The Development of Modularized Post Processing GPS Software Receiving Platform using MATLAB Simulink

This work presents a Decode-&-Forward (D&F) protocol hardware implementation for downlink Multiple-Input Multiple-Output (MIMO) for Co-operative 5G network. Using a Software Defined Radio (SDR) platform, the Two-Hop D&F Co-operative 5G network has been implemented. The proposed co-operative system is composed of one emulated gNodeB, the proposed D&F relay node, and an emulated User Equipment (UE). The performance and feasibility of the development of the D&F relay node implemented using Matlab software has been measured on a test-bench in a real outdoor-to-indoor scenario. One of the main new features in this development is that the downlink 5G signal fulfils the New Radio (NR) 3GPP standard and was validated employing MS2090A-Anritsu LTE/5G spectrum analyzer. The obtained results support that the D&F protocol of the Co-operative 5G Network clearly improves the Bit Error Rate (BER) and Throughput in the 5G wireless communication between gNodeB and UE nodes. It has been demonstrated the viability and flexibility of the D&F Co-operative 5G Network based on SDR platform and Matlab software.

Software-defined radio (SDR) platforms represent a compelling solution for low-cost, flexible, dual-polarized radar systems. However, the phase coherency requirements of a dual-polarized radar system between the transmit ports and between the receive ports as well as between transmission and reception, are difficult to attain in popular SDRs. In this paper, we provide high-level overviews of SDR radar systems, dual-polarization radars, and system phase calibration procedures found in literature. The method adopted to achieve coherency involves a manual calibration procedure, which is applied to four dual-polarized radar system configurations designed around commercial off-the-shelf SDR platforms. The implemented, calibrated designs were exercised in a laboratory setting to determine the coherence performance of the SDR-based radar architectures in characterizing a fixed target’s full-polarization scattering matrix.

The Space Telecommunications Radio System (STRS) provides a common, consistent framework to abstract the application software from the radio platform hardware. STRS aims to reduce the cost and risk of using complex, configurable and reprogrammable radio systems across NASA missions. The Glenn Research Center (GRC) team made a software-defined radio (SDR) platform STRS compliant by adding an STRS operating environment and a field programmable gate array (FPGA) wrapper, capable of implementing each of the platforms interfaces, as well as a test waveform to exercise those interfaces. This effort serves to provide a framework toward waveform development on an STRS compliant platform to support future space communication systems for advanced exploration missions. Validated STRS compliant applications provided tested code with extensive documentation to potentially reduce risk, cost and efforts in development of space-deployable SDRs. This paper discusses the advantages of STRS, the integration of STRS onto a Reconfigurable, Intelligently-Adaptive, Communication System (RIACS) SDR platform, the sample waveform, and wrapper development efforts. The paper emphasizes the infusion of the STRS Architecture onto the RIACS platform for potential use in next generation SDRs for advance exploration missions.

This paper describes a new software-defined radio (SDR) platform targeted for rapid prototyping of small-cell systems. The SDR hardware combines the signal processing power of Xilinx ML605 Virtex-6 FPGA board with the Nutaq Radio420X frequency-agile transceiver and reconfigurable antennas to form a highly versatile platform for spectrum sensing, spectrum access, and cooperative communications. We evaluate the platform with two example applications: an offline OFDM physical processing flow based on WARPLab, and a real-time online automatic gain control mechanism. The results show that our SDR platform can reliably handle both offline and online processing demands with the added benefit of frequency agility offered by a state-of-the-art radio transceiver.

Proliferation and innovation of wireless technologies require significant amounts of radio spectrum. Recent policy reforms by the FCC are paving the way by freeing up spectrum for a new generation of frequency-agile wireless devices based on software defined radios (SDRs). But despite recent advances in SDR hardware, research on SDR MAC protocols or applications requires an experimental platform for managing physical access. We introduce Papyrus, a software platform for wireless researchers to develop and experiment dynamic spectrum systems using currently available SDR hardware. Papyrus provides two fundamental building blocks at the physical layer: flexible non-contiguous frequency access and simple and robust frequency detection. Papyrus allows researchers to deploy and experiment new MAC protocols and applications on USRP GNU Radio, and can also be ported to other SDR platforms. We demonstrate the use of Papyrus using Jello, a distributed MAC overlay for high-bandwidth media streaming applications and Ganache, a SDR layer for adaptable guardband configuration. Full implementations of Papyrus and Jello are publicly available.

