Software-Defined Radio Demonstrators: An Example and Future Trends

Hindawi Publishing Corporation International Journal of Digital Multimedia Broadcasting Volume 2009, Article ID 547650, 12 pages doi:10.1155/2009/547650 Research Article Software-Defined Radio Demonstrators: An Example and Future Trends Ronan Farrell, Magdalena Sanchez, and Gerry Corley Centre for Telecommunications Value Chain Research, Institute of Microelectronics and Wireless Systems, National University of Ireland Maynooth, Maynooth, Co. Kildare, Ireland Correspondence should be addressed to Ronan Farrell, Received 30 September 2008; Accepted 14 January 2009 Recommended by Daniel Iancu Software-defined radio requires the combination of software-based signal processing and the enabling hardware components. In this paper, we present an overview of the criteria for such platforms and the current state of development and future trends in this area. This paper will also provide details of a high-performance flexible radio platform called the maynooth adaptable radio system (MARS) that was developed to explore the use of software-defined radio concepts in the provision of infrastructure elements in a telecommunications application, such as mobile phone basestations or multimedia broadcasters. Copyright © 2009 Ronan Farrell et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1. Introduction In recent years the technologies required to implement the concept of software-defined radio (SDR) have matured, and the SDR Forum presents a tier-based taxonomy for the capabilities of various SDR systems [1]. Systems are now appearing that offer flexibility and adaptability to system developers—providing advantages when addressing the issues of constrained spectrum resources, increasingly rapid changes in wireless standards, and cost-effectively developing products for niche markets [2, 3]. As the required technologies have matured, we are now seeing SDR implementations delivering wide bandwidth applications with a high quality of service, for example, in mobile data communications such as WiMAX-e. In the future it can be imagined that SDR architectures will be increasingly used to deliver telecommunication services such as mobile telephony, digital TV and radio broadcasts and heterogeneous combinations such as streaming video in the mobile environment. As spectrum is a finite-shared resource that is increasingly congested with existing users, obtaining access to spectrum for the delivery of new services is increasingly difficult. Frequency agile SDR systems offer a solution where the flexible SDR radio can avail of an unused slice of spectrum, temporarily, to deliver the service. Originally this concept met strong resistance from existing spectrum holders and the regulators, however, recently there has been increasing interest from the regulators (who can allow greater diversity of services) and from spectrum holders (who can utilize their spectrum more profitably). One initiative that supports this trend is the developing discussions in Europe on “Wireless Access Platforms for Electronic Communications Services (WAPECS)” where it is proposed that some services may opportunistically use spectrum, if available, in regional and temporal bases [4]. Though at an early stage, these initiatives suggest new opportunities for telecommunication services. In this paper we will present an overview of the challenges in designing an SDR platform that can be used for research or deployment. We will discuss the issues that need to be addressed and the current state-of-the art in softwaredefined radio demonstrators. This will then be followed by a detailed description of the maynooth adaptable radio system (MARS), its design criteria, architecture, and some use cases. Finally the paper will be concluded with some comments on the future direction of experimental SDR platforms. 2. Design Criteria for SDR Platforms Software-defined radio platforms are integrated systems of software and hardware that enable SDR applications to be International Journal of Digital Multimedia Broadcasting PHY RF signal processing Hardware 2 Baseband signal processing ? ? ? ? Data control & error correction Software MAC Modulation & demodulation Figure 1: Partitioning between software and hardware in an SDR system. developed and evaluated. Of the two, the software aspects are relatively more mature, and current work in this area focuses on performance enhancement and cognitive radio techniques. The hardware aspects of a platform consist of the radio-frequency (RF) elements, some baseband signal processing and communications link to the softwarebased signal processing element—perhaps a DSP, FPGA, or a general purpose processor (GPP). One aspect of the software-defined radio concept is that flexibility can be delivered through software. An often overlooked corollary is that the hardware performance to support that flexibility is more challenging than for a single-mode implementation, and optimal solutions remain elusive [5]. This section will comment on some of these issues and how they impact on the hardware architecture of software radio platform. 2.1. Partitioning of Resources. The software-defined radio philosophy represents a trend in electronic devices from transistors to software. This has been facilitated by the rapid increase in software capabilities and processing power. In software-defined radio the argument is to implement as much of the radio as possible in software and to control the remaining hardware features. However, the choice of where the partition between hardware and software has a fundamental impact on the design of any SDR platform [6, 7]. One desirable partitioning of functionality is to take all signal processing into the software domain and that only I- and Q-sampled data is passed into the hardware domain. In this scenario the hardware element of the system need undertakes no signal processing. This places a severe performance requirement upon the software processing element, particularly where bandwidths in excess of 1 MHz need to be supported. Alternatively some of the software processing load may be allocated to customized hardware (often in the form of an embedded FPGA or a specialist DSP device). In this scenario the load is shared but FPGAs are expensive and arguably offer less flexibility. One of the important issues to consider when choosing the partitioning is the data communications protocol between the different elements. For unprocessed IQ signals, for every 1 MHz of spectrum, that is, being supported a data link capacity of 40 Mbps is required, assuming 16 bit samples and 8 b/10 b encoding. This is doubled for duplex transceivers. This severely limits the bandwidth capabilities of platforms that are required to connect to standard interfaces on general purpose computers. More complex, higher performance (...truncated)