Advanced SDR-Based Custom OFDM Protocol for Improved Data Rates in HF-NVIS Links

Abstract

In the current context of global communications, HF (High Frequency) NVIS (Near Vertical Incidence Skywave) data networks can be of strategic importance, providing short- and medium-range communication capabilities independent of terrestrial configuration and existing conventional communications infrastructure. They are essential in critical conditions, such as natural disasters or conflicts, when terrestrial networks are unavailable. This paper investigates the development of such systems for HF NVIS data communications by introducing a customized Orthogonal Frequency Division Multiplexing (OFDM) protocol with parameters adapted to HF ionospheric propagation, implemented on Software-Defined Radio (SDR) systems, which provide extensive configurability and high adaptability to varying HF channel conditions. This work presents an innovative approach to the application of OFDM narrow-channel aggregation in the HF spectrum, a technique that significantly enhances system performance. The aggregation enables a more efficient utilization of the available spectrum and an increase in the data transmission rate, which represents a substantial advancement in NVIS communications. The implementation was realized using an SDR system, which allows flexible integration of the new OFDM protocol and dynamic adaptation of resources. The work also includes the development of a messaging application capable of using this enhanced HF communication system, taking advantage of the new features of channel aggregation and SDR flexibility. This application demonstrates the applicability of the protocol in real-world scenarios and provides a robust platform for data transmission under conditions of limited access to other means of communication. Thus, this study contributes to the technological advancement of NVIS communications and opens new research and deployment directions in HF communications.

1. Introduction

In the last decades, communications in the HF (High Frequency) band have been intensively studied, in particular in the context of the implementation of OFDM (Orthogonal Frequency Division Multiplexing) modulation using SDR (Software-Defined Radio) platforms. Numerous studies have explored the parameters required for ionospheric propagation and proposed innovative concepts such as channel aggregation in the HF spectrum.

OFDM represents a significant digital transmission technology that has been widely adopted in a multitude of modern communication systems, including Wi-Fi, Mobile WiMAX, LTE, and emerging fifth-generation (5G) networks [1]. OFDM is distinguished by its ability to split a high-data-rate stream into multiple low-data-rate streams, a capability that is advantageous in scenarios where high-data-rate streams are required but not the sole priority. Furthermore, it can be transmitted simultaneously on multiple subcarriers. The parallel transmission scheme employed by OFDM renders the technology highly resistant to interference and multipath fading [2], thereby enhancing its robustness and reliability across a range of communication environments.

A notable advancement in OFDM technology is the implementation of channel aggregation, which is also referred to as channel combining or carrier aggregation. The objective of this technology is to enhance overall data throughput by combining multiple narrowband channels to form a singular wideband channel [3,4]. Channel aggregation is the process of combining several contiguous or non-contiguous frequency bands (channels) to form a larger channel bandwidth [5,6,7].

The aggregation process results in an improvement in the overall efficiency of data transmission [8], as the combined bandwidth of the aggregated channels is utilized more effectively. Two principal categories of aggregation technology exist. The first is continuous aggregation, in which adjacent channels are combined to form a wider channel. The second method, non-contiguous aggregation, involves the combination of non-contiguous channels [9]. This approach provides greater flexibility with regard to spectrum usage.

OFDM channel aggregation offers a number of advantages. The technique increases data throughput by enhancing the total bandwidth, improving frequency efficiency through frequency slicing, and augmenting the system capacity to accommodate a greater number of users and more demanding data rates, particularly in high-density environments.

In today’s modern communications systems, such as those employing Wi-Fi and LTE-Advanced, channel aggregation is a widely utilized technique. Channel aggregation involves the combination of 20 MHz channels with higher bandwidths (40 MHz, 80 MHz, or 160 MHz) to achieve enhanced throughput in Wi-Fi standards, including Wi-Fi 4/5/6 [10]. Similarly, carrier aggregation permits the combination of up to five 20 MHz carriers, thereby achieving a bandwidth of up to 100 MHz in LTE-Advanced [11] and 5G [12,13].

