Software Defined Radio Research Articles

Multiple PUE Attack Detection in Cooperative Mobile Cognitive Radio Networks

The Mobile Cognitive Radio Network (MCRN) are an alternative to spectrum scarcity. However, like any network, it comes with security issues to analyze. One of the attacks to analyze is the Primary User Emulation (PUE) attack, which leads the system to give the attacker the service as a legitimate user and use the Primary Users’ (PUs) spectrum resources. This problem has been addressed from perspectives like arrival time, position detection, cooperative scenarios, and artificial intelligence techniques (AI). Nevertheless, it has been studied with one PUE attack at once. This paper implements a countermeasure that can be applied when several attacks simultaneously exist in a cooperative network. A deep neural network (DNN) is used with other techniques to determine the PUE’s existence and communicate it with other devices in the cooperative MCRN. An algorithm to detect and share detection information is applied, and the results show that the system can detect multiple PUE attacks with coordination between the secondary users (SUs). Scenarios are implemented on software-defined radio (SDR) with a cognitive protocol to protect the PU. The probability of detection (PD) is measured for some signal-to-noise ratio (SNR) values in the presence of one PUE or more in the network, which shows high detection values above 90% for an SNR of -7dB. A database is also created with the attackers’ data and shared with all the SUs.

Enhanced Resolution and Accuracy in Software Defined Radio Applications Using a SAR ADC with Integrated ECC Mechanism and Dual-Stage SAR Architecture

Enhanced Resolution and Accuracy in Software Defined Radio Applications Using a SAR ADC with Integrated ECC Mechanism and Dual-Stage SAR Architecture

Over-the-air testing of LTE-A PHY layer in reverberation chamber

Reliable, repeatable, and flexible testing is crucial for assessing system performance and ensuring the quality of communication. In reverberation chambers (RC), real-life propagation environments can be emulated by loading absorbers, facilitating controlled testing of the system. This work presents over-the-air (OTA) testing of the LTE-A PHY layer in the RC. We assessed the performance of the LTE-A link using key performance indicators (KPIs) such as error vector magnitude (EVM), bit error rate (BER), and signal-to-noise ratio (SNR) for varying transmitter (Tx) and receiver (Rx) gains. Additionally, we have compared the results both in an empty RC and when the RC was loaded with RF absorbers. We used software-defined radio (SDR) for OTA transmission of LTE-A frames. The measurement results indicate that loading the RC with RF absorbers improves EVM, BER, and SNR. We also quantified the performance of the LTE-A link by changing the position of RF absorbers. Results showed that loading absorbers yielded up to 72.8% improvement in EVM, and placing absorbers closer to Rx helped reduce the amount of multipath, resulting in better transmission performance.

A switched full duplex MIMO architecture with digital linear and nonlinear cancellation

Enabling full duplex (FD) in MIMO systems is challenging due to increased hardware complexity and increased training overhead required for canceling not only self-interference (SI) but also cross-link-interference (CLI) signals, considering both linear and nonlinear effects on each stream. In this paper, we propose switched FD MIMO (FD-SW-MIMO) architecture as a low-complexity, low-overhead solution, which enables stream-based nonlinear estimation to be performed independently from channel estimation, so that those nonlinear reference signals are fed to linear SI and CLI cancellation stages. For improved performance at high transmit power levels, the Random Fourier Features - Least Mean Squares (RFF-LMS) algorithm is employed on the residual SI and CLI signals per stream. Our experiments conducted on a software-defined radio based 2x2 FD MIMO test setup reveal that the proposed FD-SW-MIMO architecture can provide up to 12 dB enhancement over linear only digital cancellation. The proposed architecture requires only minor hardware modification(s), avoiding active analog cancellation circuitry and extra Tx/Rx chains. Requiring the same training overhead as linear only cancellation, FD-SW-MIMO architecture can quadruple the rate of HD SISO for low to moderate transmit power levels, and for high transmit power levels, the HD SISO rate is tripled due to slightly increased overhead.

A Software-Defined Radio Platform for Teaching Beamforming Principles

This paper presents the development and validation of a hybrid beamforming system based on software-defined radio (SDR), designed for telecommunications engineering education. The system provides an agile and user-friendly platform that allows students to observe, test, and evaluate beamforming techniques in real time. The platform integrates a multichannel SDR device (USRP N310) with traditional radiofrequency equipment and open-source software, facilitating hands-on learning experiences. The paper details the proposed hardware and software architecture and documents the calibration and validation phases. The testing and validation processes were conducted using a 3.5 GHz antenna array in both indoor and outdoor environments. The results demonstrated the system’s effectiveness in achieving the desired beam orientations, with experimental results aligning closely with simulation and theoretical predictions. Significant differences in the radiation patterns observed between the indoor and outdoor measurements were documented, highlighting the impact of environmental factors on beamforming performance. The insights gained from this research provide valuable contributions to the education of future telecommunications engineers, enhancing their understanding of practical beamforming applications and the integration of modern SDR technology.

