Academic literature on the topic 'Software defined radio/Software radio (SDR/SR)'

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Journal articles on the topic "Software defined radio/Software radio (SDR/SR)"

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Tato, Anxo. "Software Defined Radio: A Brief Introduction." Proceedings 2, no. 18 (September 19, 2018): 1196. http://dx.doi.org/10.3390/proceedings2181196.

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In this short article the concept of Software Defined Radio (SDR) is introduced and compared with the traditional radio. Then, a research project of atlanTTic center which used this technology was briefly presented and lastly, we include a reference to some dissemination activities related with SDR to be developed shortly.
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Sârbu, Annamaria, and Dumitru Neagoie. "Wi-Fi Jamming Using Software Defined Radio." International conference KNOWLEDGE-BASED ORGANIZATION 26, no. 3 (June 1, 2020): 162–66. http://dx.doi.org/10.2478/kbo-2020-0132.

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AbstractIn this article we present software defined radio (SDR) instrumentation used for interfering or jamming Wi-Fi networks. A Wi-Fi network analyzer application was used together with a low cost, commercially available SDR, Hack RF one, to conduct aimed interference on a 802.11 b/g/n network. A GNU radio flowchart was used to control the radio transceiver (SDR) by emitting a jamming signal aimed towards the targeted client by means of a directional antenna. Various signal bandwidths and distance from the targeted device were tested to characterize the adequate parameters of an effective jamming signal with respect to the calculated signal to noise ratio (SNR). Jamming efficiency was evaluated by means of a Wi-Fi connectivity speed test application installed on the targeted device, in order to measure connectivity degradation if complete jamming was not possible. Results presented suggest that Wi-Fi jamming is possible by means of SDR technology, providing insights on the methodology used and initial optimisation procedures in the test environment.
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Machado-Fernández, José Raúl. "Software Defined Radio: Basic Principles and Applications." REVISTA FACULTAD DE INGENIERÍA 24, no. 38 (December 28, 2014): 79. http://dx.doi.org/10.19053/01211129.3160.

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<p align="justify">The author makes a review of the SDR (Software Defined Radio) technology, including hardware schemes and application fields. A low performance device is presented and several tests are executed with it using free software. With the acquired experience, SDR employment opportunities are identified for low-cost solutions that can solve significant problems. In addition, a list of the most important frameworks related to the technology developed in the last years is offered, recommending the use of three of them.</p>
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Cwalina, Krzysztof, Piotr Rajchowski, and Jarosław Sadowski. "Wideband Radio Direction Finder Implemented in Software Defined Radio Technology." Applied Mechanics and Materials 817 (January 2016): 348–55. http://dx.doi.org/10.4028/www.scientific.net/amm.817.348.

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In the paper a wideband radio direction finder (RDF) implemented in software defined radio (SDR) technology and the results of hardware layer research, including developed antenna switching unit (ASU), are presented. The results of tests of the devices, which are the part of the software defined radio platform (SDRP), and antenna switching unit, confirmed the possibility of using selected components in the final solution.
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Estrela, Vania V. "Why Software-Defined Radio (SDR) Matters in Healthcare?" Medical Technologies Journal 3, no. 3 (November 11, 2019): 421–29. http://dx.doi.org/10.26415/2572-004x-vol3iss3p421-429.

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Sotyohadi, Sotyohadi, and Irrine Budi Sulistiawati. "DESAIN LOW NOISE TRANSCEIVER 7 MHZ BERBASIS SOFTWARE DEFINED RADIO (SDR)." Jurnal Mnemonic 2, no. 1 (December 14, 2019): 73–78. http://dx.doi.org/10.36040/mnemonic.v2i1.55.