OFDM is also becoming a popular choice in high-frequency (HF) data communications [14,15,16], where it is known to be a robust and efficient technology. The 3 to 30 MHz range is employed for long-range transmissions due to its capacity to reflect off the ionosphere [17]. Nevertheless, the attainment of high data rates and reliable communications in this band is challenging due to its narrow bandwidth. OFDM addresses these challenges by dividing the available bandwidth into a number of orthogonal subcarriers, each of which is modulated with a low-speed data stream [18,19].

The use of SDRs in the implementation of OFDM with channel aggregation in HF data communications offers significant advantages [20,21,22]. The flexibility and reconfigurability of SDR allows for dynamic software adjustments [23,24,25,26], enabling rapid protocol and bandwidth adaptation essential for efficient OFDM and channel aggregation.

A notable example is the study entitled “Channel Acquisition for HF Skywave Massive MIMO-OFDM Communications” [27], which investigates channel acquisition for HF skywave communications using Multiple-Input Multiple-Output (MIMO) and OFDM modulation techniques. This paper introduces the concept of “triple beams” in the space–frequency–time domain and proposes channel estimation and prediction methods, demonstrating superior channel acquisition performance.

Another relevant study is “OFDM over wideband ionospheric HF channel: Channel modeling & optimal system design” [28], which discusses wideband HF channel modeling and optimal OFDM system design for such channels. The paper introduces a 24 kHz bandwidth HF channel model and compares the performance of OFDM and single-carrier systems under various channel conditions.

Also, the paper “On the performance of OFDM and single-carrier communication over wideband HF channels” [28] provides a detailed comparison between OFDM and single-carrier communication systems over wideband HF channels. The study analyzes the performance of both modulation schemes under varying channel conditions and proposes the implementation of a wideband HF OFDM HF transceiver using SDR technology.

Most of these studies, as presented, have focused predominantly on theoretical simulations, without practical implementations to validate the effectiveness of the proposed solutions in real scenarios. This limited approach emphasizes the need for practical experiments to evaluate the performance and challenges associated with the actual implementation of these technologies in HF communications.

This paper extends the authors’ previous research on HF ionospheric propagation, SNR analysis, and OFDM implementation for HF data communications. It addresses the following objectives/contributions:

1.

HF propagation and SNR analysis: an extension of the HF NVIS ionospheric propagation studies and an analysis of the potential for implementing new protocols in the HF range to enhance data communications.

2.

Implementation and evaluation of a novel concept for the HF range—a custom OFDM system with aggregated channels using SDR: practical implementation and evaluation of an OFDM system with aggregated channels for HF data communication under laboratory and real conditions.

3.

Development of digital signal processing hardware and software: development of the hardware system and software applications required for the efficient transmission and reception of data in the RF spectrum.

4.

User interface development: develop an intuitive interface for HF data communication.

5.

Demonstration of system performance to users and investors: the validation of the system under real-world conditions and the presentation of practical results that demonstrate reliability to potential users and investors.

2. Materials and Methods

The test system was implemented using two USRP N210 SDRs (by Ettus Research, Mountain View, CA, USA) connected back-to-back through a power attenuator to simulate realistic signal conditions. Two laptops, each equipped with GNU Radio software, version 3.10, were used to develop and implement the OFDM transceiver and receiver. This setup allowed for the precise control and monitoring of the transmission and reception processes, enabling a thorough evaluation of the OFDM aggregated system’s performance in a controlled laboratory environment. The use of the GNU Radio provided a flexible and powerful platform for developing and testing the OFDM modulation and demodulation schemes necessary for effective HF communication.

OFDM with channel aggregation was implemented using the GNU Radio framework, augmented with Python blocks developed specifically for this project. The methods described include setting up the GNU Radio environment, building specialized computing blocks, and integrating and debugging these components within a simulated OFDM system.

