Software Defined Radio Platform Research Articles

Resonance-Frequency Tracking System Based on a Software-Defined Radio Platform

Resonance-Frequency Tracking System Based on a Software-Defined Radio Platform

Ionospheric high-frequency Doppler shift based on a universal software-defined radio platform

Ionospheric high-frequency Doppler shift based on a universal software-defined radio platform

Agile FPGA Computing at the 5G Edge: Joint Management of Accelerated and Software Functions for Open Radio Access Technologies

This paper presents ReproRun, a flexible and extensible run-time framework for the reconfiguration of functions in field programmable gate array (FPGA) devices used in popular software-defined radio (SDR) platforms. The FPGA devices embed a hardwired or soft processing system (PS) which communicates with the programmable logic (PL) using a standard embedded bus interface. In order to apply a seamless run-time partial reconfiguration, we made use of all the related building blocks, design guidelines, and tools offered by AMD-Xilinx. In ReproRun, each partial bitstream targeting a reconfigurable region (RR) of the PL area comes with its respective firmware (i.e., software functions) that runs on the PS side. Our work guarantees run-time updates of the firmware without interrupting the functionality of other software processes running in the PS or PL, by employing a specialized controller, denoted as Run-timE firmWare reconfIguration contRollEr (REWIRE). The latter leverages the open asymmetric multiprocessing framework (OpenAMP). The partial bitstreams and respective firmware are fetched from a remote location using the trivial file transfer protocol (TFTP). ReproRun can be applied in different FPGA accelerators residing in disaggregated open radio access network (RAN) equipment, adaptive radio access technologies, and Edge servers hosting virtualized functions.

Frequency Instability Impact of Low-Cost SDRs on Doppler-Based Localization Accuracy.

In this paper, we explore several widely available software-defined radio (SDR) platforms that could be used for locating with the signal Doppler frequency (SDF) method. In the SDF, location error is closely related to the accuracy of determining the Doppler frequency shift. Therefore, ensuring high frequency stability of the SDR, which is utilized in the location sensor, plays a crucial role. So, we define three device classes based on the measured frequency stability of selected SDRs without and with an external rubidium clock. We estimate the localization accuracy for these classes for two scenarios, i.e., short- and long-range. Using an external frequency standard reduces the location error from 20 km to 30 m or 15 km to 2 m for long- and short-range scenarios, respectively. The obtained simulation results allowed us to choose an SDR with appropriate stability. The studies showed that using an external frequency standard is necessary for minimizing SDR frequency instability in the Doppler effect-based location sensor. Additionally, we review small-size frequency oscillators. For further research, we propose two location sensor systems with small size and weight, low power consumption, and appropriate frequency stability. In our opinion, the SDF location sensor should be based on the bladeRF 2.0 micro xA4 or USRP B200mini-i SDR platform, both with the chip-scale atomic clock CSAC SA.45s, which will allow for minor positioning errors in the radio emitters.

Spray: A Spectrum-efficient and Agile Concurrent Backscatter System

Recent works have achieved considerable success in improving the concurrency of backscatter network. However, they do not optimize the balance between throughput and spectrum occupancy, both of which serve as pivotal parameters in concurrent transmissions. Moreover, these works also introduce complex components on tag thereby increasing both power consumption and deployment costs. In this article, we propose Spray , a tag-lightweight system to achieve high throughput and narrow-band occupancy with low power. The key idea is to incorporate an agile channel allocating and scheduling mechanism into the backscatter network. This approach allows for efficient spectrum utilization and concurrency without the need for energy-intensive components. To optimize throughput in the presence of the challenge of harmonic interference, we introduce a novel algorithm that determines the channels with an optimal combination of central frequencies and bandwidths. Additionally, we propose a fair scheduling strategy to ensure equitable transmission opportunities for all tags. We prototype the Spray tag using commercial off-the-shelf components and implement the excitation and receiver with software-defined radio platform. Our evaluation shows that the system supports 30 parallel tags transmitting in the bandwidth of 600 kHz and the throughput can reach more than 280 kbps.