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Software defined radio (SDR) adalah paradigma baru dalam desain perangkat komunikasi wireless. Teknologi SDR saat ini digunakan secara luas pada bidang telekomunikasi komersil seperti satelit komunikasi, telepon bergerak dan banyak digunakan pada kalangan komunitas radio amatir. SDR adalah suatu sistem radio dimana komponen-komponennya yang biasanya di bangun oleh perangkat keras (mixer, filter, modulator, demodulator dll) digantikan fungsinya oleh perangkat lunak. Software defined radio saat ini sangat dikenal dikalangan komunitas radio amatir di seluruh dunia. Berbagai desain transceiver berbasis SDR yang bekerja pada band high frequency (HF) telah banyak diaplikasikan, dan berbagai perangkat lunak aplikasi SDR telah dikembangkan. Perangkat transceiver berbasis SDR digemari oleh komunitas radio amatir dikarenakan rangkaian elektroniknya yang sederhana. Namun dari kelebihan tersebut muncul permasalahan yang sering dijumpai adalah noise pada penerima yang tinggi dan sensitivitas rendah. Dengan latar belakang permasalahan tersebut, maka pada penelitian ini dirancanglah suatu low noise transceiver 7 MHz berbasis software defined radio (SDR). Metode yang digunakan dalam mengurangi noise adalah dengan pemisahan grounding dari rangkaian digital, analog dan penguat RF serta pemilihan chip Tayloe detector yang memiliki nilai resistansi switch yang rendah yaitu 4 ohm. Berdasarkan hasil pengujian dengan menggunakan integrated circuit (IC) yang memiliki nilai resistansi switching yang rendah 4 ohm didapatkan kinerja transceiver yang lebih baik, dimana penerimaan lebih sensitive dan memiliki noise yang lebih rendah.
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Yang, Yun Long, You Rong Lu, Qian Cai, and Ying Yong Lai. "Design of Software Defined Radio Platform Resource Model Based on SCA." Applied Mechanics and Materials 347-350 (August 2013): 3934–39. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.3934.

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Software Defined Radio (SDR) platform resource model is the description and organization of the SDR platform resource. Its the foundation of the SDR platform resource management. Through these years, the Software Communication Architecture (SCA) has becoming the most famous specification for SDR, which standardizes the description for the SDR platform resource. Aiming at the shortages of the resource model in SCA, this paper discusses a SDR platform resource model, proposes a transfer port model and a connection model, designs a nested data model for the SDR platform resource, and a plane graph model which is easy to analyze and process.
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Teronpi, Khushboo, Kandarpa Kumar Sarma, Aradhana Misra, and Manasjyoti Bhuyan. "DTW based Modulation Detection- Verification using Software Defined Radio." WSEAS TRANSACTIONS ON COMMUNICATIONS 20 (August 10, 2021): 133–38. http://dx.doi.org/10.37394/23204.2021.20.18.

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Modulation detection is one of the major tasks of an intelligent receiver in a software defined radio (SDR). It is an intermediate step between signal detection and demodulation. In this paper we present the modulation detection based on Dynamic Time Warping (DTW) algorithm. Here the types of modulation that we use are QPSK, 8-PSK, 16-QAM and 64-QAM. The whole test and verification has been done with the help of SDR platform. After the test and trials of all the modulation schemes, it is observed that DTW provides a good efficiency with the accuracy of 93.75%.
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Tsoeunyane, Lekhobola, Simon Winberg, and Michael Inggs. "Software-Defined Radio FPGA Cores: Building towards a Domain-Specific Language." International Journal of Reconfigurable Computing 2017 (2017): 1–28. http://dx.doi.org/10.1155/2017/3925961.

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This paper reports on the design and implementation of an open-source library of parameterizable and reusable Hardware Description Language (HDL) Intellectual Property (IP) cores designed for the development of Software-Defined Radio (SDR) applications that are deployed on FPGA-based reconfigurable computing platforms. The library comprises a set of cores that were chosen, together with their parameters and interfacing schemas, based on recommendations from industry and academic SDR experts. The operation of the SDR cores is first validated and then benchmarked against two other cores libraries of a similar type to show that our cores do not take much more logic elements than existing cores and that they support a comparable maximum clock speed. Finally, we propose our design for a Domain-Specific Language (DSL) and supporting tool-flow, which we are in the process of building using our SDR library and the Delite DSL framework. We intend to take this DSL and supporting framework further to provide a rapid prototyping system for SDR application development to programmers not experienced in HDL coding. We conclude with a summary of the main characteristics of our SDR library and reflect on how our DSL tool-flow could assist other developers working in SDR field.
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da Silva, Fabrício A. B., David F. C. Moura, and Juraci F. Galdino. "Classes of Attacks for Tactical Software Defined Radios." International Journal of Embedded and Real-Time Communication Systems 3, no. 4 (October 2012): 57–82. http://dx.doi.org/10.4018/jertcs.2012100104.