2.1. Setting up the GNU Radio Environment

The experiments were performed using GNU Radio Companion (GRC), a graphical tool for designing and executing signal processing flowsheets. This environment is essential for the modular and interactive development of signal processing functionalities, especially when dealing with complex systems such as OFDM with channel aggregation. The GNU Radio flowgraphs were developed with reference to Figure 1 and Figure 2, which illustrate the transmitter and receiver, respectively.

2.2. Custom Python Block Development

To facilitate the implementation of OFDM with channel aggregation, two important Python blocks were developed, namely the “byte splitting” and “byte combining” blocks. These blocks, which ensure both effective distribution and accurate recombination of data streams, are central to managing the flow of data across multiple channels. Developed in Python, the block utilizes the NumPy library for efficient array management, crucial for handling large volumes of data at high speeds.

Byte splitter block: This block makes the distribution of data across different frequency channels and is responsible for splitting the incoming data stream into two separate paths. It operates at the packet level and manages the efficient partitioning of the data to increase the throughput and the resilience of the system.

Byte combiner block: Complementing the byte splitter, this block combines the separate data streams into a single output monitoring the packet headers. This process is critical to ensure that the aggregated data are correctly synchronized and integrated after they have been transmitted over multiple channels.

A notable technical achievement within the GNU Radio framework has been the development of custom Python blocks for OFDM channel aggregation. These blocks address the complex data handling requirements of a channel-aggregated OFDM system, thereby enabling enhanced communication capabilities and contributing to the advancement of modern HF digital communication systems.

2.3. Transmitter Application Flow Chart Development

In Figure 3, the implementation starts with a file source block, reading data from a specified text file and inserting it into a byte division block. The byte splitting block assigns a length identifier (packet_len) to each packet, which is essential for the correct handling of the packets in the blocks that follow. The purpose of this configuration is to have a continuous repetition of the contents of the file, and therefore a continuous flow of data.

The output of the byte splitter is split into two parallel paths, each leading to a block from the stream to the tagged stream. These blocks process the data, using the packet_len tag to mark the boundaries, by converting the stream into tagged packets of a specified length (in this case, 94 bytes). The processed streams are then fed into two identically configured OFDM transmitter blocks. Each OFDM transmitter block modulates the incoming stream on multiple orthogonal carriers of 64 and 16 symbols, respectively. The transceivers use BPSK for the header and QPSK for the payload, with pilot symbols and timing words to ensure proper receiver demodulation.

Figure 4 shows an implementation for processing and visualizing OFDM signals. The diagram starts with two parallel signal chains, each with a throttling block to set the sampling rate to 24 kHz, followed by an interpolated resampling block to increase the sampling rate to 240 kHz. The next channels are set in spectrum. This is done by multiplying the 50 kHz and −50 kHz cosine waves generated by the source blocks. The modulated signals, representing two parallel OFDM channels, are combined by an adder block that adds the OFDM aggregation into a single mixed signal.

This mixed signal is sent to a UHD receiver block: the USRP sink block, which interfaces with a USRP hardware device configured to transmit the signal at a center frequency of 7 MHz, with a sampling rate of 240 kHz and a gain value of 15. The diagram also includes QT GUI spectrum sinks to visualize the spectrum in real time at different stages: before and after resampling, modulation, and final transmission. This setup demonstrates a practical OFDM transmitter, showing how signals are generated, modulated, aggregated, and transmitted with GNU Radio and USRP hardware, while providing detailed spectral analysis to aid debugging and optimization of the communication process.

2.4. Receiver Application Flow Chart Development

The first receiving flowchart illustrates the reception of the signal and the first steps of processing. It starts with a UHD, a USRP source block that receives the signal from a USRP hardware device (Figure 5). A sample rate of 240 kHz and a center frequency of 7 MHz are configured on the USRP. This block provides the output of the received signal, which is split into two parallel paths for further processing.

