The rationale behind a lower inclination orbit is that satellites in these orbits cover more frequently certain coverage regional bands allowing for more frequent imaging opportunities of the areas of interest (higher temporal resolution). Missions that call for a specialized perspective of a certain location, such as a single continent or a specified region will benefit from this. The satellite can deliver more frequent and dependable data for these applications by keeping near to a confined latitude range.

The capabilities and performance of a satellite can be impacted by a number of significant changes between polar SSO and lower inclination orbits. The amount of time the satellite spends over a certain spot on the surface of the Earth is one of the key distinctions. The satellite will repeatedly cross a specific point while in an orbit with a lower inclination, delivering regular updates and information. However, the satellite will pass over a certain place less frequently in an orbit with a high inclination, producing fewer frequent updates. Furthermore, satellite constellations in lower inclination orbits allow total number of satellites and mission costs to be reduced by focusing on confined latitude ranges. These constellations can be designed to ensure ideal revisit times only in the geographical regions where it matters the most [31].

2.3. Lower Inclination Orbit Mission Definition

The satellite will be designed based on the Lean satellite standard, which will be orbiting in the LEO. The mission is to use an IoT terminal for satellite communication to cover remote or hard-to-reach areas in the near-equatorial regions. The payload is a LoRa receiver onboard the satellite. It is capable of receiving LoRa message packets from the ground IoT terminal and decoding the messages before being sent down to the ground station (GS) via S-band. The GS is located in the DEWA’s Research and Development Centre in Dubai-UAE. The aim of the mission is to cover the entire area of interest daily and maximize the revisit time. Additionally, to increase the number of passes of the satellite above the GS, so that we can get updated data within a few hours. The targeted areas are the cities/countries confined within latitude bands between, which are at the 0° to ±27° latitudes. The elevation angle between the satellite and GS should be at least greater than 30° at the MidPass [32] to ensure useful data through a favorable link margin.

In the simulation, the orbital parameters of DEWASAT-1 will be used as SSO. On the other hand, the satellite in the mission scenario with a lower inclination angle will use the same parameters except the inclination angle which will be changed to determine the optimum angle that will optimize the mission requirements.

Table 1. Orbital Elements of SSO and Lower Inclination Orbit Satellites.

Simulation Parameters	SSO Value	Lower Inclined Value
Semi-major axis	6928 km	6928 km
Inclination	98°	0°–90°
Eccentricity	0°	0°

below shows the orbital parameters of the two satellites used in the simulations.

2.4. LoRa-IoT Design Requirements

Before designing the IoT terminal, it is important to define the design requirements of the terminal and the satellite receiver to ensure perfect communication between both of them. The design requirements of the IoT ground terminal are as follows:

• The IoT terminal shall be able to operate autonomously and under remote object control for different use-cases.
• The IoT terminal shall be able to transmit LoRa-CSS packets.
• The IoT terminal shall be able to transmit and receive LoRaWAN packets.
• The IoT terminal shall be able to provide interfaces to sensors.
• The IoT terminal shall be able to provide a transceiver power within the allowed range.
• The IoT terminal shall be able to uplink data to the satellite with the specified frequency range.
• The IoT terminal shall be able to withstand space environment temperatures.
• The IoT terminal shall be able to carry a portable battery that power the terminal for a duration of 7 days.
• The IoT terminal shall be able to carry a memory to store the collected data from sensors.
• The IoT terminal shall be able to carry an antenna and a GPS.
• The IoT terminal shall be able to transmit 50 bytes per LoRa message.

Moreover, the design requirements of the IoT-LoRa payload (satellite receiver) are as follows:

• The LoRa Payload shall be able to fit within the 3U CubeSat platform.
• The LoRa Payload shall be able to withstand the operating temperature of the space environment.
• The LoRa Payload shall be work within the specific frequency range selected by IoT terminal.
• The LoRa Payload shall be able to receive data from the ground terminal.
• The LoRa Payload shall follow the CubeSat Space Protocol (CSP)
• The LoRa Payload shall have high sensitivity Received Signal Strength Indicator (RSSI).
• The LoRa Payload shall consume low power.
• The LoRa Payload shall have a weight up-to 200 g.

2.5. IoT Terminal Design

The IoT terminal is designed based on the design requirements to operate at the 865.07 MHz frequency band using LoRa payload. It would utilize either LoRa CSS or FHSS for the transmission of data. The terminal would have a LoRa transceiver and antenna capable of transmitting and receiving signals at the specified frequency. It would also have a microprocessor and memory to store and process data, as well as a power source and potential external sensors for data collection.