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This survey presents a classification of attacks that Software Communications Architecture (SCA) compliant Software Defined Radios (SDR) can suffer. This paper also discusses how attack mitigation strategies can impact the development of a SCA-compliant software infrastructure and identifies several research directions related to SDR security. The SCA standard was originally proposed by the Joint Tactical Radio System program (JTRS), which is a program for the development of military tactical radios sponsored by the US Department of Defense. The classification presented in this paper is based on attack results on the radio set, which can also be associated with the adversary’s objectives when planning an intrusion. The identification of classes of attacks on a radio, along with the associated threats and vulnerabilities, is the first step in engineering a secure SDR system. It precedes the identification of security requirements and the development of security mechanisms. Therefore, the identification of classes of attacks is a necessary step for the definition of realistic and relevant security requirements.
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Dissertations / Theses on the topic "Software defined radio/Software radio (SDR/SR)"

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Sundquist, Thomas. "Waveform Development using Software Defined Radio." Thesis, Linköping University, Department of Science and Technology, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-6464.

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Software Defined Radio (SDR) is a conception of implementing radio functions in computer software, instead of having electronics performing the functions. This thesis aims to compare two different ways of implementing these functions, or waveforms.

The Software Communications Architecture (SCA) is an open standard developed by the United States Department of Defense. It uses a CORBA interface environment to make waveform applications interoperable and platform independent. This method of developing SDR is compared to an open-source initiative going by the name GNU Radio.

Two waveform applications are developed, one transmitter using SCA, and one receiver using GNU Radio. The analog radio interface is simulated using the sound cards of two regular PCs. The development is done using the C++ and Python programming languages.

This thesis examines pros and cons of the two SDR methods, as well as performing studies of Software Defined Radio in general.

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Leferman, Michael Joseph. "Rapid Prototyping Interface for Software Defined Radio Experimentation." Digital WPI, 2010. https://digitalcommons.wpi.edu/etd-theses/117.

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This thesis focuses on a user-friendly software-defined radio (SDR) development workflow for prototyping, research and education in wireless communications and networks. Specifically, a Simulink interface to the Universal Software Radio Peripheral 2(USRP2) SDR platform is devised in order to enable over-the-air data transmission and reception using a Simulink signal source and sink, in addition to controlling a subset of the hardware resources of the USRP2 platform. Using the USRP2 as the RF front end, this interface will use Simulink for software radio development and signal processing libraries of the digital baseband component of the communication transceiver design. This combination of hardware and software will enable the rapid design, implementation, and verification of digital communications systems in simulation, while allowing the user to easily test the system with near real time over-the-air transmission. The use of Simulink and MATLAB for communication transceiver development will provide streaming access to the USRP2 without the steep learning curve associated with current workflows. These widely available software packages and the USRP2 will make digital communication system prototyping both affordable yet highly versatile, enabling researchers and industry engineers to conduct studies into new wireless communications and networking architectures including cognitive radio. Furthermore, the interface will allow users to become familiar with tools used in industry while learning communications and networking concepts.
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Kohls, Nicholas Everett. "Software Defined Radio Short Range Radar." BYU ScholarsArchive, 2021. https://scholarsarchive.byu.edu/etd/9027.

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High cost is a current problem with modern radar systems. Software-defined radios (SDRs) offer a possible solution for low-cost customizable radar systems. An SDR is a radio communi- cation system where, instead of the traditional radio components implemented in hardware, many of the components are implemented in software on a computer or embedded system. Although SDRs were originally designed for wireless communication systems, the firmware of an SDR can be configured into a radar system. With new companies entering the market, various types of low- cost SDRs have emerged. This thesis explores the use of a LimeSDR-Mini in a short-range radar through open software tools and custom code. The LimeSDR-Mini is successfully shown to detect targets at a short range. However, due to the instability of the LimeSDR-Mini, the consistent detection of a target is not possible. This thesis shows how the LimeSDR is characterized and how timing synchronization and instability issues are mitigated. The LimeSDR-Mini falls short of operating reliable in a radar system and other SDR boards need to be explored as viable options. Test setups using coaxial cables and test setups using antennas in an outdoor environment show the instability of the LimeSDR-Mini. The transmitter and the receiver are asynchronous. The timing difference varies slightly from run to run, which results in issues that are exacerbated in a short-range radar. The bleed-through signal is the signal leakage from the transmitter to the receiver. The bleed-through signal prevents the detection of targets at a short-range. Feed-through nulling is a signal processing technique used to eliminate the bleed-through signal so that short- range targets can be detected. The instability of the LimeSDR-Mini reduces the effectiveness of feed-through nulling techniques.
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Humphris, Les. "Software Defined Radio for Maritime Collision Avoidance Applications." Thesis, University of Canterbury. Electrical and Electronic Engineering, 2015. http://hdl.handle.net/10092/11217.