A PAPR correction scheme for LoRa self‐jamming waveforms

AbstractA LoRa self‐jamming scheme that enables secure and covert communications by adding jamming symbols when transmitting is proposed. The scheme has been validated in simulations. The work is continued by evaluating the scheme on real‐world software defined radio (SDR) equipment. Experiments immediately showed that a demodulation is impossible as the received signal is highly distorted. This comes from the fact that adding symbols at transmission actually generates high peak‐to‐average power ratio (PAPR) preventing proper waveform generation by the equipment's hardware. This paper presents a PAPR correction scheme that modifies the waveform. The properties of this modified waveform are analysed and the performances are assessed in simulations with realistic time and frequency synchronization assumption. For the ideal 0 dB PAPR corrected output, the SER performances are close to that of a legacy LoRa communication, while preserving the physical layer security capabilities of the self‐jamming scheme. It is finally shown that our PAPR correction scheme effectively recovers the self‐jamming properties on SDR devices.

Characterisation and synchronisation of a netted software defined radio radar

AbstractThe present work intends to characterise the combination of two netted software defined radios (SDR) and different radio frequency (RF) front‐ends installed in them, together with a two‐stratum time dissemination and synchronisation system. A modified implementation of the Network Time Protocol is used as coarse event synchronisation for either SDR back‐end. The White rabbit light embedded node implementation of the commonly known white rabbit synchronisation system (IEEE 1588 PTP‐2019) or arbitrary wave form generators are used as fine time dissemination system for either SDR. The resulting netted transceiver system is intended to compose a demonstrator for proof‐of‐concept experiments. The findings presented in this article show that the chosen combination of hardware and software is suitable for radar applications operating within L‐, S‐ and C‐bands. A channel coherency throughout the network with a relative modified Allan deviation of less than 80 fs for averaging intervals of 1 s, a phase noise better than −118 dBc/Hz at 10 Hz frequency offset and a fractional frequency lower than was measured. Within a single transceiver node, a fractional frequency lower than and phase noise of −124 dBc/Hz at 10 Hz frequency offset were measured as well. Multistatic radar systems exploit wide spatial diversity to enhance target detection and tracking, albeit with increased complexity when compared to a monostatic configuration. To exploit these benefits, all participating transceiver nodes within the netted radar need to synchronise to a common time base . The achieved synchronisation level increases the accuracy with which the chain of timed events at the transmitter and at the receiver side occur, intending to maximise the signal‐to‐noise ratio available at the receiver. The Universal software radio peripheral model X310 with two different daughterboard models as RF front‐end was used as SDR on either radar node. A network combining data and synchronisation purposes allowed the radar nodes under test to operate synchronously. The two‐stratum synchronisation system used glass fibres between 2 m and 5 km of length or coaxial cables with 2 m in length for network traffic, time and frequency dissemination purposes. The multiple RF front‐ends were stimulated by means of arbitrary waveform generators with calibrated traceability. Up‐chirp and sinusoid waveforms were used as stimuli for measuring the offset of either channel with regards of to ultimately estimate the achievable coherency limits of the system under test. Both analogue and digital evaluation methods were considered.

Real-time modulation classification architecture in software defined radio

Real-time automatic modulation classification (AMC) in software-defined radio (SDR), an emerging approach to blindly detect the modulation scheme in future wireless networks with applications ranging from civilian to military, has not received much attention with practical receiver architecture. This paper proposes a simple modified receiver architecture using reduced Convolutional Neural Networks (CNN) to achieve AMC, which is tested on SDR devices under the bit-error-rate (BER) metric. The results show that the proposed receiver does not change the receiver’s original architecture in practice while achieving good BER performance. The results also show that the proposed low-complexity CNN model can fasten running time, suitable for real-time AMC applications.