Each path contains a signal source block that generates a cosine waveform with a frequency of 50 kHz and a frequency of −50 kHz, respectively. In order to demodulate the respective frequency components, these signals are multiplied by the received signal in Multiply Blocks. The resulting waveforms are then displayed in the QT GUI Frequency Sink block, which displays the full spectrum and specific channels (24 kHz bandwidth) for analysis of the received waveform. After multiplication, each signal is passed through a low-pass filter to isolate the desired frequency component and reduce noise.

The next flowchart focuses on OFDM demodulation and data recovery (Figure 6). It includes two OFDM receiver blocks that are configured to match the parameters of the transmitter, including the length of the FFT, the length of the cyclic prefix, and the modulation schemes (BPSK for the headers, QPSK for the payloads). These blocks are responsible for the demodulation of the incoming OFDM signals and the extraction of the data packets.

The output from each OFDM receiver is passed to a tag debug block and then converted from unsigned char to float using UChar To Float blocks for visualization purposes. The demodulated data are then combined using a byte combiner block based on the packet_len tag, where the original data packets are reconstructed. The combined data are then written to a file using a file sink block. QT GUI Time Sink Blocks, which display the data over time for debugging purposes, are also used to visualize the demodulated data streams.

2.5. Development of a Standalone Application

A standalone graphical application was developed as a means of facilitating the transmission and reception of HF OFDM. This involved the creation of a Python 3-based application, which employed GNU Radio libraries for signal processing and the Qt library for the development of a graphical user interface. The application was devised with the objective of facilitating HF chat messaging and file transfer utilizing the OFDM protocol and channel aggregation. The following section provides a comprehensive description of the implementation process.

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Flowgraph Design of GNU Radio

GNU Radio Companion V.3.10 (GRC): The preliminary configuration of the signal processing sequence is developed within the GRC, a graphical user interface that facilitates the arrangement of blocks via a drag-and-drop mechanism, thus defining the signal processing chain. The aforementioned graphical workflow is responsible for the modulation, demodulation, and aggregation processes, as previously outlined.

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Integration with Python Script

Generation of Python V.3 code: Once the flowgraph has been designed in GRC, it can be generated in a Python script. This script serves as the basic component of the application, taking responsibility for managing the data flow, signal processing, and interaction with the underlying hardware.

The Python script can be customized to meet specific requirements. The generated Python script is then modified to facilitate integration with the Qt-based graphical user interface (GUI). This involves adding tabs and buttons to allow direct manipulation of various parameters, including frequency settings, modulation parameters, and channel aggregation options via the GUI.

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Qt-based graphical user interface (GUI)

Qt library integration: The application uses the Qt library to build a standalone GUI. This is done using PyQt or PySide, Python bindings for the Qt library. These libraries allow developers to build sophisticated, cross-platform GUIs.

The transmitter interface, which is responsible for transmitting the signal in the HF OFDM transmitter, is as follows:

Figure 7 illustrates the transmitter interface. The figure shows a simple text box for sending messages, buttons for attaching files, and a real-time spectrum analyzer (Rx Spectrum) that displays the transmitted signal.

The GUI allows users to send text messages or files by clicking on the appropriate buttons. The transmitted signal spectrum is displayed in real time, providing the user with visual feedback on the quality of the transmission and bandwidth utilization.

The receiver interface (HF OFDM RECEIVER) is as follows:

Figure 8 shows the receiver interface, which includes both a frequency sink and a waterfall sink graph. The graphs allow the visualization of the received signal in terms of frequency spectrum and time, respectively.

Subsequently, an HF chat window is displayed to show incoming messages. In addition, the user has the option to save the messages or clear the chat history using the buttons provided.

Furthermore, the receiver GUI includes controls for frequency adjustment and other settings (Figure 9), enabling the user to adapt to changing channel conditions or interference.