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The design and development of a software defined radio (SDR) receiver prototype has been completed. The goal is to replace the existing automatic identification system (AIS) manufactured by Vesper Marine with a software driven system that reduces costs and provides a high degree of reconfigurability. One of the key concepts of the SDR is the consideration of directly digitizing the radio frequency (RF) signal using subsampling. This idea arises from the ambition to implement an analog-to-digital converter (ADC) as close to the antenna interface as practically possible. Thus, majority of the RF processing is encapsulated within in the digital domain. Evaluation of a frequency planning strategy that utilizes a combination of subsampling and oversampling will illustrate how the maritime bandwidth is aliased to a lower frequency. An analog front-end (AFE) board was constructed to implement the frequency planning strategy so that the digitized bandwidth can be streamed into a field programmable gate array (FPGA) for real-time processing. Research is shown on digital front-end (DFE) techniques that condition the digitized maritime signal for baseband processing. The process of a digital down converter (DDC) is conducted by an FPGA, which acquired the in-phase and quadrature signals. By implementing a digital signal processor (DSP) for baseband processing, demodulation on an AIS test signal is evaluated. The SDR prototype achieved a receiver sensitivity of -113dBm, outperforming the required sensitivity of -107dBm specified in the International Electrotechnical Commission (IEC) 62287-1 standard for AIS applications [1].
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Olivieri, Steven J. "Modular FPGA-Based Software Defined Radio for CubeSats." Digital WPI, 2011. https://digitalcommons.wpi.edu/etd-theses/375.

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Digital communications devices designed with application-specific integrated circuit (ASIC) technology suffer from one very significant limitation�the integrated circuits are not programmable. Therefore, deploying a new algorithm or an updated standard requires new hardware. Field-programmable gate arrays (FPGAs) solve this problem by introducing what is essentially reconfigurable hardware. Thus, digital communications devices designed on FPGAs are capable of accommodating multiple communications protocols without the need to deploy new hardware, and can support new protocols in a matter of seconds. In addition, FPGAs provide a means to update systems that are physical difficult to access. For these reasons, FPGAs provide us with an ideal platform for implementing adaptive communications algorithms. This thesis focuses on using FPGAs to implement an adaptive digital communications system. Using the Universal Software Radio Peripheral (USRP) as a base, this thesis aims to create a highly-adaptive, plug and play software-defined radio (SDR) that fits CubeSat form-factor satellites. Such a radio platform would enable CubeSat engineers to develop new satellites faster and with lower costs. This thesis presents a new system, the COSMIAC CubeSat SDR, that adapts the USRP platform to better suit the space and power limitations of a CubeSat.
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Gadgil, Kalyani Surendra. "Performance Benchmarking Software-Defined Radio Frameworks: GNURadio and CRTSv.2." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/97568.

