Experimental Evaluation of Antenna Height Impact on LoRaWAN Performance in the 915 MHz ISM Band

Experimental Evaluation of Antenna Height Impact on LoRaWAN Performance in the 915 MHz ISM Band

Putera Raiz Mohmad Reduan¹, MH Mohamad², MM Yunus³, E Baharudin⁴

 ^1,2,3Fakulti Technology dan Kejuruteraan Elektronik dan Computer (FTKEK), University Technical Malaysia Melaka, (UTeM), Malaysia

⁴Fakulti Kejuruteraan Electric dan Elektronik, University Tun Hussein Onn Malaysia

DOI: https://dx.doi.org/10.47772/IJRISS.2025.908000641

Received: 16 August 2025; Accepted: 26 August 2025; Published: 25 September 2025

ABSTRACT

The objective of this work is to examine the effect of transmitter antenna height on the performance of LoRaWAN operating in the 915 MHz ISM band under realistic outdoor conditions. Reliable long-range communication is a critical requirement for Internet of Things (IoT) applications, and antenna placement represents an important factor influencing coverage and stability. To evaluate this, field experiments were conducted at Universiti Teknikal Malaysia Melaka (UTeM) using custom-designed LoRa nodes equipped with Global Positioning System (GPS) modules to enable precise geolocation data logging. The receiver was placed inside a moving vehicle to replicate dynamic IoT data collection scenarios. Measurements of the Received Signal Strength Indicator (RSSI) were obtained for three different antenna heights: 1.5 m, 5 m, and 10 m. Experimental results reveal that elevating the antenna significantly improves RSSI values, thereby enhancing signal coverage, reducing attenuation, and extending communication range. In particular, the 10 m antenna placement yielded the most stable and reliable connections across larger distances, demonstrating its suitability for large-area IoT deployments. The findings provide empirical evidence on the influence of antenna height in LoRa systems and highlight practical considerations for network planning.

Keywords— geolocation, LoRa, 915 MHz, RSSI, Antenna Height

INTRODUCTION

The Internet of Things (IoT) demands wireless communication technologies that are low-power, low-cost, and capable of long-range coverage. Among the available Low-Power Wide Area Network (LPWAN) technologies, LoRaWAN has gained significant attention due to its open-access specifications, low deployment cost, and ease of integration into existing systems. It enables the development of private networks without relying on cellular infrastructure, making it suitable for large-scale and remote IoT applications. LoRaWAN is particularly effective when devices are distributed across wide areas, offering reliable connectivity over distances of several kilometers while maintaining minimal power consumption [1].

LoRa operates in unlicensed sub-GHz frequency bands and supports long-range, low-power communication, making it ideal for various applications such as smart cities, industrial monitoring, precision agriculture, and environmental sensing [2].

NB-IoT, Sigfox, and LoRa are often viewed as complementary LPWAN technologies rather than direct competitors. NB-IoT, which operates in licensed spectrum, provides high reliability and wide-area coverage through cellular infrastructure but at higher cost and power consumption compared to unlicensed LoRa [3]. Coverage studies report NB-IoT ranges of 9–14 km in urban areas and up to 100 km in rural settings, while LoRa typically achieves 6 km in urban and up to 35 km in rural environments at 868 MHz, with even greater range at 433 MHz due to lower path loss [3], [4]. The findings at 433/915 MHz are consistent with this frequency dependence, showing that 433 MHz supports more robust long-distance links, whereas 915 MHz remains reliable with optimized parameters. Sigfox, based on ultra-narrowband transmission, offers scalability but is limited by small payload sizes and strict daily message caps [5]. In contrast, recent studies of LoRa at 2.4 GHz highlight the trade-off between higher frequency operation and reduced coverage, with outdoor ranges typically only a few kilometers [6]. Overall, these comparisons indicate that sub-GHz LoRa, particularly at 433 MHz, remains highly suitable for cost-effective, long-range IoT deployments in obstructed environments.