Оценка стабильности измерения разности фаз в пассивной бистатической системе ГНСС-радиолокации на базе программного приемника

The passive bistatic radar method using signals of global navigation satellite systems reflected from the Earth's surface can be used to determine and monitor various geophysical parameters of the reflecting surface. Most receiver architectures for this method are based on specialized hardware receivers, but software-defined radio (SDR) technology is rapidly evolving and allows real-time signal processing. This allows to develop a bistatic GNSS-reflectometry system on its basis. The article analyzes that the use of a software receiver will allow receiving and processing existing and future signals of all navigation satellite systems. Experiments with various parameters of different software receivers have been conducted, which have shown the stability of the phase difference between the receiving channels. It is shown that for some types of software receivers, a significant improvement in the measurement error of the phase difference is observed when synchronizing from an external highly stable reference generator.

Implementation of preamble based GFDM prototype for robust 5G systems

AbstractGeneralized frequency division multiplexing (GFDM) is a flexible block‐structured multi‐carrier scheme recently proposed for next‐generation wireless communication systems. There are various approaches suggested for its analysis and implementation via simulations but testing in real‐time environments is not heavily investigated. This paper carries out the real‐time implementation of the GFDM system utilizing software‐defined radio (SDR) by emphasizing mainly channel estimation and synchronization. Symbol timing, frequency offset, and channel estimate algorithms are applied using a windowed preamble with two identical halves to satisfy low egress noise requirements. Time and frequency estimation is evaluated in terms of residual offsets along with symbol error rate over frequency selective channels. This algorithm is extended to a preamble composed of multiple identical parts. This facilitates a large frequency estimation range at the cost of complexity. For practical validation of the above concepts, the National Instruments (NI) universal software radio peripheral (USRP) 2953R is employed as hardware and it is interfaced with LabVIEW.

Optimizing Multi-Tier Scheduling and Secure Routing in Edge-Assisted Software-Defined Wireless Sensor Network Environment Using Moving Target Defense and AI Techniques

Software Defined Wireless Sensor Networks (SDWSN) enable flexibility in Wireless Sensor Network (WSN) environments by defining the controllable functions to WSN nodes by the Software Defined Network (SDN) controller. Due to the rapid evolution of SDWSNs, adverse effects also have occurred in terms of interference, energy consumption, and security issues. Several state-of-the-art works lend their utmost best to the SDWSN environment. However, the complete picture (i.e., relatability and security in SDWSN) poses severe challenges. The state-of-the-art issues is addressed in this research by proposing interference-aware Multi-Tier Scheduling for the SDWSN environment (MTS-SDWSN). First, we perform network construction in which the proposed network is constructed in a 2D hexagonal grid structure to resolve the connectivity issue. Upon constructing the network, the SDWSN nodes are clustered and managed to reduce the energy consumption using the Divide Well To Merge Better (DWTMB) algorithm in which the optimal Cluster Leader (CL) is selected based on adequate constraint. The data from the clustered nodes are sent to the Local Base Station (LBS) via CL in which they are scheduled in multi-tier format to diminish the complexity and interference issues. The first tier involved in scheduling among Cluster Members (CMs) and CL using adequate metrics, whereas the successive tiers (i.e., second and third) involved in scheduling among CLs to LBSs and LBSs to Sink Node (SN) are done using the Non-Cooperative Fuzzy Theory (NCFT) method. Last, the scheduled nodes are routed to appropriate destinations using Secure and Optimal Routing Protocol (SORP). The proposed SORP includes the Alibaba and Forty Thieves (AFT) and Multi Criteria Decision Making (MCDM) algorithms for selecting and ranking the optimal routes. Further, the security of the routes is enabled by adopting trust and Moving Target Defense (MTD) mechanisms. The MTD includes route switching among the SDWSN devices and active switch handling using Cycle Generative Adversarial Networks (CGAN) among the switches. The proposed work is implemented using a NS-3.26 simulation tool, and performance of the proposed model and existing works shows that the proposed work outperforms the existing works.

Enhanced Cooperative Compressive Spectrum Sensing in Cognitive Radio Networks

ABSTRACTThe demand for bandwidth in cognitive radio networks (CRNs) is growing as applications become increasingly data intensive. Techniques such as compressed spectrum sensing (CSS) and cooperative spectrum sensing (C‐SS) are employed to address this challenge. C‐SS enhances overall detection accuracy and reliability by enabling multiple nodes to share and combine their local sensing data. Conversely, CSS effectively reduces the required information for spectrum usage decision making, thereby improving bandwidth utilization. Integrating these two methods allows CRNs to utilize the spectrum reliably and efficiently, leading to increased spectral efficiency. To further improve reconstruction performance, we leverage the sparsity concept to transcend hardware constraints and merge restrictions from both real and synthesized channels. This approach involves the virtual synthesis of channels, which linearly enhances the signal‐to‐noise ratio (SNR) within the network's size range. Simulation results demonstrate that our proposed method offers significant advantages over single‐node recovery, as validated by simulations and software defined radio (SDR) Implementation. The integration of spectral estimations from various local CR detectors enhances spatial diversity gain and sensing quality, particularly in fading channels. Compared to traditional approaches, our method achieves superior performance, evidenced by an increase in (from 93.97% to 96.52%) with almost the same .

