Software-defined networking (SDN) technology is an approach to network management that enables dynamic, programmatically efficient network configuration in order to improve network performance and monitoring making it more like cloud computing than traditional network management.[1] SDN is meant to address the fact that the static architecture of traditional networks is decentralized and complex while current networks require more flexibility and easy troubleshooting. SDN attempts to centralize network intelligence in one network component by disassociating the forwarding process of network packets (data plane) from the routing process (control plane). The control plane consists of one or more controllers which are considered as the brain of SDN network where the whole intelligence is incorporated. However, the intelligence centralization has its own drawbacks when it comes to security,[1] scalability and elasticity[1] and this is the main issue of SDN.
Software Defined Radio - Defined: A number of definitions can be found to describe Software Defined Radio, also known as Software Radio or SDR. The SDR Forum, working in collaboration with the Institute of Electrical and Electronic Engineers (IEEE) P1900.1 group, has worked to establish a definition of SDR. Software defined radios, radio whose channel modulation waveforms are defined in software is a curation of 70 resources about, Softrock SDR and Six Meters, CW Skimmer Softrock-based SDR Array, OH2NLT Experimental Digital HF Receiver, YU1LM SDR Radio, SoftRock SDR Interest Group. Resources listed under Software defined radio category belongs to Technical Reference main collection, and get.
Software Defined Radio attempts to place much or most of the complex signal handling involved in communications receivers and transmitters into the digital (DSP) style. In its purest form, and SDR receiver might consist simply of an analog-to-digital convert chip connected to an antenna. Software defined radio is a type of RF system that utilizes software to perform tasks traditionally performed by hardware, such as generating or decoding baseband signals. This allows for more freedom in RF communication systems: Changing what your radio does becomes a matter of editing code instead of modifying hardware. The definition of SDR - per the Wireless Innovation Forum (formerly the SDR Forum) - is 'a radio in which some or all of the physical-layer functions are software-defined.' The term is really focused on the physical (PHY) layer processing of the waveform, and not related to the radio-frequency (RF) front end, which is a common misconception.
SDN was commonly associated with the OpenFlow protocol (for remote communication with network plane elements for the purpose of determining the path of network packets across network switches) since the latter's emergence in 2011. However, since 2012[2][3] OpenFlow for many companies is no longer an exclusive solution, they added proprietary techniques. These include Cisco Systems' Open Network Environment and Nicira's network virtualization platform.
SD-WAN applies similar technology to a wide area network (WAN).[4]
- 7Applications
History[edit]
The history of SDN principles can be traced back to the separation of the control and data plane first used in the public switched telephone network as a way to simplify provisioning and management well before this architecture began to be used in data networks.
The Internet Engineering Task Force (IETF) began considering various ways to decouple the control and forwarding functions in a proposed interface standard published in 2004 appropriately named 'Forwarding and Control Element Separation' (ForCES).[5] The ForCES Working Group also proposed a companion SoftRouter Architecture.[6] Additional early standards from the IETF that pursued separating control from data include the Linux Netlink as an IP Services Protocol[7] and A Path Computation Element (PCE)-Based Architecture.[8]
These early attempts failed to gain traction for two reasons. One is that many in the Internet community viewed separating control from data to be risky, especially owing to the potential for a failure in the control plane. The second is that vendors were concerned that creating standard application programming interfaces (APIs) between the control and data planes would result in increased competition.
The use of open source software in split control/data plane architectures traces its roots to the Ethane project at Stanford's computer sciences department. Ethane's simple switch design led to the creation of OpenFlow.[9] An API for OpenFlow was first created in 2008.[10] That same year witnessed the creation of NOX—an operating system for networks.[11]
Work on OpenFlow continued at Stanford, including with the creation of testbeds to evaluate use of the protocol in a single campus network, as well as across the WAN as a backbone for connecting multiple campuses.[12] In academic settings there were a few research and production networks based on OpenFlow switches from NEC and Hewlett-Packard; as well as based on Quanta Computer whiteboxes, starting from about 2009.[13]
Beyond academia, the first deployments were by Nicira in 2010 to control OVS from Onix, co-developed with NTT and Google. A notable deployment was Google's B4 deployment in 2012.[14][15] Later Google acknowledged their first OpenFlow with Onix deployments in their Datacenters at the same time.[16] Another known large deployment is at China Mobile.[17]
![Software defined radio definition dictionary Software defined radio definition dictionary](/uploads/1/2/5/0/125007006/523623222.jpg)
The Open Networking Foundation was founded in 2011 to promote SDN and OpenFlow.
At the 2014 Interop and Tech Field Day, software-defined networking was demonstrated by Avaya using shortest path bridging (IEEE 802.1aq) and OpenStack as an automated campus, extending automation from the data center to the end device, removing manual provisioning from service delivery.[18][19]
Concept[edit]
SDN architectures decouple network control and forwarding functions, enabling network control to become directly programmable and the underlying infrastructure to be abstracted from applications and network services.[20]
The OpenFlow protocol can be used in SDN technologies. The SDN architecture is:
- Directly programmable: Network control is directly programmable because it is decoupled from forwarding functions.
- Agile: Abstracting control from forwarding lets administrators dynamically adjust network-wide traffic flow to meet changing needs.
- Centrally managed: Network intelligence is (logically) centralized in software-based SDN controllers that maintain a global view of the network, which appears to applications and policy engines as a single, logical switch.
- Programmatically configured: SDN lets network managers configure, manage, secure, and optimize network resources very quickly via dynamic, automated SDN programs, which they can write themselves because the programs do not depend on proprietary software.
- Open standards-based and vendor-neutral: When implemented through open standards, SDN simplifies network design and operation because instructions are provided by SDN controllers instead of multiple, vendor-specific devices and protocols.
The need for a new network architecture[edit]
The explosion of mobile devices and content, server virtualization, and advent of cloud services are among the trends driving the networking industry to re-examine traditional network architectures.[21] Many conventional networks are hierarchical, built with tiers of Ethernet switches arranged in a tree structure. This design made sense when client-server computing was dominant, but such a static architecture is ill-suited to the dynamic computing and storage needs of today's enterprise data centers, campuses, and carrier environments.[22] Some of the key computing trends driving the need for a new network paradigm include: Game ban ca an tien.