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In this thesis, we benchmark the Cognitive Radios Test System version 2.0 (CRTSv.2) to analyze its software performance with respect to its internal structure and design choices. With the help of system monitoring and profiling tools, CRTSv.2 is tested to quantitatively evaluate its features and understand its shortcomings. With the help of GNU Radio, a popular, easy-to-use software radios framework, we ascertain that CRTSv.2 has a low memory footprint, fewer dependencies and overall, is a lightweight framework that can potentially be used for real-time signal processing. Several open-source measurement tools such as valgrind, perf, top, etc. are used to evaluate the CPU utilization, memory footprint and to postulate the origins of latencies. Based on our evaluation, we observe that CRTSv.2 shows a CPU utilization of approximately 9% whereas GNU Radio is 59%. CRTSv.2 has lower heap memory consumption of approximately 3MB to GNU Radio's 25MB. This study establishes a methodology to evaluate the performance of two SDR frameworks systematically and quantitatively.
Master of Science
When picking the best person for the job, we rely on the person's performance in past projects of a similar nature. The same can be said for software. Software radios provide the capability to perform signal processing functions in software, making them prime candidates towards solving modern problems such as spectrum scarcity, internet-of-things(IoT) adoption, vehicle-to-vehicle communication etc. In order to operate and configure software radios, software frameworks are provided that let the user make changes to the waveform, perform signal processing and data management. In this thesis, we consider two such frameworks,GNU Radio and CRTSv.2. A software performance evaluation is conducted to assess framework overheads contributing to operation of an orthogonal frequency-division multiplexing (OFDM) digital modulation scheme. This provides a quantitative analysis of a signals-specific use case which can be used by researchers to evaluate the optimal framework for research. This analysis can be generalized for different signal processing capabilities by understanding the total framework overhead removed from signal processing costs.
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Gu, Haohao, and He Zhang. "Implementation of CMMB System using Software Defined Radio (SDR) Platform." Thesis, Linköping University, Computer Engineering, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-57310.

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CMMB (China Multimedia Mobile Broadingcasting) is a wireless broadcastingchannel standard for low bandwidth, low cost hand-held digital TV is adopted byall continental Chinese government TV broadcasting companies and some HongKong private TV broadcasting companies. The business potential is high, yet thefuture is hard to predict because it might be replaced by GB200600 or DTMB. Thedigital modulation is based on OFDM with pilot supporting channel estimationand equalization and CP supporting multi-path induced ISI problems.This thesis investigates the implement a CMMB system using a SDR platform.Simulation chain was implemented using MATLAB with full data precision includingCMMB transmitter and receiver. The transmitter behavior model includes RSencoder, LDPC encoder, OFDM modulation, etc. The receiver behavior modelincludes OFDM demodulation, channel estimation, channel equalization, LDPCdecoder, RS decoder, etc. Different channel models emulating pathloss, whitenoise, multi-path, and glitch were modeled. Based on the simulation chain andchannel models, T-domain, F-domain channel estimator and equalizer were implemented,optimized. Optimized TD-FD models for different mobility scenarioswere proposed. The focus of the thesis is on 2D (FD-TD) channel estimation andequalization.

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Maheshwarappa, Mamatha R. "Software defined radio (SDR) architecture for concurrent multi-satellite communications." Thesis, University of Surrey, 2017. http://epubs.surrey.ac.uk/813388/.

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SDRs have emerged as a viable approach for space communications over the last decade by delivering low-cost hardware and flexible software solutions. The flexibility introduced by the SDR concept not only allows the realisation of concurrent multiple standards on one platform, but also promises to ease the implementation of one communication standard on differing SDR platforms by signal porting. This technology would facilitate implementing reconfigurable nodes for parallel satellite reception in Mobile/Deployable Ground Segments and Distributed Satellite Systems (DSS) for amateur radio/university satellite operations. This work outlines the recent advances in embedded technologies that can enable new communication architectures for concurrent multi-satellite or satellite-to-ground missions where multi-link challenges are associated. This research proposes a novel concept to run advanced parallelised SDR back-end technologies in a Commercial-Off-The-Shelf (COTS) embedded system that can support multi-signal processing for multi-satellite scenarios simultaneously. The initial SDR implementation could support only one receiver chain due to system saturation. However, the design was optimised to facilitate multiple signals within the limited resources available on an embedded system at any given time. This was achieved by providing a VHDL solution to the existing Python and C/C++ programming languages along with parallelisation so as to accelerate performance whilst maintaining the flexibility. The improvement in the performance was validated at every stage through profiling. Various cases of concurrent multiple signals with different standards such as frequency (with Doppler effect) and symbol rates were simulated in order to validate the novel architecture proposed in this research. Also, the architecture allows the system to be reconfigurable by providing the opportunity to change the communication standards in soft real-time. The chosen COTS solution provides a generic software methodology for both ground and space applications that will remain unaltered despite new evolutions in hardware, and supports concurrent multi-standard, multi-channel and multi-rate telemetry signals.
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Putthapipat, Pasd. "Lightweight Middleware for Software Defined Radio (SDR) Inter-Components Communication." FIU Digital Commons, 2013. http://digitalcommons.fiu.edu/etd/867.