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Develop the standalone application

Once this is complete, the application must be packaged. In order to create a standalone application, tools such as PyInstaller were employed to package the Python scripts and all dependencies into a single executable. This step is mandatory for deploying the application to different systems, and eliminates the need for users to manually install Python or GNU Radio.

Improved usability: additional features such as file logging, error correction, and encryption could be integrated into the application to improve usability and security, especially for the chat and file transfer features.

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Testing and optimization

The application has undergone rigorous field testing. The application has been tested in both laboratory conditions and real outdoor HF communication scenarios. This was done to ensure that the OFDM protocol and channel aggregation work efficiently under a variety of conditions, including different signal-to-noise ratios, interference, and propagation environments.

Performance tuning is a process designed to improve the efficiency and effectiveness of a system or component. Depending on the results of performance testing, the application may require additional optimization procedures, including refining modulation parameters, adjusting channel aggregation logic, and improving the responsiveness of the graphical user interface.

3. Results and Discussion

The tests, both under laboratory conditions and in real environments, were performed with SNR levels that meet minimum requirements, ensuring full information reception with minimum or without losses. In laboratory conditions the SNR was set at 20 dB. In the real test, measurements were taken at different frequencies to identify the frequency that provided the best SNR. Once the optimal frequency with the highest SNR was identified (greater then 20 dB), the final tests were performed and all subsequent measurements in this study were performed in this manner. Focusing the tests on the frequency with the best SNR ensured a fair and accurate evaluation of the transmission performance. This approach also allowed representative packet error rate (PER) values to be obtained that accurately reflect optimal transmission conditions. The settings of the OFDM protocol and the transmission parameters were adapted based on the results of previous studies carried out by the authors in order to guarantee an optimal system performance [25,26,29]. The goal of these tests was to demonstrate a working system composed of hardware system, digital processing implementation, and a graphical user messaging interface, allowing it to be tested and demonstrated in an accessible and intuitive manner. This approach facilitates the understanding of the system by users without advanced technical knowledge and represents an important initial step in demonstrating the capabilities and potential for the further extension of this technology.

3.1. Laboratory Conditions

In the first contiguous aggregation experiment, the OFDM system was configured to effectively utilize the available bandwidth by dividing it into closely spaced channels (Figure 10). The results show a clear and well-defined spectrum with a small gap between channels, indicating the efficient use of the spectrum, as viewed through the QT GUI Frequency Sink blocks.

The flexibility of the system in avoiding spectral regions affected by interference or regulatory constraints was demonstrated by the non-continuous aggregation configuration (Figure 11), in which channels are distributed with significant gaps in the spectrum. In dynamic spectrum access scenarios where certain frequency bands may be occupied or restricted, this form of aggregation is particularly advantageous.

The performance and comportment of the OFDM receiver with regard to contiguous and non-contiguous aggregation are illustrated by the label visualization in the time domain of the received data. The impact of frequency settings on the signal sources within the OFDM system is illustrated through the visualization of the received data time-domain tag in the context of contiguous and non-contiguous aggregation. In this implementation, the signal source blocks are configured to generate cosine waveforms at specific frequencies, such as 50 kHz and −50 kHz for non-contiguous aggregation, and 12 kHz and −12 kHz for contiguous aggregation. These frequency settings permit the creation of both contiguous and non-contiguous aggregation scenarios by directly influencing the arrangement of channels within the available spectrum.

The packet_num and rx_len labels for both channels are plotted as a function of time in the view. As can be observed, the OFDM receiver is able to successfully decode the received packets, as evidenced by the amplitude and no gaps in label values in the time domain, as can be seen in Figure 12. The stability of the rx_len and the lossless packet count growth indicate that the receiver is capable of handling the received data rate and maintaining synchronization, even when faced with potential channel impairments.

Then, the received OFDM packets were analyzed using a tag debug script designed to monitor and record, in a text file, key details in each packet header (Figure 13). This script captured information such as the unique number of each packet, the reception time (rx_time) reflecting the exact time of reception, and the offset—an indicator of the phase and frequency synchronization between the transmitter and receiver. In addition, channel tap values were recorded, essential for analyzing interference and signal variations on the communication channel. The packet length (packet_length), an important parameter for identifying possible errors or partial data loss during transmission, was also recorded.