As demand increases for scalable and energy-efficient IoT solutions, LoRaWAN remains a leading technology for reliable communication. However, deploying IoT systems in the 915 MHz band presents challenges, particularly signal degradation due to environmental obstructions and suboptimal antenna placement. In complex environments like the Universiti Teknikal Malaysia Melaka (UTeM) campus, inadequate deployment planning can significantly affect communication reliability [7]. This study gathers data on Received Signal Strength Indicator (RSSI) to analyze signal performance and provide recommendations for optimizing deployment strategies.

This work integrates the Global Positioning System (GPS) into the LoRa node setup to ensure accurate location tagging of each signal measurement. GPS enables the recording of spatial positions at the exact moment each RSSI and SNR value is captured, allowing each signal reading to be accurately matched with its corresponding geographic coordinate. The integration of GPS modules in modern IoT systems enhances the capability of devices to transmit geolocation data over long distances, even in areas with poor cellular coverage. This is particularly useful in mobile or geographically dispersed deployments, including asset tracking and environmental monitoring [8][9].

Moreover, LoRaWAN devices increasingly incorporate GPS modules to support precise geolocation reporting in remote or mobile contexts. Field tests on vehicle and tracking applications demonstrate that LoRaWAN remains robust even with Doppler shifts and mobility, validating its suitability for dynamic IoT deployments [10]. The integration of GPS with appropriately positioned LoRa antennas, including those installed on vehicles or mobile units, enables reliable transmission of geolocation data using low power across wide areas. These results highlight the significant role of antenna height in enhancing LoRaWAN performance and provide practical insights for designing efficient low-power, wide-area IoT deployment

Recent simulation studies have confirmed that antenna height has a significant effect on key performance metrics, showing that placing nodes at higher positions leads to improved packet delivery ratios in both static and mobile scenarios [11]. Experimental investigations in agricultural environments similarly highlight that increasing receiver or gateway antenna height reduces obstructions, enhances RSSI and SNR, and extends coverage reliability [12]. Xu et al. [12] demonstrated that in maize fields, elevated antennas enhanced long-range LoRa link reliability, evidenced by stronger RSSI, SNR, and lower packet loss.

In indoor localization scenarios, [13] stress that using their Height-based Empirical simulation (HEM) to simulate RSSI with specific transceiver height produces significantly fewer prediction errors than conventional distance-only models. In addition, Tandiawan et al. [14] point out that when transmitting and receiving antenna height variations in indoor-to-outdoor BLE scenarios are taken into consideration, the system performance of RSSI-based location increases.

All these investigations together demonstrate that antenna height is an important consideration for RSSI optimization and ought to be incorporated into experimental design and propagation modeling.

Thus, this work proposed experimental evaluation of LoRa with integrated GPS capabilities in an extensive measurement campaign across the main campus of UTeM. The study of mapping in the signal performance of this work assesses the current spectrum utilisation in this frequency band using RSSI at predetermined campus locations. The paper is organised as: section II explains a detailed research method and section III discusses the result of the measurement. Finally, section IV concludes the outcome presented in this paperTop of FormBottom of Form

METHODOLOGY

This study presents a comprehensive methodology to evaluate the performance and feasibility of Arduino-based LoRa nodes for long-range, low-power communication applications. The approach involves configuring and testing Dragino LoRa shield as transmitters and receivers operating at 915 MHz, equipped with Neo-6M GPS module to gather precise location data.

Development of LoRa Node integrated GPS

The system consists of two main components, the transmitter and the mobile receiver.  The transmitter is built using a LoRa node, an Arduino Mega 2560 microcontroller, and a 5V portable power supply. In this setup, the Arduino generates data, which is then transmitted by the LoRa node, while the power supply ensures continuous operation of the transmitter. The receiver uses a similar configuration as the transmitter but includes an additional GPS module. This GPS module captures latitude, and longitude coordinates each time a signal is received from the transmitter.