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The ability to use Software Defined Radio (SDR) in the civilian mobile applications will make it possible for the next generation of mobile devices to handle multi-standard personal wireless devices and ubiquitous wireless devices. The original military standard created many beneficial characteristics for SDR, but resulted in a number of disadvantages as well. Many challenges in commercializing SDR are still the subject of interest in the software radio research community. Four main issues that have been already addressed are performance, size, weight, and power. This investigation presents an in-depth study of SDR inter-components communications in terms of total link delay related to the number of components and packet sizes in systems based on Software Communication Architecture (SCA). The study is based on the investigation of the controlled environment platform. Results suggest that the total link delay does not linearly increase with the number of components and the packet sizes. The closed form expression of the delay was modeled using a logistic function in terms of the number of components and packet sizes. The model performed well when the number of components was large. Based upon the mobility applications, energy consumption has become one of the most crucial limitations. SDR will not only provide flexibility of multi-protocol support, but this desirable feature will also bring a choice of mobile protocols. Having such a variety of choices available creates a problem in the selection of the most appropriate protocol to transmit. An investigation in a real-time algorithm to optimize energy efficiency was also performed. Communication energy models were used including switching estimation to develop a waveform selection algorithm. Simulations were performed to validate the concept.
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Scaperoth, David Alan. "Configurable SDR Operation for Cognitive Radio Applications using GNU Radio and the Universal Software Radio Peripheral." Thesis, Virginia Tech, 2007. http://hdl.handle.net/10919/32961.

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With interoperability issues plaguing emergency responders throughout the country, Cognitive Radio (CR) offers a unique solution to streamline communication between police, Emergency Medical Technicians (EMT), and military officers. Using Software Defined Radio (SDR) technology, a flexible radio platform can be potentially configured using a Cognitive Engine (CE) to transmit and receive many different incompatible radio standards. In this thesis, an interface between a Cognitive Engine and an SDR platform is described which modifies (i.e., configures) the radioâ s operation. The interface is based upon communicating information via eXtensible Markup Language (XML) data files that contain the radioâ s Physical (PHY) parameters. The XML data files have been designed such that more development can be made to its structure as this research develops. The GNU Radio and the Universal Software Radio Peripheral (USRP) serve as the SDR platform for an example implementation. The example implementation involves importing XML data files into the SDR for quick configuration. Three configuration examples are used to describe this process.
Master of Science
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Books on the topic "Software defined radio/Software radio (SDR/SR)"

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Stewart, Robert W., Kenneth W. Barlee, Dale S. W. Atkinson, and Louise H. Crockett. Software Defined Radio using MATLAB & Simulink and the RTL-SDR. Strathclyde Academic Media, 2015.

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The Hobbyist's Guide to the RTL-SDR: Really Cheap Software Defined Radio. CreateSpace Independent Publishing Platform, 2015.

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Donat, Wolfram. Explore Software Defined Radio: Use SDR to Receive Satellite Images and Space Signals. Pragmatic Programmers, LLC, The, 2020.

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Book chapters on the topic "Software defined radio/Software radio (SDR/SR)"

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Grayver, Eugene. "Why SDR?" In Implementing Software Defined Radio, 9–35. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-9332-8_3.

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Grayver, Eugene. "SDR Standardization." In Implementing Software Defined Radio, 97–129. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-9332-8_7.

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Grayver, Eugene. "Disadvantages of SDR." In Implementing Software Defined Radio, 37–41. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-9332-8_4.

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Grayver, Eugene. "Software-Centric SDR Platforms." In Implementing Software Defined Radio, 131–49. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-9332-8_8.

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Arnold, Steven. "The Software-Defined Radio (SDR)." In The Patrick Moore Practical Astronomy Series, 221–30. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54906-0_13.

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Grayver, Eugene. "State-of-the-Art SDR Components." In Implementing Software Defined Radio, 159–81. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-9332-8_10.

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Airoldi, Roberto, Fabio Garzia, Tapani Ahonen, and Jari Nurmi. "Ninesilica: A Homogeneous MPSoC Approach for SDR Platforms." In Computing Platforms for Software-Defined Radio, 107–19. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49679-5_6.