In the next step, a Python script was developed to analyze the packets stored in the *.txt file after each transmission using the information collected by the debug tag. The script reads the details of each packet received from the file and performs specific calculations to determine the PER, a key indicator of transmission performance (Figure 14).

PER is calculated by comparing the number of packets received to the number of packets lost during transmission. To do this, the script parses the information in each packet and identifies missing or corrupt packets based on sequence numbers and other integrity parameters. The PER result for each transmission is then reported, giving an accurate picture of the error rate and reception stability for each OFDM transmission session.

The system demonstrated a consistent packet reception with stable synchronization and no loss if the SNR met the minimum requirement level packet in both contiguous and non-contiguous aggregation configuration proximity (the transmitted message reaching 100% of the received packet, as shown in Figure 14 and Figure 15). In the contiguous aggregation configuration, in which the subcarriers are located in close proximity, the system exhibited very good packet reception and synchronization, along with an absence of packet loss. In the non-contiguous aggregation scenario, in which distinct transmission frequencies were used, the system demonstrated its ability to reliably decode packets, despite the distance between them. This flexibility in channel arrangement allows the OFDM system to efficiently utilize the available spectral gaps, making it suitable for dynamic spectrum access.

The HF communications channel is highly variable and susceptible to a multitude of influences, including those emanating from the ionospheric environment, interference, and noise. The aforementioned factors result in the manifestation of high levels of signal degradation across the spectrum of channels. The use of different modulation schemes on each OFDM channel allows for the optimization of data rate and robustness in accordance with the specific conditions of each channel. The overall spectral efficiency of the system can be optimized by matching the modulation type to the specific signal-to-noise ratio (SNR) of each aggregated channel. The use of higher-order modulations is advantageous when the SNR is high, as this allows for more efficient utilization of the spectrum and an increase in the overall data throughput. The implementation of various modulation types on each OFDM channel allows for the development of adaptive communication strategies. Adaptive modulation and coding (AMC) enable the modulation scheme to be adjusted in real-time based on the evaluation of the channel conditions.

This adaptability ensures that the system can respond to changing conditions and continue to operate at optimal efficiency. It also allows the better utilization of available bandwidth and power resources, which is essential for long-distance HF communications.

The figure below (Figure 16) illustrates the outcomes of an OFDM aggregation test in an HF data link. One channel employs QPSK modulation, while another employs 8-PSK modulation. The objective of the test is to assess the functionality and performance of these two modulation schemes when combined in a non-contiguous aggregation configuration.

The utilization of Channel 1 with QPSK has been demonstrated to offer enhanced robustness and reliability, as evidenced by the uninterrupted reception of packets and the absence of gaps in the received data (packets 498–504) (Figure 16 and Figure 17). The relatively simple modulation scheme of QPSK provides superior resistance to noise and interference, thereby ensuring stable communication at 20 dB SNR.

In contrast, on channel 2, which employs 8-PSK modulation, there are numerous gaps in packet reception (packet numbers 576–597). Of the 21 packets analyzed, only 8 were correctly received at the receiving end (Figure 16). When the PER was analyzed, there was 38.72% of packets lost (Figure 18). Although 8-PSK modulation facilitates higher data transfer rates (approximately 327 packets more than QPSK over the analyzed time period T), its elevated susceptibility to signal degradation results in diminished packet reliability. In a challenging HF environment, the elevated complexity of 8-PSK increases its susceptibility to errors and need higher SNR to have low PER. This comparison highlights the importance of selecting appropriate modulation schemes for different channels to optimize performance in non-contiguous OFDM aggregation, and demonstrates the trade-off between data rate and robustness.