ADAPTIVE COMPLEX FILTERS BASED TRANSMITTER IQ IMBALANCE REJECTION

This paper presents an efficient method for compensation of frequency-dependent (FD) transmitter In-phase Quadrature (IQ) imbalance. Proposed method compensates imbalance by exploiting indirect learning architecture (ILA) and complex filters whose coefficients are determined in an iterative process. Compensation performance is assessed after the method has been implemented in a Software Defined Radio (SDR) platform, capable of transmitting modulations at different central frequencies. Measured results demonstrate that the imbalance related images are reduced down to the noise floor. After applying the proposed IQ imbalance correction method, the transmitter image rejection ratio (IRR) is increased by 15dB in the case of an SDR transmitter operating at central frequency of 1.7 GHz. The ADC/DAC sampling rate is 61.44MS/s, while the signal bandwidth, for which the compensation is performed, is 30.72MHz. The advantage of the proposed method is low complexity in terms of a reduced number of coefficients. The method is generic and can be utilized for IQ imbalance compensation when wideband signals are transmitted.

A 2–36 GHz CMOS LNA with π-Network-Based wideband interstage matching technique for software-defined radio systems

With the advance in wireless communication, next-generation software-defined radio (SDR) systems require transceivers to operate in both sub-6GHz and millimeter-wave (mmWave) band and support multiple standards. However, bridging sub-6GHz frequencies with millimeter-wave bands exceeding 30 GHz remains a challenge for conventional wideband LNAs. To surmount this, a 2–36 GHz CMOS low-noise amplifier (LNA) designed for SDR systems is introduced in this paper. An innovative wideband input matching network capable of spanning both frequency domains is proposed. The methodology effectively mitigates the impact of vast parasitic capacitances, achieving wideband input matching against Electrostatic Discharge (ESD) and on-chip decoupling capacitor parasitic. In addition, a π-network-based wideband interstage matching technique is adopted to extend bandwidth of gain. A tri-stage prototype of the proposed LNA, designed using a 40-nm CMOS process, is designed to validate our design strategies. The post-simulation outcomes reveal a peak gain of 14 dB with a -3dB bandwidth ranging from 2 to 36 GHz, equating to a fractional bandwidth of 178 %. The Noise Figure (NF) is commendably uniform across the frequency spectrum, stabilizing at 5 dB. Furthermore, the third-order input intercept point (IIP3) is −4.2dBm to -3dBm across the bandwidth. The performance is achieved with a power of 19.4 mW and within a core area of 0.1 mm2.

Software-defined radio for monitoring the condition of infrastructure elements (continuation)

Software-defined radio for monitoring the condition of infrastructure elements (continuation)

Design an RF Up-Down Convertor using Software Defined Radio and GNU Radio

There is a need to design of RF Up/Down- converter for (from C/Ku to/from L band) signals required for several applications. The proposed work presents a design of an RF Up/Down Converter that makes use of GNU Radio and Software-Defined Radios (SDRs). The converter helps in frequency translation between the C/Ku and L bands, leading to a cost-effective and versatile solution for RF signal processing. By using open-source GNU Radio software, the proposed system enhances accessibility, enabling its deployment in diverse applications, from satellite communication to radar systems. The converter’s unique features include real-time processing capabilities, customization through an intuitive graphical interface, and Python scripting. This idea presents the design considerations, signal processing techniques, and performance evaluation of the RF Up/Down Converter. The advantages of an open-source solution over other available alternatives are in terms of cost, flexibility, and rapid prototyping. Simulation and hardware results demonstrate the efficacy of the proposed work.