Software-defined radio (SDR) is a new technology transitioning from research into commercial markets. SDR moves hardware-dominant baseband processing of multiple wireless communication protocols into software on a single chip. New cellular standards, such as HSPA+, LTE, and LTE+, require speeds in excess of 40 Mbps. SNOW 3G is a new stream cipher approved for use in these cellular protocols. Running SNOW 3G in software on our SDR platform provides a throughput of 19.1 Mbps per thread for confidentiality and 18.3 Mbps per thread for integrity. To have secure cellular communications in SDR platforms for these new protocols, the performance of security algorithms must be improved. This paper presents instruction set architecture (ISA) extensions and hardware designs for cellular confidentiality and integrity algorithms using SNOW 3G. Our ISA extensions and hardware designs are evaluated for the Sandbridge Sandblaster? 3011 (SB3011) SDR platform. With our new SNOW 3G instructions, the performance of confidentiality and integrity improve by 70 and 2%, respectively. For confidentiality, power consumption increased by 2%, while energy decreased by 40%. For integrity, power consumption remained consistent, while energy decreased by 2%.

This paper discusses the implementation of an automatic modulation classification system on a Software Defined Radio (SDR) platform, devoted to cognitive radio applications. The main objectives are to achieve an optimal realization in terms of the complexity of implementation, and flexibility which is a critical and essential factor in software radio, and to test a digital signal modulation mode identification technique, to distinguish between frequency modulation (2FSK and 4FSK) on the one hand and amplitude and phase modulations (ASK, BPSK, QPSK and 16QAM) on the other hand. The modulation schemes involved in this work are: BPSK, QPSK, QAM, ASK and FSK. The modulation identification algorithm uses the maximum value of the power spectral density of the normalized-centered instantaneous amplitude of the received signal as a metric. The test results for an AWGN channel validated the performance of the proposed architecture.

This paper presents Sora, a fully programmable software radio platform on commodity PC architectures. Sora combines the performance and fidelity of hardware software-defined radio (SDR) platforms with the programmability and flexibility of general-purpose processor (GPP) SDR platforms. Sora uses both hardware and software techniques to address the challenges of using PC architectures for high-speed SDR. The Sora hardware components consist of a radio front-end for reception and transmission, and a radio control board for high-throughput, low-latency data transfer between radio and host memories. Sora makes extensive use of features of contemporary processor architectures to accelerate wireless protocol processing and satisfy protocol timing requirements, including using dedicated CPU cores, large low-latency caches to store lookup tables, and SIMD processor extensions for highly efficient physical layer processing on GPPs. Using the Sora platform, we have developed a few demonstration wireless systems, including SoftWiFi, an 802.11a/b/g implementation that seamlessly interoperates with commercial 802.11 NICs at all modulation rates, and SoftLTE, a 3GPP LTE uplink PHY implementation that supports up to 43.8Mbps data rate.

This paper concerns design and performance testing of an HDL module called SwaMURAy that is a configurable, high-speed data sequencing and flow control module serving as an intermediary between data acquisition (or pre-processing) and subsequent processing stages. While a FIFO suffices for many applications our case needed a more elaborate solution to overcome legacy design limitations. The SwaMURAy is designed around a system where a block of sampled data is acquired at a fast rate and is then distributed among multiple processing cores to achieve a desired processing rate; this pattern of processing is sometimes needed in software defined radio (SDR) and radio astronomy applications. This solution was partly in response to legacy design restrictions of the SDR platform used, a difficulty likely experienced by many developers whereby new sampling peripherals are inhibited by legacy characteristics of the underlying reconfigurable platform. Our SDR platform has a planned lifetime of at least five years; a complete redesign and re-fabrication would be too costly. While the SwaMURAy overcame some performance problems, other problems arose. This paper overviews the SwaMURAy design, performance improvements achieved in a SDR case study, and remaining limitations and workarounds we expect will achieve further improvements.

We propose a low complexity synchronization method for the 3rd Generation Partnership Project (3GPP) long term evolution (LTE) mobile communication systems. A low complexity detection window, synchronization state machine, and two-stage detection are used to lower the computational complexity. The positions of the detection window and received samples are recorded, and the position and length of the detection window are controlled by the state machine. The positions are compared to decide if the received sample is useful for synchronization signal detection. Such techniques avoid unnecessary computations especially when implementing a receiver on a software defined radio (SDR) platform with general-purpose processors. We analyze the computational complexity of the proposed method and evaluate its performance based on simulations and using a Universal Software Radio Peripheral (USRP)-based SDR platform. The evaluation shows that the proposed method provides reliable and real-time synchronization signals on the considered SDR platform.