Реалізація алгоритму пошуку кореляційного інтерферометричного пеленгатора засобами програмної платформи GNU радіо

In the realm of modern radio equipment development, the integration of Software Defined Radio (SDR) systems, encompassing both software and hardware components, has become widespread. SDR systems, particularly, find applications in the creation of direction finders for radio signal sources. The effectiveness of direction finding and the identification of radio radiation sources largely hinge on the technical specifications of the equipment. For contemporary systems aimed at detecting the location of radio radiation sources, direction finders based on a correlation interferometer prove to be highly suitable. These direction finders excel in performing direction finding for a wide array of radio signals, capable of recognizing broadband modulated signals. They can simultaneously process and identify several signals within a single frequency channel, originating either from a singular source of radio signals (coherent) or from multiple sources (incoherent). SDR technology enables programmable reconfiguration of a radio receiver through software. Such receivers boast a broadband radio frequency component with a significant dynamic range, a high-speed Analog-to-Digital Converter (ADC) path, a robust signal processor, and a specialized digital filtering path. SDR receivers are adaptable to signals of various standards and frequencies, depending on the specific tasks at hand. The GNU RADIO software platform stands out as the most flexible open-source software platform for SDR systems. This article delves into the utilization of the GNU RADIO software platform to implement the search algorithm for the direction finder of the correlation interferometer. The Ettus USRP N210 SDR platform was selected for implementing the direction finder using the correlation interferometer algorithm. This study introduces a two-channel software-controlled model of the direction finder, operating according to the correlation interferometer algorithm. The measurement results for the placement angle of radio signal sources yielded an individual absolute error ranging from 2 to 4 degrees, with an average absolute error of about 3 degrees. These results are quite commendable for such mobile two-channel systems. While systems with four or more channels boast higher accuracy, they tend to have lower economic feasibility.

SDR-Based Portable System for Evaluating Exposure to Ambient Electromagnetic Fields

This paper discusses the need to accurately determine the population’s exposure to low-intensity radio-frequency electromagnetic fields (RF-EMF) from modern technologies like mobile networks, Wi-Fi, and IoT and proposes a practical solution for this assessment. There is no scientific consensus on the biological effects, mostly due to challenges in conducting accurate biological experiments. Recent research suggests that real-life exposure sources trigger stronger biological responses than laboratory-generated RF-EMF. However, there is a lack of research comparing the effects of these sources. This paper introduces a portable system for assessing and monitoring EMF exposure in urban areas. Employing a Software-Defined Radio (SDR) platform to ensure adaptability, the system incorporates two measurement configurations. The initial version concentrates on determining the average power within a 20 MHz Wi-Fi channel, whereas the subsequent configuration augments its functionality by introducing a frequency sweep. This sweep broadens the scrutinized bandwidth, thereby enriching the captured data content through the storage of spectrum sweeps corresponding to each average power value. These data can be used to create EMF profile maps based on individuals’ geographical coordinates. Compared to current limited-performance commercial exposimeters, the proposed system offers expanded capabilities by broadening the frequency bandwidth, georeferencing measurements, and storing data in an SQL database. Compared to high-performance commercial exposimeters, the major advantage of the system is its ability to detect short-term fluctuations in signal spectra and store the corresponding data for subsequent analysis.

Combining Software-Defined Radio Learning Modules and Neural Networks for Teaching Communication Systems Courses

The paradigm known as Cognitive Radio (CR) proposes a continuous sensing of the electromagnetic spectrum in order to dynamically modify transmission parameters, making intelligent use of the environment by taking advantage of different techniques such as Neural Networks. This paradigm is becoming especially relevant due to the congestion in the spectrum produced by increasing numbers of IoT (Internet of Things) devices. Nowadays, many different Software-Defined Radio (SDR) platforms provide tools to implement CR systems in a teaching laboratory environment. Within the framework of a ‘Communication Systems’ course, this paper presents a methodology for learning the fundamentals of radio transmitters and receivers in combination with Convolutional Neural Networks (CNNs).

CRB-based comparative study of array signal processing direction finding methods supported with SDR platform implementation

Radio Direction-Finding (DF) is an extremely important process in numerous commercial and military applications. Array signal processing-based DF methods have been developed to improve estimation performance in recent applications that require higher resolution and accuracy. Practically, angle of arrival (AOA) estimation is challenging due to various intrinsic and extrinsic parameters that affect the results. Therefore, clarifying these parameters and researching their impact on various DF methods are considered important research topics. The Cramer-Rao Bound (CRB) for estimating AOA is calculated based on a model of a linear antenna array system. This bound identify the factors that significantly impact the estimation performance. The current study conducts a comparative analysis of the most widely used array-signal-processing-based direction-finding (DF) methods under different conditions of the CRB parameters. According to the simulation results, Multiple Signal Classification (MUSIC) AOA estimator provides more accurate and stable results. Accordingly, it is chosen for implementation using a prototype testbed based on Software Defined Radio (SDR) technology using National Instruments Universal Software Radio Peripheral (NI-USRP) platform version 2930. Experimental outcomes were tested at various AOA values. The appendix includes the complete derivation for the CRB relation applied on the system model.