Cognisseum: Cognitive radios on Colosseum facing adversaries

Cognitive radio technology brings a lot of interesting features which affect the transmission and reception properties of modern communication devices. Dynamic spectrum sensing, channel hopping and allocation, and software-based control are among the many. The new features allow strategic defense mechanisms while also enabling more capable adversarial attacks. In this work, we study coalitions of secondary users (SUs) against adversaries. In the presence of primary users (PUs), we inspect the behavior of SU pairs in cognitive radio networks, before and after adversarial attacks. We propose algorithms for forming coalitions among SU pairs. We consider two attack strategies for the adversaries: smart or naïve. We study how the channels are allocated if there is an attack and how the payoffs of those SU pairs vary with varying number of channels. We also show the effects of attack from the attackers’ point-of-view and how the attack strategy changes if the adversaries act smart vs. naïve. Using Colosseum, a large-scale wireless channel emulator, we construct a functional cognitive radio network and use its software-defined radio (SDR) hardware as SU and adversarial nodes. Using this setup, we run experiments and record data by running network performance measurement tool iPerf3 for various coalitional setups.

An Adaptive RF Front-End Architecture for Multi-Band SDR in Avionics.

This study introduces a reconfigurable and agile RF front-end (RFFE) architecture that significantly enhances the performance of software-defined radios (SDRs) by seamlessly adjusting to varying signal requirements, frequencies, and protocols. This flexibility greatly enhances spectrum utilization, signal integrity, and overall system efficiency-critical factors in aviation, where reliable communication, navigation, and surveillance systems are vital for safety. A versatile RF front-end is thus indispensable, enhancing connectivity and safety standards. We explore the integration of this flexible RF front-end in SDRs, focusing on the detailed design of essential components, such as receivers, transmitters, RF switches, combiners, and splitters, and their corresponding RF pathways. Comprehensive performance evaluations confirm the architecture's reliability and functionality, including an extensive analysis of receiver gain, linearity, and two-tone test results. These assessments validate the architecture's suitability for aviation radios and address considerations of size, weight, and power-cost (SWaP-C), demonstrating significant gains in operational efficiency and cost-effectiveness. The introduction of the new RF front-end on a single SDR board not only substantially reduces size and weight but also adds up to 18 dB gain to the received signal. It also allows for a high level of design flexibility, enabling seamless software transitions between different radios and the capacity to manage three times more radios with the same hardware, thereby significantly boosting the system's ability to handle multiple radio channels efficiently.

A deep learning GNSS spoofing and jamming detection method with dual-frequency C/N0 heatmap

Abstract The Global Navigation Satellite System (GNSS) is vulnerable to interference due to the open signal structure and low signal strength, posing a significant threat to the billions of terminals worldwide that rely on GNSS receivers for precise Positioning, Navigation, and Timing (PNT) services. In this paper, we propose a cloud-edge framwork for GNSS spoofing and jamming monitoring, comprising the data acquisition module, GNSS monitoring module, detecting and reporting module. In this framwork, we design a Deep Learning (DL) method for detecting GNSS interference through Dual-frequency Carrier-to-Noise density ratio (C/N0) heatmaps (DD-C/N0). This method involves extracting and correlating features from C/N0 heatmaps of visible navigation satellites operating in the GPS L1 and L2 frequency bands, allowing the identification of anomalous patterns. A U-BLOX receiver was utilized to capture the GNSS satellite signals, while commercial jammers and Software-Defined Radio (SDR) HackRF One kits were employed to simulate the interference sources. Experimental results demonstrate that the proposed method achieves significantly higher performance, with an accuracy of 99% and 98% on the public dataset and real-time testing data, compared to unsupervised, semi-supervised, and supervised detectors that rely solely on single-channel data (L1 frequency band). Integrated with the DD-C/N0 method, the online GNSS monitoring system will be improved and deployed to automate spoofing and jamming detection tasks in the next step.

LS-based multipath channel measurement method using software defined radio platform

Multipath channel measurement is the foundation of multipath channel modeling and analysis. Recently, the software defined radio (SDR) has provided new ideas for the design of multipath channel measurement systems due to universality and reconfigurability. Therefore, this paper introduces a multipath channel measurement method applicable to various SDR platforms. At first, to enhance the resolution of multipath measurements, a signal processing approach combining the least squares (LS) estimation algorithm within the SDR framework is proposed. Furthermore, to mitigate LS estimation errors stemming from high correlation among baseband signals, a scrambled measurement signal is introduced and its effectiveness is demonstrated through eigenvalue decomposition. Next, the systematic errors of In-phase and Quadrature(IQ) imbalance and bandwidth limitation are further analyzed and addressed within the SDR framework. Finally, the proposed measurement method is implemented based on a practical universal software radio peripheral (USRP) device and validated under simulated and real channels. The proposed measurement method mainly focuses on the baseband signal processing within the software component of SDR, making it applicable to most general USRP devices. The experiment results demonstrate that multipath channel measurement results with high accuracy can be obtained.