Software Radio-Based Decentralized Dynamic Spectrum Access Networks: A Prototype Design and Experimental Results Feng Ge * , Aravind Radhakrishnan † , Mustafa Y. ElNainay ‡ , Qinqin Chen † , Charles W. Bostian † , Allen B. MacKenzie † * Telcordia Technologies, Inc., Piscataway, NJ, USA † Wireless @ Virginia Tech, Virginia Tech, Blacksburg, VA, USA ‡ CSE Department, Faculty of Engineering, Alexandria University, Egypt fge@telcordia.com, ara254@vt.edu, ymustafa@alex.edu.eg, {chenq, bostian, mackenab}@vt.edu Abstract—Significant progress has been made in the past few years on Dynamic Spectrum Access (DSA) wireless networks which seek to use RF spectrum more efficiently and dynamically. For example, many measurements of current spectrum utilization are available and theoretical analyses and computational simula- tions of DSA networks abound. In sharp contrast, few network systems, particularly those with a decentralized structure, have been built even at a small scale to investigate the performance, behavior, and dynamics of DSA networks. Our contribution is designing a decentralized and asynchronous DSA network and building a prototype based on software radio technologies, signal detection and classification methods, distributed coop- erative spectrum sensing systems, and mobile ad-hoc network (MANET) protocols. This paper details the network’s design and implementation as well as its enabling technologies. Through systematic experiments, we identify several factors influencing performance for decentralized DSA networks. I. I NTRODUCTION Supporting Dynamic Spectrum Access (DSA) in decentral- ized wireless networks drives complexity both within individ- ual nodes and over the whole network to an unprecedented level [1]. Both innovative protocols and novel architecture are needed. For example, the most basic requirement in DSA net- works is to guarantee non-interference to primary users while using RF spectrum more efficiently and dynamically. This requires a new set of functions related to spectrum sensing at the Physical (PHY) Layer. Node cooperation protocols and policy modules are also needed [1]. The coupling of channel allocation, power control, and topology control is necessary in DSA networks because of the dynamic radio environment [2], [3]. Further, cross-layer architecture is fundamentally required in DSA networks because the operating frequency bands depend on the channel occupancy measured at the PHY layer and directly impact the above layers both within and across nodes [4]. Moreover, new protocols and methods like Disruption Tolerant Networking (DTN) protocols and Content Based Access (CBA) techniques are also being included in DSA network design to cope with network connection disrup- tions under different environments [5], [6]. The first and third authors were previously with Virginia Tech. Because of the system complexity and the unavailability of a suitable open platform [7], few physical networks have been built to investigate the performance and dynamics of decentralized DSA networks. Nonetheless, good theoretical analyses and simulations have been carried out. For example, coupled power control and channel allocation optimization are heavily investigated [2], [3]. Game theory is also used to propose new protocols in spectrum sharing and to investigate individual nodes’ behavior in cognitive radio networks [8], [9]. Widely known in this research community are two built networks: DARPA’s XG [1] and Wireless Network after Next (WNaN) projects [6]. The first generated several publications which present significant results and insights in developing spectrum sensing methods, building individual DSA nodes, and testing overall systems in different network scenarios and RF environments [1]. Overall, this project reflects the com- plexity of DSA node architecture and some unique dynamics in DSA networks under different RF environments. However, the XG project was a centralized network [1]. An important goal of WNaN is to build a decentralized DSA network with about a thousand nodes [6]. Unfortunately, few details about the project are yet publicly available. Considering the complexity of both individual nodes and the network in DSA networks, experiments are necessary to gain insights into network design and to investigate network performance under different scenarios [1]. For example, a pro- tocol for power control must consider newly needed functions, their computation and communication cost, and the associated increase of system/network complexity. Otherwise, achievable power performance derived from theoretical analysis or sim- ulation will not be approached [3]. Further, in research of complex systems like cognitive radio networks, experimental methods can assess system/network conditions that may be neglected by analysis or simulation. Our view of decentralized DSA networks is shown in Figure 1. In this network, nodes opportunistically use vacant channels when primary users are not transmitting. The whole network consists of decentralized mobile nodes and works in a dynamic radio environment where fading and interference 978-1-4244-5638-3/10/$26.00 ©2010 IEEE This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE Globecom 2010 proceedings.