Location for Measurement

This study selects the open space area at Faculty of Electronic & Computer Technology Engineering (FTKEK), Universiti Teknikal Melaka Malaysia (UTeM) as the most suitable location for placing the transmitter, primarily due to its elevated terrain. High elevation is a well-established factor in improving signal transmission efficiency, as it helps optimize line-of-sight while minimizing potential obstructions caused by surrounding buildings and terrain variations [15].

By placing the transmitter on elevated ground, it ensures wider and more efficient coverage of the 915 MHz signal, which is critical for accurate performance evaluation across diverse campus environments [16]. This strategic placement also ensures consistency in the transmitter’s position, enabling a standardized basis for comparing signal strength across different receiver locations [17].

Comprehensive analysis of the signal’s behavior is achieved by systematically collecting receiver measurements from various locations across the UTeM main campus. The data collection process uses a mobile receiver mounted on a vehicle that follows pre-determined routes throughout the campus. Along these routes, signal strength indicators such as RSSI and SNR are recorded at consistent time intervals. This real-time, location-based approach reflects realistic IoT deployment conditions in diverse environments, allowing the study to effectively capture the variability and challenges associated with signal propagation [18].

The evaluation of LoRaWAN network performance requires the measurement of several critical parameters, starting with the RSSI. RSSI is a widely recognized metric for assessing signal quality and range, as it directly reflects the power level of the received signal. Another essential parameter is the SNR, which evaluates the ratio of the received signal power to the background noise. SNR is a key determinant of data reliability, particularly in areas with high interference levels.

Measurement setup

A thorough assessment of LoRaWAN performance was conducted using an organized measuring setup that combined hardware, software, and operational parameter setups. Table 3.1 lists the operational parameters that were used in this work.

TABLE I Operational Parameters

A 125 kHz bandwidth was chosen for the LoRaWAN system, as it offers a good balance between data rate, communication range, and network performance. The selected bandwidth is well-suited for typical IoT applications, as it balances reliable data transmission with robust signal integrity across diverse environments [19]. Specifically, a 125 kHz bandwidth supports extended transmission range, whereas a 250 kHz bandwidth enhances signal reliability by offering improved signal-to-noise ratio (SNR) performance [20].

Fig. 1 illustrates the system configuration used in this study, showing the relationship between the LoRa transmitter mounted at various heights on the FTKEK building and the mobile receiver mounted on a vehicle. Parameters such as spreading factor and bandwidth are configured in the transmitter and receiver pair to support long-range signal propagation over the 915 MHz ISM band.

The transmitter was configured to achieve optimal signal coverage by placing the LoRa nodes at three different heights around the FTKEK is shown in Table2. The low-height setup was located at ground level in the FTKEK open field to observe signal behavior near the ground. The medium-height setup was placed on the first floor of the bridge connecting between laboratory buildings, providing a partially obstructed environment. The high-height setup was positioned on the second floor of the same bridge to maximize line-of-sight and reduce obstructions. All the measurement setup is displayed in Fig. 2.

Fig. 1 Measurement of RSSI with Mobile Receiver

TABLE 2 LoRA Transmitter Node Location

Fig 2. LoRa Transmitter placement in 3 scenarios

RESULT AND DISCUSSIONS

A clear and constant correlation between antenna height and connectivity was shown by the measurement data that was gathered. The collected data was processed using MATLAB and Google Maps to generate coverage maps illustrating the geolocation distribution of RSSI across the campus. These maps were complemented by comparative analyses of the average RSSI values obtained for each antenna height.

The prototype of Lora transmitter node and Mobile receiver is shown in Fig. 3 and Fig. 4 illustrate how it was placed on the car for measurement purposes.

Fig3. Prototype of the Mobile LoRa

Fig. 4 Placement of Mobile LoRa on the car dashboard

Fig. 5, 6 and 7 illustrate the geolocation distribution of mobile LoRa measurements obtained around Universiti Teknikal Malaysia Melaka (UTeM). The plot, generated using Google Maps, overlays the recorded GPS coordinates with corresponding signal strength indicators. Markers in varying colors represent different RSSI categories, where red denotes weak signals, blue indicates moderate reception, and yellow marks the LoRa transmitter location.