- Changing traffic patterns
- Within the enterprise data center, traffic patterns have changed significantly. In contrast to client-server applications where the bulk of the communication occurs between one client and one server, today's applications access different databases and servers, creating a flurry of 'east-west' machine-to-machine traffic before returning data to the end user device in the classic 'north-south' traffic pattern. At the same time, users are changing network traffic patterns as they push for access to corporate content and applications from any type of device (including their own), connecting from anywhere, at any time. Finally, many enterprise data centers managers are contemplating a utility computing model, which might include a private cloud, public cloud, or some mix of both, resulting in additional traffic across the wide area network.
- The 'consumerization of IT'
- Users are increasingly employing mobile personal devices such as smartphones, tablets, and notebooks to access the corporate network. IT is under pressure to accommodate these personal devices in a fine-grained manner while protecting corporate data and intellectual property and meeting compliance mandates.
- The rise of cloud services
- Enterprises have enthusiastically embraced both public and private cloud services, resulting in unprecedented growth of these services. Enterprise business units now want the agility to access applications, infrastructure, and other IT resources on demand and à la carte. To add to the complexity, IT's planning for cloud services must be done in an environment of increased security, compliance, and auditing requirements, along with business reorganizations, consolidations, and mergers that can change assumptions overnight. Providing self-service provisioning, whether in a private or public cloud, requires elastic scaling of computing, storage, and network resources, ideally from a common viewpoint and with a common suite of tools.
- 'Big data' means more bandwidth
- Handling today's 'big data' or mega datasets requires massive parallel processing on thousands of servers, all of which need direct connections to each other. The rise of mega datasets is fueling a constant demand for additional network capacity in the data center. Operators of hyperscale data center networks face the daunting task of scaling the network to previously unimaginable size, maintaining any-to-any connectivity without going broke.[23]
Architectural components[edit]
A high-level overview of the software-defined networking architecture
The following list defines and explains the architectural components:[24]
- SDN Application
- SDN Applications are programs that explicitly, directly, and programmatically communicate their network requirements and desired network behavior to the SDN Controller via a northbound interface (NBI). In addition they may consume an abstracted view of the network for their internal decision-making purposes. An SDN Application consists of one SDN Application Logic and one or more NBI Drivers. SDN Applications may themselves expose another layer of abstracted network control, thus offering one or more higher-level NBIs through respective NBI agents.
- SDN Controller
- The SDN Controller is a logically centralized entity in charge of (i) translating the requirements from the SDN Application layer down to the SDN Datapaths and (ii) providing the SDN Applications with an abstract view of the network (which may include statistics and events). An SDN Controller consists of one or more NBI Agents, the SDN Control Logic, and the Control to. Security and Communication Networks. 9 (18): 5803–5833. doi:10.1002/sec.1737.
- ^'Software-defined networking is not OpenFlow, companies proclaim'. searchsdn.techtarget.com.
- ^'InCNTRE's OpenFlow SDN testing lab works toward certified SDN product'.
- ^'Predicting SD-WAN Adoption'. gartner.com. 2015-12-15. Retrieved 2016-06-27.
- ^L. Yang (Intel Corp.), R. Dantu (Univ. of North Texas), T. Anderson (Intel Corp.) & R. Gopal (Nokia.) (April 2004). 'Forwarding and Control Element Separation (ForCES) Framework'.CS1 maint: multiple names: authors list (link)
- ^T. V. Lakshman, T. Nandagopal, R. Ramjee, K. Sabnani, and T. Woo (Nov 2004). 'The SoftRouter Architecture'(PDF).CS1 maint: multiple names: authors list (link)
- ^J. Salim (Znyx Networks), H. Khosravi (Intel), A. Kleen (Suse), and A. Kuznetsov (INR/Swsoft) (July 2003). 'Linux Netlink as an IP Services Protocol'.CS1 maint: multiple names: authors list (link)
- ^A. Farrel (Old Dog Consulting), J. Vasseur (Cisco Systems, Inc.), and J. Ash (AT&T) (August 2006). 'A Path Computation Element (PCE)-Based Architecture'.CS1 maint: multiple names: authors list (link)
- ^Martìn Casado, Michael J. Freedman, Justin Pettit, Jianying Luo, and Nick McKeown (Stanford University) (August 2007). 'Ethane: Taking Control of the Enterprise'(PDF).CS1 maint: multiple names: authors list (link)
- ^N. McKeown, T. Anderson, H. Balakrishnan, G. Parulkar, L. Peterson, J. Rexford, S. Shenker, and J. Turner. (April 2008). 'OpenFlow: Enabling Innovation in Campus Networks'(PDF).CS1 maint: multiple names: authors list (link)
- ^N. Gude, T. Koponen, J. Pettit, B. Pfaff, M. Casado, N. McKeown, and S. Shenker. (July 2008). 'NOX: Towards an Operating System for Networks'(PDF).CS1 maint: multiple names: authors list (link)
- ^'GENI. Campus OpenFlow topology'. 2011.
- ^Kuang-Ching “KC” Wang (Oct 3, 2011). 'Software Defined Networking and OpenFlow for Universities: Motivation, Strategy, and Uses'(PDF).
- ^Sushant Jain, Alok Kumar, Subhasree Mandal, Joon Ong, Leon Poutievski, Arjun Singh, Subbaiah Venkata, Jim Wanderer, Junlan Zhou, Min Zhu, Jonathan Zolla, Urs Hölzle, Stephen Stuart and Amin Vahdat (Google) (August 12–16, 2013). 'B4: Experience with a Globally-Deployed Software Defined WAN'(PDF).CS1 maint: multiple names: authors list (link)
- ^brent salisbury (May 14, 2013). 'Inside Google's Software-Defined Network'.