A Channel Rendezvous Algorithm for Multi-Unmanned Aerial Vehicle Networks Based on Average Consensus.

Realizing the distributed adaptive network construction of multi-UAV networks is an urgent challenge, as they lack a reliable common control channel and can only maintain a limited sensing range in crowded electromagnetic environments. Multi-unmanned aerial vehicle (UAV) networks are gaining popularity in many fields. In order to address these issues, this paper proposes a multi-UAV network channel rendezvous algorithm based on average consistency. The goal of the algorithm is to adjust the communication channels of each UAV to converge on the same channel, since the communication link of the multi-UAV network is broken due to interference. The proposed memory-based average consistency (MAC) algorithm utilizes the network adjacency matrix as prior information. Furthermore, for the case where the adjacency matrix is unknown, this paper also proposes the Multi-Radio Average Consensus (MRAC) algorithm, which achieves a beneficial trade-off between rendezvous performance and hardware cost. Simulation results demonstrate that the proposed MAC and MRAC algorithms provide superior network convergence time and scalability in networks of different densities. Finally, a hardware simulation platform based on a multi-UAV network was designed using a software-defined radio platform, and experimental simulations were performed to prove the effectiveness of the MAC algorithm in a real environment.

Deep Learning - Powered Radio Frequency Fingerprint Identification: Methodology and Case Study

Radio frequency fingerprint identification (RFFI) is an authentication technique that identifies wireless devices by analyzing the characteristics of the received physical layer signals. In recent years, RFFI has been significantly enhanced by deep learning. A neural network (NN) is often leveraged to predict device identity. As a data-driven approach, deep learning requires the collection of large amounts of data for NN training. In addition, the RFFI system should be evaluated on datasets collected under various conditions to assess the system's robustness. However, only a few RFFI datasets are publicly available, and there are no clear guidelines for building an RFFI testbed for data collection. This paper presents a tutorial to build both closed-set and openset RFFI systems. A LoRa- RFFI testbed is created as a case study and the implementation details are described in depth. The LoRa-RFFI testbed involves 60 commercial-off-the-shelf (COTS) LoRa development boards as devices to be identified, and a USRP N210 software-defined radio (SDR) platform for physical layer signal reception. Experiments are carried out using the implemented LoRa-RFFI testbed, and the collected datasets are made publicly available online. It is anticipated that this work can aid the research community in constructing RFFI testbeds and facilitate the development of RFFI research.

A study on mobile telecommunication systems using OpenAirInterface platform

Significant progress has been made in deploying 5G mobile networks in the last few years, providing rapid connectivity and low-latency communications. This study thoroughly analyzes the deployment of 5G networks utilizing the Open Air Interface (OAI), a free and open-source wireless communication technology. The survey gives a general overview of OAI's various fields and applications. It then looks at numerous uses and industries where OAI-based networks for 5G have been effectively implemented. The paper includes in-depth discussions of OAI's technical features and information on how it supports creating software-defined radio (SDR) platforms for 5G networks. It emphasizes OAI's versatility and flexibility, allowing researchers and developers to test various network setups and protocols. The survey's results show how OAI is becoming increasingly crucial to designing and rolling out 5G networks in various sectors. Researchers and professionals can investigate fresh applications and services that make the most of 5G technology by utilizing the capabilities of OAI. The taxonomy is designed and developed by categorizing the existing proposed solutions using OAI to easily deploy mobile telecommunication networks cost-effectively and flexibly to support various features and functionalities. Each category in the developed taxonomy is discussed and compared regarding multiple parameters.

Wireless Communication Between Multi-FPGAs

PHY Layer implementation of the IEEE 802.11 a/g/n Wi-Fi standard using Software-Defined Radio (SDR) architecture. It addresses the challenge of implementing Wi-Fi on SDR platforms, which has been difficult due to the strict timing requirements of Wi-Fi protocols such as the Short Inter-Frame Space (SIFS) and the need for low-latency communication between the radio front-end and the processing unit. This architecture enables the implementation of the PHY (Physical layer) and low-level MAC (Media Access Control) functionalities in the FPGA, ensuring low latency and precise timing control. Key Words:

Improved TDD operation on Software-Defined Radio platforms towards future wireless standards