The IoT terminal hosts two main subsystems. The primary subsystem is a microcomputer configured to execute various tasks and measurements. The second subsystem is the radio transceiver with uplink antennas to perform transmission (Tx) operations.

The main board is a Raspberry Pi Zero W [33], with a single core 1GHz CPU and 512 MB of RAM. The specifications operate well in a low-power IoT application with minimal multi-tasking and threading. The deployment of these IoT terminals is planned for the near-equatorial regions specifically remote areas of the desert with high daytime temperatures and cool night-time temperatures. To combat the temperature effects, the IoT device is constructed in a weatherproof box capable of operating in the −10 °C to +50 °C range. The host board additionally offers a number of remote interfaces, making it the ideal development environment for satellite communications. These interfaces include an RS485 input, a communication protocol that meets industrial specifications and specifies the physical hardware and electrical interface for point-to-point electrical device communication [34]. This makes it possible for remote sensing applications to use DCTS and for the IoT Terminal to successfully interface with various devices using the Modbus protocol. The main board also allows remote management and a powerful scripting engine to perform controlled tests in an updatable manner.

The second subsystem is an ARM Node processor with a Semtech SX1262 Radio for uplink procedures [35]. The radio transceiver operates at a +22 dBm power output between the frequencies of 150 MHz and 960 MHz [35]. All LoRa CSS and LoRa Long-Range Frequency Hopping Spread Spectrum (LR-FHSS) modulations can be used with the uplink radio. In order to test the maximum power permitted for LoRa CSS, the node is also equipped with a +27 dBm power amplifier. Figure 5 shows the system architecture and Figure 6 shows the practical, in-house developed IoT terminal.

Antenna selection is a crucial point in establishing a successful link between the LoRa IoT terminal and the satellite. Monopole omnidirectional antennas receive signals equally from all directions, while directional antennas can detect comparatively weaker signals in a specific direction [36]. The gain of the antenna is another parameter that can be utilized to add to the transmitted power of the signal to account for any spatial or atmospheric losses. Omnidirectional antennas work on 2-dimensional planes, radiating a flat signal [37] shown in Figure 7.

With omnidirectional antennas, the orientation of the antenna either horizontally or vertically, plays a role in how the signal is transmitted to the satellite. LEO satellites orbit from west to east [16], and therefore placing the antenna facing east and horizontally provides the best output signal from the antenna. The typical radiation pattern of an omnidirectional antenna is shown in Figure 7 [32].

For LoRa CSS, the terminal would operate using a constant spreading factor to transmit data, allowing for a longer range but a lower data rate. In spread-spectrum communication systems, the bandwidth and data rate of a transmitted signal are determined by spreading parameters. There are several spreading factors that can be utilized in the case of LoRa, each with different trade-offs in terms of range and data rate.

For a fixed bandwidth (125 kHz), a smaller spreading factor, such as SF7, leads to a greater data rate, enabling the transmission of more data in less time. As a result, the signal’s range is likewise shortened, and it is more vulnerable to noise and interference. A larger spreading factor, such as SF12, on the other hand, causes a lower data rate, enabling a greater range and better signal quality. The quantity of data that may be delivered in each length of time is nonetheless decreased as a result [38].

The final decision about the spreading factor is made considering the needs and limitations of the communication system, including the intended range, data rate and amount of interference. The potential for interference with other signals running at the same frequency, which might result in subpar performance, is a limitation when utilizing LoRa CSS. When a transmitter and receiver are moving relative to one another, a phenomenon known as doppler shift happens [39]. This may result in a change in the operating frequency for satellite communications, which can have an impact on the signal’s quality. The terminal can use adaptive frequency hopping and frequency correction techniques to minimize the doppler shift and maintain a steady signal. To adjust for frequency changes brought on by the doppler effect or other variables, communication systems utilize frequency correction algorithms. These algorithms, which may be used in either the transmitter or the receiver, usually include constantly checking the signal strength and modifying the operating frequency to keep the connection steady.

Utilizing input from the receiver to change the transmitter’s frequency is a typical method of frequency correction. This may be achieved by comparing the received signal to a reference signal and changing the transmitter’s frequency in accordance with the variation between the two. Implementing adaptive frequency hopping is another strategy where the transmitter continually modifies its operating frequency in response to various factors, such as the quantity of interference or the caliber of the received signal. This enables the transmitter to maintain a solid connection with the receiver while avoiding frequencies that could be blocked or degraded.