- ^Arjun Singh, Joon Ong, Amit Agarwal, Glen Anderson, Ashby Armistead, Roy Bannon, Seb Boving, Gaurav Desai, Bob Felderman, Paulie Germano, Anand Kanagala, Jeff Provost, Jason Simmons, Eiichi Tanda, Jim Wanderer, Urs Hölzle, Stephen Stuart, Amin Vahdat (2015). 'Jupiter Rising: A Decade of Clos Topologies and Centralized Control in Google's Datacenter Network'.CS1 maint: multiple names: authors list (link)
- ^''MPLS-TP OpenFlow Protocol Extensions for SPTN' becomes a formal ONF standard by unanimous approval'. June 27, 2017.
- ^Camille Campbell (February 6, 2014). 'Avaya Debuts Networking Innovations at 'Tech Field Day''.
- ^Elizabeth Miller Coyne (September 23, 2016). 'Huawei Exec: SDN's Become a 'Completely Meaningless Term''.
- ^'Software-Defined Networking (SDN) Definition'. Opennetworking.org. Retrieved 26 October 2014.
- ^'White Papers'. Opennetworking.org. Retrieved 26 October 2014.
- ^Montazerolghaem, Ahmadreza.; Yaghmaee, M. H.; Leon-Garcia, A. (2017). 'OpenSIP: Toward Software-Defined SIP Networking'. IEEE Transactions on Network and Service Management. PP (99): 184–199. arXiv:1709.01320. Bibcode:2017arXiv170901320M. doi:10.1109/tnsm.2017.2741258. ISSN1932-4537.
- ^Vicentini, Cleverton; Santin, Altair; Viegas, Eduardo; Abreu, Vilmar (January 2019). 'SDN-based and multitenant-aware resource provisioning mechanism for cloud-based big data streaming'. Journal of Network and Computer Applications. 126: 133–149. doi:10.1016/j.jnca.2018.11.005.
- ^'SDN Architecture Overview'(PDF). Opennetworking.org. Retrieved 22 November 2014.
- ^S.H. Yeganeh, Y. Ganjali, 'Kandoo: A Framework for Efficient and Scalable Offloading of Control Applications,' proceedings of HotSDN, Helsinki, Finland, 2012.
- ^R. Ahmed, R. Boutaba, 'Design considerations for managing wide area software defined networks,' Communications Magazine, IEEE, vol. 52, no. 7, pp. 116–123, July 2014.
- ^T. Koponen et al, 'Onix: A Distributed Control Platform for Large scale Production Networks,' proceedings USENIX, ser. OSDI’10, Vancouver, Canada, 2010.
- ^D. Tuncer, M. Charalambides, S. Clayman, G. Pavlou, 'Adaptive Resource Management and Control in Software Defined Networks,' Network and Service Management, IEEE Transactions on, vol. 12, no. 1, pp. 18–33, March 2015.
- ^B. Heller, R. Sherwood, and N. McKeown, 'The Controller Placement Problem,' proceedings of HotSDN’12, 2012.
- ^Y.N. Hu, W.D. Wang, X.Y. Gong, X.R. Que, S.D. Cheng, 'On the placement of controllers in software-defined networks,' Journal of China Universities of Posts and Telecommunications, vol. 19, Supplement 2, no. 0, pp. 92 – 171, 2012.
- ^F.J. Ros, P.M. Ruiz, 'Five nines of southbound reliability in software defined networks,' proceedings of HotSDN’14, 2014.
- ^D. Tuncer, M. Charalambides, S. Clayman, G. Pavlou, 'On the Placement of Management and Control Functionality in Software Defined Networks,' proceedings of 2nd IEEE International Workshop on Management of SDN and NFV Systems (ManSDN/NFV), Barcelona, Spain, November 2015.
- ^'OpenFlow: Proactive vs Reactive'. NetworkStatic.net. 2013-01-15. Retrieved 2014-07-01.
- ^'Reactive, Proactive, Predictive: SDN Models | F5 DevCentral'. Devcentral.f5.com. 2012-10-11. Retrieved 2016-06-30.
- ^Pentikousis, Kostas; Wang, Yan; Hu, Weihua (2013). 'Mobileflow: Toward software-defined mobile networks'. IEEE Communications Magazine. 51 (7): 44–53. doi:10.1109/MCOM.2013.6553677.
- ^Liyanage, Madhusanka (2015). Software Defined Mobile Networks (SDMN): Beyond LTE Network Architecture. UK: John Wiley. pp. 1–438. ISBN978-1-118-90028-4.
- ^Jose Costa-Requena, Jesús Llorente Santos, Vicent Ferrer Guasch, Kimmo Ahokas, Gopika Premsankar, Sakari Luukkainen, Ijaz Ahmed, Madhusanka Liyanage, Mika Ylianttila, Oscar López Pérez, Mikel Uriarte Itzazelaia, Edgardo Montes de Oca, SDN and NFV Integration in Generalized Mobile Network Architecture , in Proc. of European Conference on Networks and Communications (EUCNC), Paris, France. June 2015.
- ^Madhusanka Liyanage, Mika Ylianttila, Andrei Gurtov, Securing the Control Channel of Software-Defined Mobile Networks , in Proc. of IEEE 15th International Symposium on World of Wireless, Mobile and Multimedia Networks (WoWMoM), Sydney, Australia. June 2014.
- ^Haranas, Mark (8 October 2016). '16 Hot Networking Products Putting The Sizzle In SD-WAN'. CRN. Retrieved 1 November 2016.
- ^'SD-WAN: What it is and why you'll use it one day'. networkworld.com. 2016-02-10. Retrieved 2016-06-27.
- ^Serries, William (12 September 2016). 'SD-LAN et SD-WAN : Deux Approches Différentes pour le Software Defined Networking'. ZDNet. Retrieved 1 November 2016.
- ^Kerravala, Zeus (13 September 2016). 'Aerohive Introduces the Software-defined LAN'. Network World. Retrieved 1 November 2016.
- ^Kreutz, Diego; Ramos, Fernando; Verissimo, Paulo (2013). 'Towards secure and dependable software-defined networks'. Proceedings of the second ACM SIGCOMM workshop on Hot topics in software defined networking. pp. 50–60.
