The flexibility possible with software-defined radios (SDRs) is key to the future of wireless communication systems. Prior generations of wireless devices relied on highly customized, application-specific hardware with little emphasis on future-proofing or adaptation to new standards. This design approach generally yielded power- and performance-optimized solutions at the expense of flexibility and interoperability.
Over the past decade, SDRs have evolved and spawned related technologies such as cognitive radios (CRs), to give the current generation of communication systems tremendous flexibility, reusability, and adaptability. Wireless device developers, as well as service providers and end users, can upgrade or reconfoigure SDRs and CRs continually as new versions of wireless standards are released. Furthermore, SDR/CR devices can adapt continually to changes in the spectral or network environment, including modulation schemes, channel coding, and bandwidth. They can use be used to establish and maintain ad hoc networks.
Given these advantages, SDR research has been accelerating at an astounding pace. The primary challenges are performance limitations imposed by the current generation of underlying hardware and software architectures. The size, weight, performance, and power consumption of current digital processing hardware, such as FPGAs and DSPs, are inadequate for realizing a fully software-based radio. As a result, SDR research is ongoing in all areas: hardware solutions, algorithms, protocols, software implementations, and applications. All these areas are interrelated and tightly coupled, so it’s unlikely that a solution in a single area—for example, a reconfigurable, massively parallel, general-purpose processor—will enable the ultimate SDR vision: a radio consisting of nothing more than an antenna, analog-to-digital converter, and digital processor. Advancing the SDR state of the art will require cross-disciplinary research and engineering.
Selected Articles for Software-Defined Radio
To explore the development of both the underlying SDR hardware and software, as well as the capabilities of an SDR communications system, we’ve selected five articles for this special theme that investigate the state of the art in several areas.
The first two papers describe the analysis of SDR applications and algorithms that lead to processor microarchitectures and instruction-set decisions. “AnySP: Anytime Anywhere Anyway Signal Processing” (login required for full text) is an article IEEE Micro magazine that describes the development of a complete device based on the analysis of mobile-signal-processing algorithms. “Dynamically Reconfigurable Instruction Set for Software Radio Encoding/Coding,” (login required for full text) a conference paper, develops reconfigurable DSP instruction sets that reduce the computational cost of implementing complex encoding and decoding algorithms.
Another conference paper, “Open Platform for Prototyping of Advanced Software Defined Radio and Cognitive Radio Techniques,” (login required for full text) describes the ongoing development of a hardware platform to support prototyping a wide range of SDR and CR systems.
The fourth article, “Semantics in Cognitive Radio,” (login required for full text) examines the need to develop a language that lets radios communicate with each other and interpret local, regional, and national spectrum policies. This capability would let SDRs be fully self-aware of not only the spectral environment but also the network and other communication devices in their range.
The final article, “Radio Tomographic Imaging with Wireless Networks,” (login required for full text) is from the IEEE Transactions on Mobile Computing. The authors describe an interesting application that takes advantage of SDR’s flexibility to identify object location and motion using only wireless links. The application demonstrates SDRs capabilities in an ad hoc peer-to-peer network.
All these articles are available from the Computer Society Digital Library through this month’s special issue of Computing Now. In addition, numerous articles from other IEEE societies are well worth review; we’ve included links to some of these article and their abstracts in the Related Resources section below.
SDR exemplifies a new computing paradigm in which computing hardware works in concert with general analog hardware to form a system that’s more capable than the sum of its parts. Computing provides the traditional capabilities of user interfaces, data management and conversion, and protocol management, but it can also augment or replace hardware in areas such as modulation and demodulation, encoding and decoding, and noise cancellation. In addition, computing can perform many tasks that haven’t yet been implemented in significant ways, such as whitespace utilization, sophisticated capability- and cost-based service negotiations, and new applications.
Opportunities in SDR abound—read, explore, and contribute!
The following links are to article abstracts. The articles are available to IEEE Xplore subscribers for free and to other interested readers for a fee.
Note: Login is required to access the full text of these articles.
- “An Agile Radio for Wireless Innovation,” by Gary J. Minden et al., IEEE Communications Magazine, vol. 45, no. 5, May 2007, pp. 113–121; DOI: 10.1109/MCOM.2007.358857. Sponsored by IEEE Communications Society.
- “Implementation of an SDR System using Graphics Processing Unit,” by June Kim, Seungheon Hyeon, and Seungwon Choi, IEEE Communications Magazine, vol. 48, no. 3, Mar. 2010, pp. 156–162; DOI: 10.1109/MCOM.2010.5434388. Sponsored by IEEE Communications Society.
- “A Disruptive Receiver Architecture Dedicated to Software-Defined Radio,” by Francois Rivet et al. IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 55, no. 4, Apr. 2008, pp. 344–348; DOI: 10.1109/TCSII.2008.919512. ISSN: 1549-7747. INSPEC Accession Number: 9921370. Sponsored by the IEEE Circuits and Systems Society.
- “A Survey of Artificial Intelligence for Cognitive Radios,” by An He et al., IEEE Transactions on Vehicular Technology, vol. 59, no. 4, May 2010, pp. 1578–1592; DOI: 10.1109/TVT.2010.2043968. Sponsored by IEEE Vehicular Technology Society.
- “Towards a Unified Policy Language for Future Communication Networks: A Process,” by Mieczyslaw M. Kokar et al., Proc. 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN 08), IEEE Press, 2008, pp. 673–682. DOI: 10.1109/DYSPAN.2008.74.
- “Open-Source SCA-Based Core Framework and Rapid Development Tools Enable Software-Defined Radio Education and Research,” by Carlos R. Aguayo Gonzalez et al., IEEE Communications Magazine, vol. 47, no. 10, Oct. 2009, pp. 48–55. DOI: 10.1109/MCOM.2009.5273808. Sponsored by IEEE Communications Society.
- “Using Software Defined Radio (SDR) to Demonstrate Concepts in Communications and Signal Processing Courses,” by Sharlene Katz and James Flynn, Proc. 29th IEEE Frontiers in Education Conference (FIE 09), IEEE Press, 2009, pp. 1432–1437. DOI: 10.1109/FIE.2009.5350716.