2.6. Link Budget Analysis

Link budget analysis is a critical aspect of wireless communication system design that allows for the estimation of the signal quality and strength between transmitters and receivers. In a wireless communication system, the transmitted signal experiences attenuation, which reduces its strength and quality as it propagates through the air. Link budget analysis is the process of determining the total attenuation of the transmitted signal and comparing it to the minimum required signal strength at the receiver to achieve reliable communication.

2.6.1. Receiver Sensitivity

In the LoRa module selected for the system architecture, the SX1262 [35] transmitter’s receiver sensitivity, S, can be calculated to attain the minimum signal level. Equation (2) calculates the minimum signal level to achieve target performance based on bandwidth [40].

$$S=-174+10 \log \left(BW\right)+NF+{SNR}_{\lim it}$$

(2)

where BW is the bandwidth in Hz, NF is the noise figure gain and SNR_{lim it} is the limiting signal-to-noise ratio.

2.6.2. Link Margin

The link margin, expressed in dB, represents the ideal value to determine whether a communication link between a spacecraft and a ground station will be effective. Thus, the communication design should result in a positive link margin to guarantee a solid communication connection. The following equation is used to calculate the link margin, where the expected value of energy per symbol to noise ratio $\left(\frac{E_s}{N_o}\right)$ is compared with the required value as follows:

$$Linkmargin(dB)={{\left(\frac{E_s}{N_o}\right)}_{Expected}-\left(\frac{E_s}{N_o}\right)}_{Req}$$

(3)

Equations (4) and (5) define the required and expected $\frac{E_s}{N_o}$:

$${\left(\frac{E_s}{N_o}\right)}_{Req}={\left(\frac{E_b}{N_o}\right)}_{Req}+10 log (SF)$$

(4)

$${\left(\frac{E_s}{N_o}\right)}_{Expected}=EIRP-L_{Tot}-G/T-Boltzman$$

(5)

where $\frac{E_b}{N_o}$ is the signal-to-noise ratio per bit, SF is the spreading factor, $EIRP$ is the equivalent isotopically radiated power, $L_{Tot}$ is the total losses, $G/T$ is the ratio of receive antenna gain to noise temperature and Boltzmann is a constant.

The $EIRP$ [38] is expressed as follows:

$$EIRP=P_{tx}+G_{tx}$$

(6)

where $P_{tx}$ is the transmitted power, and $G_{tx}$ is the transmission antenna gain. Equation (7) shows the total losses in dB that affects the communication system.

$$L_{Tot}=L_{FSPL}+L_{Polz}+L_{Rain}+L_{Poin}+L_{Imp}$$

(7)

where $L_{FSPL}$ is the free space path loss, $L_{Polz}$ is the polarization loss, $L_{Rain}$ is the rain loss, $L_{Poin}$ is the pointing loss, $L_{Imp}$ is the implementation loss. Moreover, $L_{FSPL}$ is defined as follows:

$$L_{FSPL}=20 log(\frac{4\pi }{c})+20 log(f)+20 log(d)$$

(8)

where $f$ is the frequency in MHz, $d$ is the distance in kilometer and c is the speed of light in kilometers MHz. The distance $d$ [38] from the satellite to the GS is computed from Equation (9).

$$d=\sqrt{{\left(r+h\right)}^2-{\left(rcosØ\right)}^2}-rsinØ$$

(9)

where r is the radius of the earth, h is the altitude of the orbit, $\mathrm{Ø}$ is the elevation angle between the satellite and GS. Finally, $G/T$ is defined by Equation (10).

$$G/T(dB/K)=Satelliteantennagain-10log\left(noisetemperature\right)$$

(10)

2.6.3. Bit Rate

The bit rate is an important parameter in communication systems as it determines the maximum amount of data that can be transmitted or received within a given time period. It is often used as a performance metric to evaluate the efficiency and capacity of communication systems, such as wireless networks, digital television broadcasting and internet connectivity. Bit rate is a measure of how quickly bits are moved between two locations. It is the product of symbol rate, code rate and spreading factor [41], as shown in Equation (11), where symbol rate (Equation (12)) is the transmission rate of signals along certain connections and code rate (CR) is the proportion of transmitted bits that actually carry information. For LoRa communication, the code rate has four values [42], which are 4/5, 4/6, 4/7 and 4/8, and they are shown in Equation (13), where n is between 1 and 4.