- ^Scott-Hayward, Sandra; O'Callaghan, Gemma; Sezer, Sakir (2013). 'SDN security: A survey'. Future Networks and Services (SDN4FNS), 2013 IEEE SDN for. pp. 1–7.
- ^Benton, Kevin; Camp, L Jean; Small, Chris (2013). 'Openflow vulnerability assessment'. Proceedings of the second ACM SIGCOMM workshop on Hot topics in software defined networking. pp. 151–152.
- ^Abdou, AbdelRahman; van Oorschot, Paul; Wan, Tao (May 2018). 'A Framework and Comparative Analysis of Control Plane Security of SDN and Conventional Networks'. IEEE Communications Surveys and Tutorials. to appear. arXiv:1703.06992. Bibcode:2017arXiv170306992A.
- ^Giotis, K; Argyropoulos, Christos; Androulidakis, Georgios; Kalogeras, Dimitrios; Maglaris, Vasilis (2014). 'Combining OpenFlow and sFlow for an effective and scalable anomaly detection and mitigation mechanism on SDN environments'. Computer Networks. 62: 122–136. doi:10.1016/j.bjp.2013.10.014.
- ^Braga, Rodrigo; Mota, Edjard; Passito, Alexandre (2010). 'Lightweight DDoS flooding attack detection using NOX/OpenFlow'. Local Computer Networks (LCN), 2010 IEEE 35th Conference on. pp. 408–415.
- ^Feamster, Nick (2010). 'Outsourcing home network security'. Proceedings of the 2010 ACM SIGCOMM workshop on Home networks. pp. 37–42.
- ^Jin, Ruofan & Wang, Bing (2013). 'Malware detection for mobile devices using software-defined networking'. Research and Educational Experiment Workshop (GREE), 2013 Second GENI. 81-88.
- ^Jafarian, Jafar Haadi; Al-Shaer, Ehab; Duan, Qi (2012). 'Openflow random host mutation: transparent moving target defense using software defined networking'. Proceedings of the first workshop on Hot topics in software defined networks. pp. 127–132.
- ^Kampanakis, Panos; Perros, Harry; Beyene, Tsegereda. SDN-based solutions for Moving Target Defense network protection(PDF). Retrieved 23 July 2014.
- ^ abSherwood, Rob; Gibb, Glen; Yap, Kok-Kiong; Appenzeller, Guido; Casado, Martin; McKeown, Nick; Parulkar, Guru (2009). 'Flowvisor: A network virtualization layer'. OpenFlow Switch Consortium, Tech. Rep.
- ^Al-Shaer, Ehab & Al-Haj, Saeed (2010). 'FlowChecker: Configuration analysis and verification of federated OpenFlow infrastructures'. Proceedings of the 3rd ACM workshop on Assurable and usable security configuration. pp. 37–44.
- ^Canini, Marco; Venzano, Daniele; Peresini, Peter; Kostic, Dejan; Rexford, Jennifer; et al. (2012). A NICE Way to Test OpenFlow Applications. NSDI. pp. 127–140.
- ^Bernardo and Chua (2015). Introduction and Analysis of SDN and NFV Security Architecture (SA-SECA). 29th IEEE AINA 2015. pp. 796–801.
- ^B. Pfaf; et al. (February 28, 2011). 'OpenFlow Switch Specification'(PDF). Retrieved July 8, 2017.
- ^T. Zhu; et al. (October 18, 2016). 'MCTCP: Congestion-aware and robust multicast TCP in Software-Defined networks'. 2016 IEEE/ACM 24th International Symposium on Quality of Service (IWQoS). IEEE. pp. 1–10. doi:10.1109/IWQoS.2016.7590433. ISBN978-1-5090-2634-0. Retrieved July 3, 2017.
- ^M. Noormohammadpour; et al. (July 10, 2017). 'DCCast: Efficient Point to Multipoint Transfers Across Datacenters'. USENIX. Retrieved July 3, 2017.
- ^M. Noormohammadpour; et al. (2018). QuickCast: Fast and Efficient Inter-Datacenter Transfers using Forwarding Tree Cohorts. arXiv:1801.00837. Bibcode:2018arXiv180100837N. doi:10.31219/osf.io/uzr24. Retrieved January 23, 2018.
- ^ abWilliam, Stalling (2016). 'Foundations of Modern Networking: SDN, NFV, QoE, IoT, and Cloud'. Pearson Education.
- ^Rowayda, A. Sadek (May 2018). 'An Agile Internet of Things (IoT) based Software Defined Network (SDN) Architecture'. Egyptian Computer Science Journal. 42 (2): 13–29.
- ^Platform to Multivendor Virtual and Physical Infrastructure
- ^Graham, Finnie (December 2012). 'The Role Of DPI In An SDN World'. White Paper.
- ^Series, Y. (May 2015). 'Global Information Infrastructure, Internet Protocol Aspects And NextGeneration Networks'. ITU-T Y.2770 Series, Supplement on DPI Use Cases and Application Scenarios.
Retrieved from 'https://en.wikipedia.org/w/index.php?title=Software-defined_networking&oldid=915356785'
Multiplexing |
---|
Analog modulation |
Related topics |
Analog modulation |
---|
Digital modulation |
Hierarchical modulation |
Spread spectrum |
See also |
Software-defined radio (SDR) is a radiocommunication system where components that have been traditionally implemented in hardware (e.g. mixers, filters, amplifiers, modulators/demodulators, detectors, etc.) are instead implemented by means of software on a personal computer or embedded system.[1] While the concept of SDR is not new, the rapidly evolving capabilities of digital electronics render practical many processes which were once only theoretically possible.
A basic SDR system may consist of a personal computer equipped with a sound card, or other analog-to-digital converter, preceded by some form of RF front end. Significant amounts of signal processing are handed over to the general-purpose processor, rather than being done in special-purpose hardware (electronic circuits). Such a design produces a radio which can receive and transmit widely different radio protocols (sometimes referred to as waveforms) based solely on the software used.