Software-Defined Radio (SDR) platforms are valuable for research and development activities or high-end systems that demand flexible wireless protocols. While low-latency digital baseband processing can be achieved using a dedicated processing unit, like an FPGA or hardware accelerator, its multi-purpose Radio Frequency (RF) front-end often poses a limitation. Zero Intermediate Frequency (ZIF) transceivers are favorable for SDR, however, even for Time Division Duplex (TDD) systems, these transceivers suffer from self-interference when the transmitting and receiving Local Oscillator (LO) is set to the same frequency. To achieve low self-interference, switching from receiving to transmitting mode is needed. However, the time this takes (turnaround time, TT) for configurable RF front-ends often violates the strict timing requirements of protocols like Wi-Fi and 5G, which require response times in the order of microseconds. In this work, we first evaluate the advantages and disadvantages of several methods to suppress self-interference of a ZIF transceiver. Next, a novel approach is proposed, which can reduce the TT to as low as 640ns using the widely used AD9361 configurable ZIF RF front-end, while the noise floor is at the same level as achieved by the conventional way of switching between transmit and receive mode. We have realized and validated this approach using openwifi — an open-source Wi-Fi implementation on SDR. As a result, the receiver sensitivity is improved by up to 17dB in the 2.4GHz band and 9.5dB in the 5GHz band, for over-the-air transmissions.

Real-Time Statistical Measurement of Wideband Signals Based on Software Defined Radio Technology

The increase in channel bandwidth and peak-to-average power ratio (PAPR) of modern communication standards poses a serious challenge to performing channel power (CP) and complementary cumulative distribution function (CCDF) measurements in real-time using standard measurement solutions based on spectrum analyzers (SA). Recently, Software Defined Radio (SDR) technology has become a viable alternative to the conventional real-time spectrum monitoring approach based on SA due to its reduced cost. Therefore, in this paper, we propose a novel, innovative, agile and cost-effective solution to enable both CP and CCDF measurements on a state-of-the-art SDR platform. The proposed solution exploits the ability of the SDR equipment to access signal samples in the time domain and defines both CP and CCDF-type measurements. The two measurement functions are software implemented in GNU Radio by designing customized blocks and integrated into a graphical user interface. The proposed system was first tested and parameterized in a controlled environment using emitted signals specific to the IEEE 802.11ax family of wireless local area networks. After parameterization, the SDR-based system was used for over-the-air measurements of signals emitted in the 4G+, 5G and 802.11ax communication standards. By performing the measurement campaign, we have demonstrated the capabilities of the measurement system in performing real-time measurements on broadband channels (up to 160 MHz for IEEE 802.11ax). Altogether, we have proved the usability of CP and CCDF measurement functions in providing valuable insights into the power distribution characteristics of signals emitted by the latest communication standards. By exploiting the versatility of SDR technology, we have enabled a cost-effective solution for advanced real-time statistical measurements of modern broadband signals.

Implementation of a Low-Cost Chipless RFID System With Paper-Based Substrates Printed Tags for Traceability Applications in the Packaging Sector

Increasing competitiveness as well as levels of sustainability are some of the main challenges that the packaging sector is facing. The introduction of information and communication technologies provides new functionalities, such as traceability within logistic processes. In this context, RFID technologies can play a key role but can also pose hurdles, owing to increased cost, as well as to difficulties in relation with recycling and complying with product circularity. In this sense chipless RFID opens new possibilities, by avoiding the use of information coded chips, reducing costs in material and placement, as well by improving recyclability. In this work, a frequency based chipless RFID solution is presented, in which 2D geometrical patterns printed with conductive ink, resembling transmitive or reflective metasurfaces, are designed and integrated within paper-based substrates. An in-house reader system is implemented based on conventional Software Defined Radio platforms in the 0-6GHz and in the 0-12GHz range, in which received signal post-processing is performed to increase reader sensitivity, without the need of using Vector Network Analyzer equipment. Moreover, in order to reduce material waste, an automatic fault detection system based on artificial vision coupled to a robot arm is designed and tested. Different prototypes in paper substrates as well as in reference printed circuit boards have been fabricated and measured, showing good agreement. The proposed solution provides a feasible chipless RFID system with a portable low-cost reader which can be embedded in paper/cardboard materials in packaging applications.