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.

In this paper an approach for implementation of a time of flight ranging methods on a software defined radio (SDR) platform is presented. The proposed approach is intended to be implemented in software running on a host computer without changing the existing hardware of the SDR platform. This approach can be easily extended for use in positioning methods. Using this approach a two way ranging (TWR) method is implemented on a SDR platform. All of the necessary processing is performed using software written in C/C++. This implementation was tested in the 2.4/5 GHz ISM band, with a channel bandwidth of 25 MHz. With this approach a nanosecond precision time of arrival estimation is achieved. This precision is needed in time of flight based ranging and positioning applications. A ranging accuracy better than 1 meter was obtained and demonstrated using the proposed approach. The developed TWR system performs 100 distance estimations per second. Nevertheless, with the processing power of the currently available general purpose processors a distance estimation rate of over 500 estimations per second can be achieved. The proposed approach can be also used in positioning scenarios, by performing TWR with multiple anchor nodes.

Software-defined radio (SDR) is widely used in wireless research because it allows communication algorithms to be rapidly developed, tested, and validated over the air (OTA) using flexible hardware and software platforms, enabling rapid prototyping across the physical (PHY) and medium access control (MAC) layers. As wireless environments become increasingly dynamic and adversarial, artificial intelligence (AI) and machine learning (ML) have emerged as promising tools to enhance adaptability and resilience in SDR-based systems, particularly in cognitive radio (CR) and wireless security. However, a gap remains in the literature: few surveys link AI/ML methods with their specific SDR implementations and provide insights into what works or does not work in practice. This survey addresses that gap by focusing on two broad domains: (i) CR, where we trace the evolution from classical SDR prototypes (energy/cyclostationary/eigenvalue sensing, spectrum mobility, MAC design) to AI-enabled approaches (shallow learning, deep networks, and reinforcement learning for access and handoff); and (ii) cybersecurity for SDR-enabled radios, where we synthesize jamming, spoofing, and eavesdropping studies from classical toolchains to AI/ML-based detection and mitigation. We compile representative SDR testbeds and toolkits, providing a structured taxonomy that emphasizes what AI/ML can alleviate (such as manual thresholding and moderate hardware drift) and what remains challenging (including wideband real-time scanning on commodity SDRs, resilience to correlated noise and impairments, as well as the burdens of dataset management and retraining). The outcome is a practical roadmap for AI in SDR, guiding researchers and practitioners from initial concepts to reproducible, hardware-supported experiments.

In this paper, a parallel frequency space search acquisition algorithm for a GPS (Global Positioning System) receiver is implemented using software defined radio (SDR) technology. The proposed algorithm is implemented and tested using National Instruments MyRio real time software processor platform. The results of the proposed algorithm are confirmed and compared with the parallel code phase search algorithm using different implementation platforms. The parallel frequency search implementation is highly recommended for real time and high speed seamless applications in product development and industry platforms where low cost, low complexity with reliable performance is of dire need. The novelty of this approach stands as no published literature has demonstrated parallel frequency search algorithm as an SDR platform using National Instruments Labview on MyRio real time processor environment. In this research, parallel frequency space acquisition of GPS signals on an NI myRio device is implemented. The parallel frequency acquisition is selected because of its moderate code acquisition complexity and its better resource management compared to parallel code phase algorithm, which is considered a large resource consumer.

In communication and signal processing course there are some challenges in explaining the basic theory of signal and how to process the signal as well. Educational tool to demonstrate how the system works is important and more attractive to improve the understanding of student. Software Defined Radio (SDR) brings the concept of software-based processing. This paper implements the using of SDR as the innovative teaching method to demonstrate the fundamental concept in signal processing course. Students build the audio signal processing projects on SDR platform using GNU Radio. Three interesting projects including the adjustment of sampling rate, DSB-AM modulation, and audio processing for gender identification are simulated using GNU Radio software. This Project Based Learning shows the positive result of the implementation of SDR in raising the student interest and motivation. Furthermore this study opens wide application of SDR based technique especially for education.