Software radios have significant utility for the military and cell phone services, both of which must serve a wide variety of changing radio protocols in real time.
In the long term, software-defined radios are expected by proponents like the SDRForum (now The Wireless Innovation Forum) to become the dominant technology in radio communications. SDRs, along with software defined antennas are the enablers of the cognitive radio.
A software-defined radio can be flexible enough to avoid the 'limited spectrum' assumptions of designers of previous kinds of radios, in one or more ways including:[2]
- Spread spectrum and ultrawideband techniques allow several transmitters to transmit in the same place on the same frequency with very little interference, typically combined with one or more error detection and correction techniques to fix all the errors caused by that interference.
- Software defined antennas adaptively 'lock onto' a directional signal, so that receivers can better reject interference from other directions, allowing it to detect fainter transmissions.
- Cognitive radio techniques: each radio measures the spectrum in use and communicates that information to other cooperating radios, so that transmitters can avoid mutual interference by selecting unused frequencies. Alternatively, each radio connects to a geolocation database to obtain information about the spectrum occupancy in its location and, flexibly, adjusts its operating frequency and/or transmit power not to cause interference to other wireless services.
- Dynamic transmitter power adjustment, based on information communicated from the receivers, lowering transmit power to the minimum necessary, reducing the near-far problem and reducing interference to others, and extending battery life in portable equipment.
- Wireless mesh network where every added radio increases total capacity and reduces the power required at any one node.[3] Each node transmits using only enough power needed for the message to hop to the nearest node in that direction, reducing the near-far problem and reducing interference to others.
- 1Operating principles
- 2History
- 3Current usage
- 3.1Military
Operating principles[edit]
Software defined radio concept
Ideal concept[edit]
The ideal receiver scheme would be to attach an analog-to-digital converter to an antenna. A digital signal processor would read the converter, and then its software would transform the stream of data from the converter to any other form the application requires.
An ideal transmitter would be similar. A digital signal processor would generate a stream of numbers. These would be sent to a digital-to-analog converter connected to a radio antenna.
The ideal scheme is not completely realizable due to the current limits of the technology. The main problem in both directions is the difficulty of conversion between the digital and the analog domains at a high enough rate and a high enough accuracy at the same time, and without relying upon physical processes like interference and electromagnetic resonance for assistance.
Receiver architecture[edit]
Most receivers use a variable-frequency oscillator, mixer, and filter to tune the desired signal to a common intermediate frequency or baseband, where it is then sampled by the analog-to-digital converter. However, in some applications it is not necessary to tune the signal to an intermediate frequency and the radio frequency signal is directly sampled by the analog-to-digital converter (after amplification).
Real analog-to-digital converters lack the dynamic range to pick up sub-microvolt, nanowatt-power radio signals. Therefore, a low-noise amplifier must precede the conversion step and this device introduces its own problems. For example, if spurious signals are present (which is typical), these compete with the desired signals within the amplifier's dynamic range. They may introduce distortion in the desired signals, or may block them completely. The standard solution is to put band-pass filters between the antenna and the amplifier, but these reduce the radio's flexibility. Real software radios often have two or three analog channel filters with different bandwidths that are switched in and out.
History[edit]
The term 'digital receiver' was coined in 1970 by a researcher at a United States Department of Defense laboratory. A laboratory called the Gold Room at TRW in California created a software baseband analysis tool called Midas, which had its operation defined in software.
The term 'software radio' was coined in 1984 by a team at the Garland, Texas, Division of E-Systems Inc. (now Raytheon) to refer to a digital baseband receiver and published in their E-Team company newsletter. A 'Software Radio Proof-of-Concept' laboratory was developed by the E-Systems team that popularized Software Radio within various government agencies. This 1984 Software Radio was a digital baseband receiver that provided programmable interference cancellation and demodulation for broadband signals, typically with thousands of adaptive filter taps, using multiple array processors accessing shared memory.[4]
In 1991, Joe Mitola independently reinvented the term software radio for a plan to build a GSM base station that would combine Ferdensi's digital receiver with E-Systems Melpar's digitally controlled communications jammers for a true software-based transceiver. E-Systems Melpar sold the software radio idea to the US Air Force. Melpar built a prototype commanders' tactical terminal in 1990-91 that employed Texas Instruments TMS320C30 processors and Harris digital receiver chip sets with digitally synthesized transmission. The Melpar prototype didn't last long because when E-Systems ECI Division manufactured the first limited production units, they decided to 'throw out those useless C30 boards,' replacing them with conventional RF filtering on transmit and receive, reverting to a digital baseband radio instead of the SPEAKeasy like IF ADC/DACs of Mitola's prototype. The Air Force would not let Mitola publish the technical details of that prototype, nor would they let Diane Wasserman publish related software life cycle lessons learned because they regarded it as a 'USAF competitive advantage.' So instead, with USAF permission, in 1991 Mitola described the architecture principles without implementation details in a paper, 'Software Radio: Survey, Critical Analysis and Future Directions' which became the first IEEE publication to employ the term in 1992.[5] When Mitola presented the paper at the conference, Bob Prill of GEC Marconi began his presentation following Mitola with 'Joe is absolutely right about the theory of a software radio and we are building one.' Prill gave a GEC Marconi paper on PAVE PILLAR, a SPEAKeasy precursor. SPEAKeasy, the military software radio was formulated by Wayne Bonser, then of Rome Air Development Center (RADC), now Rome Labs; by Alan Margulies of MITRE Rome, NY; and then Lt Beth Kaspar, the original DARPA SPEAKeasy project manager and by others at Rome including Don Upmal. Although Mitola's IEEE publications resulted in the largest global footprint for software radio, Mitola privately credits that DoD lab of the 1970s with its leaders Carl, Dave, and John with inventing the digital receiver technology on which he based software radio once it was possible to transmit via software.