Advanced Military Radio Channels Monitoring System Based on Software Defined Radio Platform: Preliminary Analysis

Abstract The use of electromagnetic spectrum monitoring for military emissions is essential due to the mobility and diversity of military operations. A tactical communications system used in the military domain includes encrypted and unencrypted data, voice and video communications using wideband and narrowband waveforms. This research focuses on the development of a high capability monitoring system based on Software-Defined Radio (SDR) technology for monitoring military waveforms. The implemented system has been tested for its ability to detect both wideband military waveforms and narrowband frequency hopping waveforms. The proposed SDR-based system provides a cost-effective solution for military waveform monitoring that can be used for real-time monitoring and analysis of the electromagnetic spectrum.

Implementation on SDR platform of algorithms for noncoherent reception of optimal signals built on the basis of eigenfunctions

Formulation of the problem. When transmitting data at speeds above the Nyquist barrier, the algorithmic and computational complexity of radio modems increases significantly, especially with incoherent signal reception. Non-coherent reception algorithms can be implemented on a software-defined radio platform, on which optimal signals are formed and received. The ability to programmatically change the radio frequency parameters of signals without making structural changes to the transmit-receive path can significantly reduce the computing resources of radio modems. The goal is to determine the possibility of practical implementation on the SDR platform (Software Defined Radio) of noncoherent processing algorithms with decision feedback with the choice of optimal values of the observation interval for symbol rates R>1/T using optimal signals built on the basis of eigenfunctions. Results. The possibility of using differential modulation of optimal signals, the forms of which are obtained as a result of solving an optimization problem in accordance with the criterion of the maximum decay rate of the spectrum level outside the occupied frequency band, is shown for packet data transmission protocols and the use of an incoherent processing algorithm in channels with additive Gaussian noise. It is shown that when using algorithms of incoherent element-by-element processing with optimization of the observation interval, it is possible to ensure stable reception of binary optimal signals up to transmission rates exceeding the Nyquist barrier by 1.66 times and for an error probability of 10–3, the energy loss is about 18 dB relative to potential noise immunity. The digital modem of optimal spectrally efficient signals, built on the basis of the SDR platform, makes it possible to conduct spectral and energy efficiency studies in real time in the presence of additive channel noise, and the influence of clock synchronization inaccuracies during packet messaging leads to energy losses of no more than 1 dB. Practical significance. The use of differential modulation of optimal signals can be used in digital television and radio broadcasting systems in the European digital television standards DVB-S2 (Digital Video Broadcasting Satellite Second Generation), DVB-T2 (Digital Video Broadcasting Terrestrial Second Generation).

Covert Channel Based on Quasi-Orthogonal Coding

The paper presents a method of creating a hidden channel using a signals’ superposition. According to this idea, a transmitter simultaneously sends overt and covert (secret) signals, whereby the overt signal is a carrier for the covert one. Due to the need to ensure a low probability of detection for covert communication, the covert signal should have low power. This implies a number of problems relating to its correct reception. This is similar to non-orthogonal multiple access (NOMA) systems, where the collective signal is a superposition of signals with different powers dedicated to different users. In this case, the successive interference cancellation (SIC) process is used in the receiver for the separation of the component signals. SIC requires accurate channel estimation. Even a small channel estimation error causes a significant increase in bit error rate (BER), performance degradation, or connection loss for covert transmission. This is due to the residual signal, i.e., the remnant of the cover signal after an imperfect SIC operation. The paper proposes a method of transforming (i.e., encoding) the applied hidden signal in such a way that the residual signal in the receiver is quasi-orthogonal to the hidden signal. The proposed model is based on appropriate sorting and, compared to methods with fixed constellation points, provides the covert channel with a low BER while maintaining high protection against detection as measured by the Kolmogorov–Smirnov distance. The proposed solution was tested using the USRP-2920 software-defined radio platform.

Effective autocorrelation‐based spectrum sensing technique for cognitive radio network applications

SummarySpectrum sensing based on detection techniques enables cognitive radio networks to detect vacant frequency bands. The spectrum sensing gives the opportunity to increase the radio spectrum channels re‐utilization. However, the main challenge in spectrum sensing is the simplicity of the considered detection approach and the amount of prior information needed to make an accurate decision. This paper proposes a novel sensing technique based on the autocorrelation function. This novel approach is based on the speed of convergence to zero of all autocorrelation coefficients. This technique shows the highest probability of detection for the same probability of false alarm target at low signal‐to‐noise ratio (SNR) compared with many standard detection techniques. The proposed method has been implemented using GNU Radio software and SDR (software‐defined radio) platforms. The experimental results show the effectiveness of the proposed method under real scenarios.