3.2. Real Field Conditions

In order to validate the performance and reliability of the standalone HF OFDM communication applications developed using GNU Radio and the Qt library, a real field-testing setup was deployed. The configuration comprised a fixed transmission system and a mobile receiving system. The principal objective was to assess the efficacy of the system in transmitting and receiving messages under conditions that approximate those encountered in the HF band, which are often characterized by variable propagation, interference, and noise.

Before all tests, measurements were taken at different frequencies to identify the frequency that provided the best SNR. Once the optimal frequency/frequencies with the highest SNR was identified (minimum 20 dB for BPSK modulation), the real-world test was performed.

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The fixed transmitter system comprises the following hardware components:

The Universal Software Radio Peripheral (USRP) N210 was employed in this configuration. The USRP N210 was employed as the principal hardware for the generation and transmission of OFDM signals. This device is renowned for its high performance and flexibility, rendering it an optimal choice for real-world communication testing.

Laptop: A laptop was connected to the USRP N210 via a Gigabit Ethernet interface. The laptop operated the standalone HF OFDM transmitter application, which was responsible for controlling the modulation, channel aggregation, and transmission processes.

A 4-W power amplifier was used to ensure that the transmitted signal would have sufficient power to reach the mobile receiver over a considerable distance. The amplifier augmented the signal power prior to its transmission via the antenna.

An inverted V antenna (Figure 19a), mounted on a mast, was employed to transmit the RF signal from the amplifier. This type of antenna is particularly well suited to HF communication, offering an optimal balance between performance and ease of installation. The antenna was tuned to operate within the target frequency range for HF transmission, which was used for the OFDM signal.

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Mobile Receiver System (Figure 19b)

Similarly, the USRP N210was used as the receiving hardware, in a manner similar to that of the transmitter. This approach ensured consistency in the hardware used, allowing any variations in performance to be attributed to environmental factors rather than differences in equipment.

Laptop: The laptop, which was running the standalone HF OFDM receiver application, was connected to the USRP N210. The application in question was responsible for the demodulation, decoding, and display of received messages and files.

A whip, HF antenna was also used. This antenna was selected on the grounds of its portability and ease of installation on the mobile platform. Despite its compact nature, the whip antenna proved to be an adequate means of capturing HF signals over moderate distances.

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The transmission and reception of messages:

The testing started with the transmission of basic text messages from the fixed transmitter (Figure 20). The mobile receiver, situated at different distances, successfully received the transmitted messages (Figure 21, Figure 22, Figure 23 and Figure 24). The process was repeated with different message lengths, including longer text messages and small file transfers, in order to assess the system’s capability to handle varying data sizes.

The quality of the received signal was monitored continuously using the receiver application’s real-time spectrum and waterfall displays. The analysis of the quality of the received signal was conducted in terms of SNR (the results were analyzed only for the test that met minimum 20 dB), PER (Figure 21), and the ability to decode the message correctly (Figure 22 and Figure 23).

To assess the system’s performance in the context of typical HF communication propagation challenges, a series of scenarios were tested. These included line-of-sight conditions, obstructed paths (e.g., behind hills or buildings), and varying distances.

The subsequent tests were conducted with the objective of evaluating the transmission of attached files. The system continues to demonstrate the same optimal performance as previously observed, in accordance with the specified SNR requirements.

To expand the scope of our field testing, additional experiments were conducted which focused on NVIS propagation, a technique commonly used for short to medium-range communication over distances typically ranging from 50 to 650 km. The utility of NVIS propagation lies in its capacity to facilitate communication in situations where direct, unobstructed line-of-sight is impeded by terrain, such as in mountainous or forested areas. The modification of the whip antenna on the mobile receiver enabled the experimental setup to be adapted for the assessment of NVIS propagation. The assessment was conducted with the objective of evaluating system performance in conditions that emulate real-world scenarios.