A few months after the National Telesystems Conference 1992, in an E-Systems corporate program review, a vice-president of E-Systems Garland Division objected to Melpar's (Mitola's) use of the term 'software radio' without credit to Garland. Alan Jackson, Melpar VP of marketing at that time, asked the Garland VP if their laboratory or devices included transmitters. The Garland VP said 'No, of course not — ours is a software radio receiver'. Al replied 'Then it's a digital receiver but without a transmitter, it's not a software radio.' Corporate leadership agreed with Al, so the publication stood. Many amateur radio operators and HF radio engineers had realized the value of digitizing HF at RF and of processing it with Texas Instruments TI C30 digital signal processors (DSPs) and their precursors during the 1980s and early 1990s. Radio engineers at Roke Manor in the UK and at an organization in Germany had recognized the benefits of ADC at the RF in parallel, so success has many fathers. Mitola's publication of software radio in the IEEE opened the concept to the broad community of radio engineers. His May 1995 special issue of the IEEE Communications Magazine with the cover 'Software Radio' was regarded as watershed event with thousands of academic citations. Mitola was introduced by Joao da Silva in 1997 at the First International Conference on Software Radio as 'godfather' of software radio in no small part for his willingness to share such a valuable technology 'in the public interest.'
The package also includes thoughts, prayer and daily devotional on that specific verse.- Read the Afrikaans Bible free, can switch between of 57 languages of Bible, include Bible, Verses, Audios.- Scripture Pictures, update daily, choose picture, download, set as app background and set as lock screen, shareable.- Bookmarks: Add favorites verse, Sharing, memorizing, finding your favorite verses - Create note. Easy create your note, your opinion.- Share verses with friends: social media, email, or SMS/text.Read, study, and share with friends. Download afrikaanse bybel 1953 vertaling penny. Moenie 'n oomblik langer wag nie, kry die Afrikaanse Bybel gratis sodat u u gunsteling verse elke dag kan lees en die leringe ted eel met u vriende en geliefdes.Onthou dat God u altyd sal lief he, begeleidend wees op u pad en Hy sal altyd na u omsien. Bybel - Afrikaans Bible- READ THE AFRKAANS HOLY BIBLE DAILYFeature: - Delivers a new verse of the day from Afrikaans languages and 11 other languages. Moet nooit alleen of hulpeloos voel nie, volg Sy woord en u sal die lig aan die einde van die tonnel sien.Word elke oggend wakker en lees verse van Sy Heilige Boek en u sal sien hoe u dag heeltemal verander.
Perhaps the first software-based radio transceiver was designed and implemented by Peter Hoeher and Helmuth Lang at the German Aerospace Research Establishment (DLR, formerly DFVLR) in Oberpfaffenhofen, Germany, in 1988.[6] Both transmitter and receiver of an adaptive digital satellite modem were implemented according to the principles of a software radio, and a flexible hardware periphery was proposed.
The term 'software defined radio' was coined in 1995 by Stephen Blust, who published a request for information from Bell South Wireless at the first meeting of the Modular Multifunction Information Transfer Systems (MMITS) forum in 1996, organized by the USAF and DARPA around the commercialization of their SPEAKeasy II program. Mitola objected to Blust's term, but finally accepted it as a pragmatic pathway towards the ideal software radio. Although the concept was first implemented with an IF ADC in the early 1990s, software-defined radios have their origins in the U.S. and European defense sectors of the late 1970s(for example, Walter Tuttlebee described a VLF radio that used an ADC and an 8085 microprocessor).[7] about a year after the First International Conference in Brussels. One of the first public software radio initiatives was the U.S. DARPA-Air Force military project named SpeakEasy. The primary goal of the SpeakEasy project was to use programmable processing to emulate more than 10 existing military radios, operating in frequencybands between 2 and 2000 MHz.[8] Another SPEAKeasy design goal was to be able to easily incorporate new coding and modulation standards in the future, so that military communications can keep pace with advances in coding and modulation techniques.
SPEAKeasy phase I[edit]
From 1990 to 1995, the goal of the SPEAKeasy program was to demonstrate a radio for the U.S. Air Force tactical ground air control party that could operate from 2 MHz to 2 GHz, and thus could interoperate with ground force radios (frequency-agile VHF, FM, and SINCGARS), Air Force radios (VHF AM), Naval Radios (VHF AM and HFSSBteleprinters) and satellites (microwaveQAM). Some particular goals were to provide a new signal format in two weeks from a standing start, and demonstrate a radio into which multiple contractors could plug parts and software.
The project was demonstrated at TF-XXI Advanced Warfighting Exercise, and demonstrated all of these goals in a non-production radio. There was some discontent with failure of these early software radios to adequately filter out of band emissions, to employ more than the simplest of interoperable modes of the existing radios, and to lose connectivity or crash unexpectedly. Its cryptographic processor could not change context fast enough to keep several radio conversations on the air at once. Its software architecture, though practical enough, bore no resemblance to any other. The SPEAKeasy architecture was refined at the MMITS Forum between 1996 and 1999 and inspired the DoD integrated process team (IPT) for programmable modular communications systems (PMCS) to proceed with what became the Joint Tactical Radio System (JTRS).
The basic arrangement of the radio receiver used an antenna feeding an amplifier and down-converter (see Frequency mixer) feeding an automatic gain control, which fed an analog to digital converter that was on a computer VMEbus with a lot of digital signal processors (Texas Instruments C40s). The transmitter had digital to analog converters on the PCI bus feeding an up converter (mixer) that led to a power amplifier and antenna. The very wide frequency range was divided into a few sub-bands with different analog radio technologies feeding the same analog to digital converters. This has since become a standard design scheme for wideband software radios.
SPEAKeasy phase II[edit]
The goal was to get a more quickly reconfigurable architecture, i.e., several conversations at once, in an open software architecture, with cross-channel connectivity (the radio can 'bridge' different radio protocols). The secondary goals were to make it smaller, cheaper, and weigh less.
The project produced a demonstration radio only fifteen months into a three-year research project. This demonstration was so successful that further development was halted, and the radio went into production with only a 4 MHz to 400 MHz range.