$$Bitrate\left(bit/s\right)=Symbolrate\ast CR\ast SF$$

(11)

$$Symbolrate=\frac{BW}{2^{SF}}$$

(12)

$$CR=\frac{4}{4+n}wheren=\mathrm{1,2},\mathrm{3,4}$$

(13)

2.6.4. Airtime

Time on air, or airtime, is directly related to the amount of data that can be transmitted over the wireless channel within a given time period. The more airtime that is available, the more data that can be transmitted. To optimize the use of airtime in wireless networks, various techniques are used, such as dynamic channel allocation, adaptive modulation and power control. These techniques help to minimize interference and increase the efficiency of data transmission, thereby improving the overall performance of the link margin. Airtime is the time it takes for the signal to reach the receiver on the satellite from the ground terminal. Equation (14) is used to calculate airtime [43].

$$Airtime(s)=\frac{2^{SF}}{BW}\ast Totframelength$$

(14)

$$Totframelength\left(symbols\right)=n_{payload}+n_{preamble}+4.25$$

(15)

where $n_{payload}$ is the payload length that is expressed in Equation (16) and $n_{preamble}$ is the preamble length.

$$n_{payload}=8+max(ceil(\frac{\left(8\ast Payloadlength-4\ast SF+28+16\right)}{SF})\ast (\frac{1}{CR}),0)$$

(16)

2.6.5. Design Indicators and Criteria

This section defines the system design indicators to be used for the link budget analysis for the LoRa-IoT communication system using CSS modulation technique for up linking.

Table 2. Design Parameters.

Variables
Satellite elevation angle	0 to 90°
Spreading Factor	7 to 12
n in Code Rate	1 to 4
Limitation and constrains
Ground transceiver power (IoT Terminal)	25 dBm
Nonlicenses central frequency for LoRa	865.07 MHz
Band width	125 kHz
Satellite antenna gain	6.5 dBi
Altitude	550 km
Constants
Boltzmann	−228.6 dBW/Hz/K
Receiver noise figure	458 K
Worst case
Ground antenna gain	0 dBi
Losses	(dB)
Pointing loss	0.5
Polarization loss	0.5
Rain loss	0.2
Implementation loss	0.5
Req. Eb/N0	6

outlines all the design parameters that were considered, including the limitations and constraints.

3. Results and Discussion

This section presents and discusses the simulation findings from the lower inclination orbit proposal over the near-equatorial region, including the link budget, and also the real-time data collected from the satellite using the designed IoT terminal.

3.1. Ground Track Analysis

Ground track analysis (GTA) is used to forecast and evaluate the coverage that a satellite can offer to various points on the surface of the Earth. It is a crucial tool for satellite operators since it enables them to deploy and operate the satellites optimally to increase coverage.

The coverage time probability for various inclined satellites is plotted in Figure 8 as a function of both latitude and inclination angle for various inclination degrees from 0° to 70°. The chart is symmetrical for negative values of latitude. As the latitude increases, the coverage time probability also increases until it reaches a certain latitude value, where it drops sharply to zero. Although the inclination increases, greater global coverage is achieved despite a lower coverage time probability per region. This is desired in global IoT applications that do not require the frequent revisit time offered by lower-inclination orbits.

Additionally, when the inclination angle is smaller, the possibility of coverage at higher latitudes is impossible. This is because LEO satellites with lower inclination angles do not reach areas at greater latitudes since their ground tracks are more closely aligned with the equator. On the other hand, satellites with greater inclination angles have ground tracks that are inclined further toward the poles and are therefore more likely to cover areas at higher latitudes.

Looking at Figure 8, for the near-equatorial regions residing in the 0–±27°, the optimum inclination angle is chosen at 24°. This is because it provides a coverage time of ~12% for the near-equatorial regions.

3.2. Coverage Percentage

The angle between a satellite’s body axis and the line of sight of its sensor or communication antenna is referred to as the off-boresight angle. It plays a significant role in determining how well a satellite’s sensors or communication systems operate. For instance, a satellite built to capture high-resolution photos of the ground can feature a camera with a narrow field of view that is suited for collecting pictures at close off-boresight angles. On the other hand, a satellite may include an antenna with a broad field of view that may sustain a strong signal at greater off-boresight angles if it is intended to connect with other satellites or ground stations. Figure 9 shows the same coverage as in Figure 8 but considers that the satellites can provide coverage to a certain range or angle off their Nadir ground track. The latitude is represented by the x-axis, and the coverage percentage of the orbits is shown on the y-axis. Three separate satellites are represented by the various lines on the graph. By incorporating the off-Nadir angle, one can observe that the coverage does not reduce so sharply beyond a certain max latitude value. Figure 9 and Figure 10 show how the fields of view at 30° and 60° vary in coverage, respectively.