The propagation of NVIS is dependent upon the transmission of signals at an angle approaching vertical into the ionosphere. Subsequently, the signal is reflected at an acute angle back to Earth. This propagation mode results in a substantial increase in the coverage area surrounding the transmitter. Consequently, this approach represents an effective method for regional communication, eliminating the necessity for relay stations or repeaters.

In order to facilitate typical NVIS communication, the antennas in question must radiate the signal in a near-vertical direction. The transmitter is equipped with an inverted V antenna, which enables the achievement of NVIS propagation. To achieve this with the mobile receiver’s whip antenna, a simple modification was implemented: the antenna tip was tied down using a rope, effectively bending the antenna into a more horizontal orientation (Figure 25). This modification altered the radiation pattern of the antenna, focusing more of the energy upwards rather than towards the horizon, which is necessary for NVIS communication.

The results of the NVIS propagation tests demonstrated a notable increase in signal variability when compared to the findings of the ground wave propagation tests. The observed variations in signal strength were attributed to the inherent dynamic nature of ionospheric conditions, which can give rise to sudden changes in both reflection angles and signal path lengths.

The signal power received in NVIS mode was, on average, lower than that received in ground wave mode. This is to be expected, given that the signal propagates over a more extensive path, undergoing reflection off the ionosphere prior to reaching the receiver, which inevitably results in a degree of signal loss.

Despite the enhanced signal variability and diminished signal power, the communication system remained operational in the majority of instances. The OFDM modulation demonstrated efficacy in maintaining the integrity of the transmitted data, even in the context of fluctuating NVIS conditions. Despite the noted degradation in quality, messages and files were successfully received in most tests, although this was more challenging in certain conditions because of the high variation of SNR level during transmission.

The evaluation indicated that the system consistently maintained optimal functionality and data integrity across diverse modulation formats, provided the specified SNR thresholds are satisfied for each digital modulation employed.

4. Conclusions

The aim of this research was to develop an HF data communication system based on OFDM. This system introduces an important innovation for HF communications, the use of narrowband channel aggregation, which allows a significant increase in transmission rate and spectral efficiency. HF channel characteristics are highly variable due to ionospheric and noise variations, which makes the use of wideband channels (>12 KHz) for OFDM transmissions difficult and impossible due to peak-to-average variations, desynchronization, subcarrier frequency variations, etc. However, by using the higher bandwidths resulting from channel aggregation, the system has higher data transmission capabilities, but is less affected by the channel, making it ideal for applications requiring high throughput, such as advanced digital communication systems.

The flexibility of deployment on Software Defined Radio (SDR) platforms facilitates rapid configuration and efficient deployment. Both laboratory and real-world tests have shown that the application operates without packet loss under favorable SNR conditions, confirming the robustness and performance of the system.

An HF CHAT communication application has also been developed to integrate these innovative capabilities. The application provides an intuitive user interface that enables live chat and attachment transmission, enhancing the usability and efficiency of modern RF communications. A number of studies have been conducted on OFDM for HF links and channel aggregation into VHF/UHF broadband channels. However, many of these studies are still in the early stages of simulation and have produced no practical, usable systems. In contrast, our research has made significant progress, resulting in the prototyping of fully operational and efficient systems.

Future developments will be oriented towards conducting further field trials of the OFDM aggregation system in order to validate its performance in dynamic and challenging radio frequency environments. These tests will assess the system’s resilience to ionospheric variations, interference, and SNR, and will include long-distance communication trials. By knowing the lost packets at the receiver, the system will be set to resend only that packet, helping when SNR has low values. Moreover, in order to optimize the system’s performance under varying channel conditions, further improvements in adaptive modulation and encryption techniques, such as the Advanced Encryption Standard (AES), will be explored. Continued advances in SDR technology will support these innovations, paving the way for more efficient and reliable HF communications systems. Finally, the system will be modified to operate in full duplex, enabling it to function as a transceiver. This will be followed by a transition from the development stage to real-field testing. This marks a critical milestone in the research, where the system will be deployed in an actual field environment to be used under real applications.