The software architecture identified standard interfaces for different modules of the radio: 'radio frequency control' to manage the analog parts of the radio, 'modem control' managed resources for modulation and demodulation schemes (FM, AM, SSB, QAM, etc.), 'waveform processing' modules actually performed the modem functions, 'key processing' and 'cryptographic processing' managed the cryptographic functions, a 'multimedia' module did voice processing, a 'human interface' provided local or remote controls, there was a 'routing' module for network services, and a 'control' module to keep it all straight.
The modules are said to communicate without a central operating system. Instead, they send messages over the PCIcomputer bus to each other with a layered protocol.
As a military project, the radio strongly distinguished 'red' (unsecured secret data) and 'black' (cryptographically-secured data).
The project was the first known to use FPGAs (field programmable gate arrays) for digital processing of radio data. The time to reprogram these was an issue limiting application of the radio. Today, the time to write a program for an FPGA is still significant, but the time to download a stored FPGA program is around 20 milliseconds. This means an SDR could change transmission protocols and frequencies in one fiftieth of a second, probably not an intolerable interruption for that task.
Current usage[edit]
Military[edit]
USA[edit]
The Joint Tactical Radio System (JTRS) was a program of the US military to produce radios that provide flexible and interoperable communications. Examples of radio terminals that require support include hand-held, vehicular, airborne and dismounted radios, as well as base-stations (fixed and maritime).
This goal is achieved through the use of SDR systems based on an internationally endorsed open Software Communications Architecture (SCA). This standard uses CORBA on POSIX operating systems to coordinate various software modules.
![Comparisons Comparisons](/uploads/1/2/5/0/125007006/901355377.jpg)
The program is providing a flexible new approach to meet diverse soldier communications needs through software programmable radio technology. All functionality and expandability is built upon the SCA.
The SCA, despite its military origin, is under evaluation by commercial radio vendors for applicability in their domains. The adoption of general-purpose SDR frameworks outside of military, intelligence, experimental and amateur uses, however, is inherently hampered by the fact that civilian users can more easily settle with a fixed architecture, optimized for a specific function, and as such more economical in mass market applications. Still, software defined radio's inherent flexibility can yield substantial benefits in the longer run, once the fixed costs of implementing it have gone down enough to overtake the cost of iterated redesign of purpose built systems. This then explains the increasing commercial interest in the technology.
SCA-based infrastructure software and rapid development tools for SDR education and research are provided by the Open Source SCA Implementation – Embedded (OSSIE[9]) project. The Wireless Innovation Forum funded the SCA Reference Implementation project, an open source implementation of the SCA specification. (SCARI) can be downloaded for free.
Amateur and home use[edit]
Microtelecom Perseus - a HF SDR for the amateur radio market
A typical amateur software radio uses a direct conversion receiver. Unlike direct conversion receivers of the more distant past, the mixer technologies used are based on the quadrature sampling detector and the quadrature sampling exciter.[10][11][12][13]
The receiver performance of this line of SDRs is directly related to the dynamic range of the analog-to-digital converters (ADCs) utilized.[14] Radio frequency signals are down converted to the audio frequency band, which is sampled by a high performance audio frequency ADC. First generation SDRs used a PC sound card to provide ADC functionality. The newer software defined radios use embedded high performance ADCs that provide higher dynamic range and are more resistant to noise and RF interference.
A fast PC performs the digital signal processing (DSP) operations using software specific for the radio hardware. Several software radio efforts use the open source SDR library DttSP.[15]
The SDR software performs all of the demodulation, filtering (both radio frequency and audio frequency), and signal enhancement (equalization and binaural presentation). Uses include every common amateur modulation: morse code, single sideband modulation, frequency modulation, amplitude modulation, and a variety of digital modes such as radioteletype, slow-scan television, and packet radio.[16] Amateurs also experiment with new modulation methods: for instance, the DREAMopen-source project decodes the COFDM technique used by Digital Radio Mondiale.
There is a broad range of hardware solutions for radio amateurs and home use. There are professional-grade transceiver solutions, e.g. the Zeus ZS-1[17][18] or the Flex Radio,[19] home-brew solutions,e.g. PicAStar transceiver, the SoftRock SDR kit,[20] and starter or professional receiver solutions, e.g. the FiFi SDR[21] for shortwave, or the Quadrus coherent multi-channel SDR receiver[22] for short wave or VHF/UHF in direct digital mode of operation.
Internals of a low-cost DVB-T USB dongle that uses Realtek RTL2832U (square IC on the right) as the controller and Rafael Micro R820T (square IC on the left) as the tuner.
It has been discovered that some common low-cost DVB-T USB dongles with the Realtek RTL2832U[23][24] controller and tuner, e.g. the Elonics E4000 or the Rafael Micro R820T,[25] can be used as a wide-band SDR receiver. Recent experiments have proven the capability of this setup to analyze perseids shower using the graves radar signals.[26]
GNU Radio logo
More recently,[when?] the GNU Radio using primarily the Universal Software Radio Peripheral (USRP) uses a USB 2.0 interface, an FPGA, and a high-speed set of analog-to-digital and digital-to-analog converters, combined with reconfigurable free software. Its sampling and synthesis bandwidth is a thousand times that of PC sound cards, which enables wideband operation.
The HPSDR (High Performance Software Defined Radio) project uses a 16-bit 135 MSPS analog-to-digital converter that provides performance over the range 0 to 55 MHz comparable to that of a conventional analogue HF radio. The receiver will also operate in the VHF and UHF range using either mixer image or alias responses. Interface to a PC is provided by a USB 2.0 interface, although Ethernet could be used as well. The project is modular and comprises a backplane onto which other boards plug in. This allows experimentation with new techniques and devices without the need to replace the entire set of boards. An exciter provides 1/2 W of RF over the same range or into the VHF and UHF range using image or alias outputs.[27]
WebSDR[28] is a project initiated by Pieter-Tjerk de Boer providing access via browser to multiple SDR receivers worldwide covering the complete shortwave spectrum. Recently he has analyzed Chirp Transmitter signals using the coupled system of receivers.[29]
Other SDR applications
Many studies have identified SDR's potential applications[30] in Opportunity Driven Multiple Access (ODMA), Spectrum Regulation and Cost Reduction, cooperative wireless networks diversity, quantum optical communications, investigations of the strength of the magnetic resonance etc. as the research advances rapidly.