Analyzing Figure 9 and Figure 10 proves that, for the near-equatorial regions, a satellite with a lower inclination of 24° is favorable to an SSO or polar-type orbit. For example, in the countries/cities at 25° N, such as Algeria, Egypt, Saudi Arabia and the United Arab Emirates, the daily coverage percentage is at 20%, as opposed to 8.5% for SSO. The higher coverage provides a lower revisit time and more access for a closer to real-time application of IoT. However, at higher latitudes, it is less likely to receive coverage from satellites with lower inclination angles, as their ground tracks are further away from the equator.

3.3. Coverage Time

In the mission scenario defined, a low-incline orbit of 24° provides a peak coverage of 27% at 24° latitude. In the near-equatorial region spanning from 0° to ±27°, the satellite has a minimum coverage of 10%, providing more access and a shorter revisit time to the regions selected for the various communication missions. The coverage time as a function of latitude is shown in Figure 11.

3.4. Accumulated Coverage

The accumulated coverage of both the SSO and lower inclination orbits for a period of 7 days is shown in Figure 12. It is obvious that the total coverage percentage of the satellite with a 24-degree inclination angle is higher than the satellite with SSO. The satisfied coverage percentage was more than 95% for lower inclination orbits and 67.5% for SSO.

3.5. Access Time

Focusing on the United Arab Emirates as the ground station location, Figure 13 shows the difference in access time between SSO and the proposed lower inclination orbit for a 24-h period chosen randomly. A usable pass is one considered when the elevation angle is greater than 30° for an IoT-LoRa communication with a good link budget.

As shown, for this day, the SSO provides four usable passes a day, while the low-incline concept provides eight in the same 24-h window. With longer access times, the revisit time is minimized, enabling near real-time data transmission and reception for IoT applications and other communication missions.

Additionally, the number of accesses as a function of latitude was plotted in Figure 14. It is clear that the satellite in a lower inclination orbit will have much more contacts than the satellite in SSO. Since the satellite in SSO provides global coverage, the number of accesses to the near-equatorial region, the region of interest, will be small and constant for all latitude values (approximately 3.7). However, the number of accesses of the satellite with a 24-degree inclination angle will be approximately 8.5, which is more than twice as high as that with SSO, and then it will start increasing till it reaches the peak at 22° N point, where the GS is located. This means that we will get more data from the satellite with the lower inclination orbit. Thus, the number of satellites will be smaller in case we need to have a constellation.

3.6. Average Revisit Time

The revisit time is the time when the satellite passes over the targeted regions. In lower inclination orbits, areas with latitudes closer to the inclination angle chosen have the best (least) revisit time. Figure 15 shows the satellite path with a 24-degree inclination angle (low inclinations), while Figure 16 displays a visual representation of the revisit time of the proposed orbit on a 3D plane.

The green regions in the figures show an average revisit time as low as 4 h, with a maximum revisit time of 18 h at the extremities of the near-equatorial region defined. Moreover, in Figure 17, the average revisit times are plotted over a 7-day period for the SSO and lower inclination orbits. The x-axis shows the near-equatorial latitude selected in the mission definition, from 0° to ±27°. The green and black lines highlight the lower inclination orbit and the SSO average revisit time, respectively. It is clear that in the near-equatorial regions, the lower inclination orbit is preferred, as the average revisit time is lower. For example, at the 10° N point, the average revisit time for the lower inclination orbit is 19 h, as opposed to 105 h for the SSO.

Lastly, in Figure 18, the lower inclined orbit has a lower gap duration than that for SSO. Additionally, for the same duration, the lower inclined orbit has a higher access percentage than the SSO. For instance, for a duration of 25 h, the lower inclined orbit has an access of 92% while SSO has only 80%.

3.7. Link Budget Simulation

The link budget calculation involves several parameters, such as transmit power, receiver sensitivity, path loss and antenna gains, which are taken into account to determine the power budget of the wireless link. The simulation is performed by evaluating the power received at the receiver end and comparing it with the minimum required power for successful communication.