SF12 was selected for the measurements as it provides greater resistance to noise and supports longer communication distances due to its lower data rate. While RSSI decreases gradually with distance, the relatively stable SNR indicates consistent communication quality, making SF12 well-suited for evaluating long-range LoRa performance.

Fig. 5 presents the geolocation mapping of LoRa signal strength measurements obtained with a low antenna height, whereas Fig. 6 illustrates the corresponding results for a medium antenna height. The comparison reveals that increasing the antenna height from low to medium improves signal distribution and coverage consistency across the UTeM campus, as evidenced by the wider spread of moderate-strength reception points in Fig. 6 and Fig. 7.

Fig 5. Geolocation mapping of Mobile LoRa and signal strength for Low antenna height

Fig 6. Geolocation mapping of Mobile LoRa and Signal Strength for Medium Antenna Height

Fig 7. Geolocation mapping of Mobile LoRa and Signal Strength for High Antenna Height

The measured RSSI values for three antenna height configurations are shown as a function of transmission distance in scatter plot Fig. 8.  The measurements span a range of 0 to 0.6 km, with RSSI values recorded in dBm. The results demonstrate a consistent decline in RSSI as the distance from the transmitter increases, which aligns with the expected behavior of signal attenuation in open environments. Notably, antenna height significantly influences signal performance. The high antenna configuration consistently yields superior RSSI values across all measured distances, followed by the medium and low configurations.

At shorter distances (<0.2 km), the RSSI differences among the three height levels are relatively minor. However, as the distance increases, the disparity becomes more distinct. The low antenna setup exhibits a steep decline in RSSI, reaching values below -115 dBm at the farthest point, whereas the high antenna maintains RSSI above -95 dBm throughout. These findings validate recent studies that emphasize the positive correlation between antenna height and RSSI [21][22].

Fig 8. Scatter plot for RSSI versus distance at different antenna heights.

TABLE 3 Statistical Analysis of RSSI

The statistical analysis of Received Signal Strength Indicator (RSSI) across three antenna heights in Table 3 provides clear evidence of the impact of elevation on LoRaWAN signal performance. At the low height (1.5 m), the mean RSSI was recorded at –115.73 dBm, with a relatively low standard deviation of 2.76 dB, indicating weak signal strength but comparatively stable reception. The maximum RSSI at this level was –108 dBm, reflecting significant path loss likely due to ground-level obstructions and multipath fading.

The high antenna placement (10 m) yielded the strongest performance, with a mean RSSI of –101.15 dBm, corresponding to an overall improvement of more than 14 dB relative to the lowest height. The maximum RSSI reached –87 dBm, indicating significant enhancement in link quality. Although the standard deviation increased further to 4.25 dB, the stronger signal strength and wider coverage outweigh the variability.

These results confirm that higher antenna elevation reduces propagation loss and improves link reliability, consistent with existing studies on low-power wide-area network performance [22], [23]. The findings highlight the importance of optimizing antenna placement to enhance coverage and stability in large-scale IoT deployments.

CONCLUSIONS

The experimental results confirm that antenna height is a key determinant of LoRaWAN performance in the 915 MHz ISM band. Measurements across three elevation levels demonstrated that higher antenna placement yields stronger RSSI, improved coverage, and extended communication range, despite slightly increased variability. These findings emphasize the importance of antenna deployment strategies in achieving reliable, large-scale IoT connectivity. Future work will extend this study by examining additional parameters, including spreading factors, bandwidth, and diverse environmental conditions, to further optimize LoRa network planning.

ACKNOWLEDGMENT

The authors are grateful to the Centre for Research & Innovation Management (CRIM) and Universiti Teknikal Malaysia Melaka (UTeM) for the opportunity and support, including financial through relevant grants where applicable.

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