See also[edit]
References[edit]
- ^Software Defined Radio: Architectures, Systems and Functions (Markus Dillinger, Kambiz Madani, Nancy Alonistioti) Page xxxiii (Wiley & Sons, 2003, ISBN0-470-85164-3)
- ^Staple, Gregory; Werbach, Kevin (March 2004). 'The End of Spectrum Scarcity'. IEEE Spectrum.
- ^'Open Spectrum: A Global Pervasive Network'.
- ^P. Johnson, 'New Research Lab Leads to Unique Radio Receiver,' E-Systems Team, May 1985, Vol. 5, No. 4, pp 6-7 http://chordite.com/team.pdf
- ^Mitola III, J. (1992). Software radios-survey, critical evaluation and future directions. National Telesystems Conference. pp. 13/15 to 13/23. doi:10.1109/NTC.1992.267870. ISBN0-7803-0554-X.
- ^P. Hoeher and H. Lang, 'Coded-8PSK modem for fixed and mobile satellite services based on DSP,' in Proc. First Int. Workshop on Digital Signal Processing Techniques Applied to Space Communications, ESA/ ESTEC, Noordwijk, Netherlands, Nov. 1988; ESA WPP-006, Jan. 1990, pp. 117-123.
- ^First International Workshop on Software Radio, Greece 1998
- ^RJ Lackey and DW Upmal contributed the article 'Speakeasy: The Military Software Radio' to the IEEE Communications Magazine special issue that Mitola edited and for which Mitola wrote the lead article 'Software Radio Architecture', in May 1995.
- ^'OSSIE'. vt.edu. Archived from the original on 2009-03-12.
- ^Youngblood, Gerald (July 2002), 'A Software Defined Radio for the Masses, Part 1'(PDF), QEX, American Radio Relay League: 1–9
- ^Youngblood, Gerald (Sep–Oct 2002), 'A Software Defined Radio for the Masses, Part 2'(PDF), QEX, American Radio Relay League: 10–18
- ^Youngblood, Gerald (Nov–Dec 2002), 'A Software Defined Radio for the Masses, Part 3'(PDF), QEX, American Radio Relay League: 1–10
- ^Youngblood, Gerald (Mar–Apr 2003), 'A Software Defined Radio for the Masses, Part 4'(PDF), QEX, American Radio Relay League: 20–31
- ^Rick Lindquist; Joel R. Hailas (October 2005). 'FlexRadio Systems; SDR-1000 HF+VHF Software Defined Radio Redux'. QST. Retrieved 2008-12-07.
- ^DttSP http://dttsp.sourceforge.net/
- ^http://sourceforge.net/projects/sdr Open source SDR transceiver project using USRP and GNU Radio
- ^ZS-1 Project http://zs-1.ru
- ^ZS-1 Zeus Transceiver http://www.radioaficion.com/HamNews/articles/9483-zeus-zs-1-sdr-transceiver.html
- ^Flex Radio SDR Transceiver http://www.flex-radio.com/
- ^SoftRock SDR Kits http://wb5rvz.com/sdr/
- ^FiFi SDR Receiver http://o28.sischa.net/fifisdr/trac
- ^Quadrus coherenet multi-channel SDR receiver http://spectrafold.com/quadrus
- ^Using DVB USB Stick as SDR Receiver http://sdr.osmocom.org/trac/wiki/rtl-sdr
- ^RTL-SDR Blog http://www.rtl-sdr.com
- ^Support for the Rafael Micro R820T tuner in Cocoa Radio http://www.alternet.us.com/?p=1814
- ^'Perseids shower using graves radar'. EB3FRN.
- ^'HPSDR Web Site'.
- ^WebSDR http://websdr.org
- ^Chirp Signals analyzed using SDR http://websdr.ewi.utwente.nl:8901/chirps/
- ^Machado-Fernández, José Raúl (January 2015). 'Software Defined Radio: Basic Principles and Applications'. Revista Facultad de Ingeniería. 24 (38): 79–96. ISSN0121-1129.
Further reading[edit]
- Rohde, Ulrich L (February 26–28, 1985). 'Digital HF Radio: A Sampling of Techniques'. Third International Conference on HF Communication Systems and Techniques. London, England.
- Software defined radio : architectures, systems, and functions. Dillinger, Madani, Alonistioti. Wiley, 2003. 454 pages. ISBN0-470-85164-3ISBN9780470851647
- Cognitive Radio Technology. Bruce Fette. Elsevier Science & Technology Books, 2006. 656 pags. ISBN0-7506-7952-2ISBN9780750679527
- Software Defined Radio for 3G, Burns. Artech House, 2002. ISBN1-58053-347-7
- Software Radio: A Modern Approach to Radio Engineering, Jeffrey H. Reed. Prentice Hall PTR, 2002. ISBN0-13-081158-0
- Signal Processing Techniques for Software Radio, Behrouz Farhang-Beroujeny. LuLu Press.
- RF and Baseband Techniques for Software Defined Radio, Peter B. Kenington. Artech House, 2005, ISBN1-58053-793-6
- The ABC's of Software Defined Radio, Martin Ewing, AA6E. The American Radio Relay League, Inc., 2012, ISBN978-0-87259-632-0
- Software Defined Radio using MATLAB & Simulink and the RTL-SDR, R Stewart, K Barlee, D Atkinson, L Crockett, Strathclyde Academic Media, September 2015. ISBN978-0-9929787-2-3
External links[edit]
Wikimedia Commons has media related to Software defined radios. |
Software Defined Radio Receiver
- The world's first web-based software-defined receiver at the university of Twente, the Netherlands
Sfdr Definition Software Defined Radio
Retrieved from 'https://en.wikipedia.org/w/index.php?title=Software-defined_radio&oldid=917160649'