3.7.1. Link Budget Sample Calculation

The calculation in this section uses a spreading factor of eight and a code rate of 4/5 to determine the required transmit power and the received power at the receiver end. The results of the simulation indicate that the required successful link margin is 4.3 dB at a minimum elevation of 20°. These results indicate that the link is operating within the specified power budget, and the communication is expected to be successful. Figure 19 below highlights the link budget simulation with the left-hand-side showing the unacceptable link budget. The yellow is a moderate link budget whilst the green is the successful link margin.

3.7.2. Link Margin

Using the link budget analysis conducted in Section 2.6, the link margin was calculated and plotted in Figure 20 for different satellite elevation angles while varying the SF. It is noticeable that increasing the elevation angle will enhance the link margin so that at 90 degrees, the link margin will be maximum for a certain SF. In addition, increasing the SF will also lead to an increase in the link margin. Additionally, for small elevation angles with an SF of 7 or 8, the results show that the link margin will be negative, which is undesirable.

3.7.3. Bit Rate

In Figure 21, the bit rate and code rate are varied across different spreading factors. With a higher spreading factor, the bit rate decreases significantly for all code rates. In addition, increasing the code rate (x-axis) from 4/8 (indicated as 1/2 in the figure below) to 4/5 will increase the bit rate, as it is shown in the figure below.

3.7.4. Airtime

In Figure 22, the airtime vs. the code rate is evaluated against different spreading factors. The set payload length is 25 bytes with a bandwidth of 125 kHz. The lower the spreading factor, the lower the airtime. This means that using a higher spreading factor will provide more airtime for all code rates. This becomes unsustainable at higher payloads, where the higher spreading factors would not be able to transmit the packets successfully. Moreover, increasing the code rate (x-axis) from 4/8 (indicated as 1/2 in the figure below) to 4/5 will decrease the airtime, as it is shown in the figure below. From the previous discussion, we can conclude that the airtime is inversely proportional to the bit rate. Therefore, to get a higher bit rate and faster time on air, it is preferable to select a small SF with a large code rate. However, it is important to strike a balance between selecting SF and ensuring a positive link margin.

3.8. Weather Real-Time Satellite Data

The sensors that were implemented in the weather IoT terminal are temperature, relative humidity and air quality index PM2.5 and PM10. The collected data were sent to DEWASAT-1, and then the satellite downloaded the data using ultra-high frequency (UHF). The real-time satellite data were plotted and illustrated in the below Figure 23 and Figure 24. The figures prove that the terminal performed perfectly, and it was able to send data to the satellite using the CSS modulation. Additionally, they show that the data were gathered continuously and were successfully collected by the satellite. Moreover, there were some days where no data were downloaded from the satellite to the ground station, probably because of the low elevation angle between the antenna and the GS. Therefore, if the satellite was launched in a lower inclination orbit, more data would be collected on a daily basis.

4. Conclusions

In conclusion, this paper investigated the improvements in launching nanosatellites in lower inclination orbits for IoT communications missions in the near-equatorial regions. The simulation results proved that the use of low-inclination orbits will reduce the number of satellites in the constellation. Comparing it with the SSO, the findings of the simulation showed that the coverage percentage of the near-equatorial region is higher for satellites with low inclination angles. Moreover, while SSO provides global coverage, the coverage time for each region is almost identical and low, and the revisit time is high. Additionally, the number of accesses to the ground station is lower. On the other hand, for an IoT communication mission, a satellite with an inclination of 24° will provide higher coverage time and more coverage area to the region covering from 0° to ±27° latitude. In addition, the revisit time is lower and the number of accesses to the ground station is higher. The IoT terminal design used allows any sensor to be connected to collect data and forward it instantly to the satellite when in view. Unfortunately, due to power constraints, the limitations on packet size apply and less data can be sent out of the terminal. From the link budget simulation, we can conclude that a higher spreading factor offers a higher and positive link margin, while lower spreading factors offer a higher data rate and require less airtime.

Furthermore, the use of the lean satellite standard reduces the monetary and time cost of the development of satellites, allowing developing countries in the near-equatorial regions to design and deploy IoT applications using LEO satellites across various industries, such as telemedicine, agriculture and the enabling of smart cities. Finally, future research could focus on exploring other regions and new IoT designs, and also, expanding the scope of the study to include real data from launched satellites in lower inclination orbit.