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Chun, Anthony, and Jeffrey D. Hoffman. "Application of the Scalable Communications Core as an SDR Baseband." In Computing Platforms for Software-Defined Radio, 123–45. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49679-5_7.

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Haziza, Nathalie, Mohamed Kassab, Raymond Knopp, Jérôme Härri, Florian Kaltenberger, Philippe Agostini, Marion Berbineau, et al. "Multi-technology Vehicular Cooperative System Based on Software Defined Radio (SDR)." In Lecture Notes in Computer Science, 84–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37974-1_7.

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Morgado, Alonso, Rocío del Río, and José M. de la Rosa. "A 1.2-V 90-nm CMOS Adaptive Concurrent Resonation-Based 2-2-2 Cascade ΣΔM for SDR." In Nanometer CMOS Sigma-Delta Modulators for Software Defined Radio, 201–46. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0037-0_6.

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Conference papers on the topic "Software defined radio/Software radio (SDR/SR)"

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Heidinger, Michael, Florian Hanebeck, Qihao Jin, Rainer Kling, and Wolfgang Heering. "IRFi-SDR: An IR software defined radio." In 2019 Global LIFI Congress (GLC). IEEE, 2019. http://dx.doi.org/10.1109/glc.2019.8864113.

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2

Nuñez Ortuño, Jose Maria, and Carlos Mascareñas Pérez-Iñigo. "SOFTWARE DEFINED RADIO (SDR) ON RADIOCOMMUNICATIONS TEACHING." In International Technology, Education and Development Conference. IATED, 2016. http://dx.doi.org/10.21125/inted.2016.1244.

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3

Bulychev, Roman V., Dmitry E. Goncharov, and Irina F. Babalova. "Obtaining IMSI by software-defined radio (RTL-SDR)." In 2018 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus). IEEE, 2018. http://dx.doi.org/10.1109/eiconrus.2018.8316859.

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4

Glossner, John. "Special session on software defined radio (SDR) and Cognitive Radio (CR)." In 2010 International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation (SAMOS X). IEEE, 2010. http://dx.doi.org/10.1109/icsamos.2010.5642053.

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5

Zhuang, Hui, Suiping Guo, Benkai Jia, and Ning Xu. "Research on the Software-Defined Radio (SDR)-Radiosonde Receiver." In Wireless Communications. Calgary,AB,Canada: ACTAPRESS, 2011. http://dx.doi.org/10.2316/p.2011.730-066.

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6

Saraswati, S. B., Manjunath G. Asuti, and Aumkarnath Mishra. "DSB-SC AM based software defined radio(SDR) design." In 2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT). IEEE, 2016. http://dx.doi.org/10.1109/rteict.2016.7808052.

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7

Rodriguez, Anton S., Michael C. Mensinger, In Soo Ahn, and Yufeng Lu. "Model-based software-defined radio(SDR) design using FPGA." In 2011 IEEE International Conference on Electro/Information Technology (EIT 2011). IEEE, 2011. http://dx.doi.org/10.1109/eit.2011.5978602.

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8

Krishnan, Rahul, R. Ganesh Babu, S. Kaviya, N. Pragadeesh Kumar, C. Rahul, and S. Santhana Raman. "Software defined radio (SDR) foundations, technology tradeoffs: A survey." In 2017 IEEE International Conference on Power, Control, Signals and Instrumentation Engineering (ICPCSI). IEEE, 2017. http://dx.doi.org/10.1109/icpcsi.2017.8392204.

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9

Velasco, Cesar, and Christian Tipantuna. "Meteorological picture reception system using software defined radio (SDR)." In 2017 IEEE Second Ecuador Technical Chapters Meeting (ETCM). IEEE, 2017. http://dx.doi.org/10.1109/etcm.2017.8247551.

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10

Zhao, Youping, Jeffrey H. Reed, Shiwen Mao, and Kyung K. Bae. "Overhead Analysis for Radio Environment Mapenabled Cognitive Radio Networks." In 2006 1st IEEE Workshop on Networking Technologies for Software Defined Radio Networks. IEEE, 2006. http://dx.doi.org/10.1109/sdr.2006.4286322.

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