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TOPICS IN RADIO COMMUNICATIONS
XG Dynamic Spectrum Access Field Test Results Mark McHenry, Eugene Livsics, Thao Nguyen, and Nivedita Majumdar, Shared Spectrum Company
ABSTRACT The XG Radio system uses dynamic spectrum access technology to determine locally unused spectrum, and then operates on these channels without causing interference to existing non-cooperative users. In August 2006 the XG Radio system was field tested at Fort A.P. Hill, Virginia, in the laboratory, and at field locations in Northern Virginia. There were three major test criteria: to cause no harm (avoid interference), to work (form and maintain connected networks), and to add value (efficiently use spectrum). This article defines the test metrics for fulfillment of these criteria, and describes the test results.
INTRODUCTION A cognitive radio system adapts its transmission and reception parameters based on the active monitoring of its radio environment to communicate efficiently without interfering with licensed users [1–6]. On August 15–17, 2006, the U.S. Department of Defense’s (DoD) Defense Advanced Research Projects Agency (DARPA) demonstrated, for the first time, a six-node network of next-generation (XG) radios [7] capable of using spectrum over a wide range of frequencies on a secondary basis. The XG networks sensed radio signals from primary users over a wide range of frequencies (225–600 MHz) and operated on the unused channels. Building on previous work [8–10], listenbefore-talk and look-through methods were demonstrated to work in multiple-network environments and allowed existing legacy radio networks to operate without interference from XG cognitive radios. Policy-based enforcement was used to operate in distinct frequency bands as permitted by DoD frequency managers in conjunction with FCC special temporary authorizations (STAs). Radios equipped with XG software successfully operated against fielded DoD military radio systems in realistic operational scenarios, as well as frequency reassignment, rendezvous, and frequency negotiation among disparate XG networks. XG networks were able to operate with up to six nodes while mobile. A DoD military training test range was used (Ft. A. P. Hill, Bowling Green, Virginia).
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In these tests, XG networks demonstrated the capability to support a variety of traffic loads, ranging from low-bit-rate data up to streaming video. XG’s live performance used a mix of preplanned scenarios and government-controlled vehicle movements. The preplanned scenarios were used to demonstrate the cognitive radios’ operation in a variety of rigorous test conditions. Government-controlled movements of XG nodes allowed government witnesses to move XG nodes while watching real-time displays of XG frequency adaptation, XG link performance, and non-interference to military legacy radio networks. This was effective in demonstrating that XG nodes were working properly. A few times XG networks did not behave as predicted. This showed us correctable weaknesses in XG algorithms, and allows us to create a list of improvements as part of DARPA’s technology maturation program for XG. The fact that these trials were live and witnessed by nearly 100 U.S. government and industry representatives permitted DARPA to receive instant feedback after the demonstration tests regarding XG’s desirability for technology insertion into funded DoD radio communications projects.
XG SYSTEM DESCRIPTION This section provides a brief description of the XG radio system. Details can be found in [11]. The A. P. Hill XG radio uses dynamic spectrum access technology to determine locally unused spectrum, and then operates on these channels without causing interference to existing noncooperative (NC) users. The system uses rendezvous, frequency selection, and spectrum access control algorithms to rapidly select available and authorized channels or bands to use at any given time and location. This technology provides a proven ability to maintain network with high quality-of-service (QoS) connectivity in challenging radio frequency (RF) environments and mobile scenarios. To avoid interference, the system uses spectrum access control policies that are derived from knowledge of multiple spectrum bands and NC legacy radio types. Sensitive detectors are used to identify unused authorized spectrum. The system uses a WiMAX physical layer, with a 1.75 MHz bandwidth orthogonal frequency-division multiplexing (OFDM) signal.
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This “transparent” and accountable software architecture facilitates the regulatory and stakeholder approval process. It also provides a flexible and comprehensive control to accommodate complex stakeholder and end-user requirements.
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The XG radios operated as either base stations or subscribers following the WiMAX architecture. (It is important to understand that the limitations inherent in a base station/subscriber system are not inherent to XG. They are imposed on the present setup only by the choice of WiMAX as a convenient testbed.) The transmit power level was 20 dBm. A custom-built transceiver frequency-translated the WiMAX modem’s intermediate frequency (IF) signal to the 225–600 MHz RF signal. The XG radios were installed in vans to enable mobile testing. The XG radios used a broad bandwidth discone antenna for the XG signal. The XG radios used the Global Positioning System (GPS) to obtain position information and synchronize the computer clocks so that time-aligned log files could be used to analyze the results. An 802.11g wireless backhaul (telemetry) system provided real-time radio state information to the displays at the VIP center where test witnesses assembled. The XG radio system under development has other components, some of which have been evaluated in tests at A. P. Hill but are not described in this article. The system under development will use a trusted dynamic policy control architecture. The policy analyzer validates externally created spectrum access policies for consistency and accuracy. The policy administrator securely and remotely manages policies on devices. The policies are stored in a protected, tamper-resistant repository. The policy enforcer ensures that each device adheres to assigned policies. This “transparent” and accountable software architecture facilitates the regulatory and stakeholder approval process. It also provides flexible and comprehensive control to accommodate complex stakeholder and end-user requirements. Additional planned elements include a scheduler that enables the detector to share the RF chain with the modem, substantially reducing the overall cost of the system. Another subsystem, group sensing, uses distributed measurements made by individual nodes and fused across a collection of nodes to provide a probabilistic estimate of the geographical location of spectrum holes. Group sensing has undergone simulation and empirical validation with propagation measurements taken at Fort A. P. Hill in separate tests. Together, these elements form a system that is able to dynamically access spectrum in many different spectrum bands (DoD, public safety, commercial spectrum, etc.) with high transmit power and without causing interference.
TEST SCENARIOS Two A. P. Hill test scenarios were used. Scenario 1 used three pairs of XG radios. Each pair was instructed to maintain communications with each other and to ignore the other XG nodes. If the XG nodes were in close proximity to each other, then three 1.75 MHz bandwidth channels would be required for operation. If the XG radios were widely separated, fewer channels were required. Each XG radio pair was allowed to dynamically select one out of six channels within the 225–600 MHz range. To show the reduction in interference provid-
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ed by the XG dynamic spectrum access (DSA) technology, each scenario was enacted twice. In scenario 1a (high interference), the XG radios operated on a fixed frequency and did not employ DSA. In scenario 1b (no interference), the XG radios used DSA. Scenario 2 used four XG radios that were instructed to form a radio net using a single 1.75 MHz bandwidth channel. If any of the four XG radios had to abandon the channel to avoid causing interference, all of the radios would rendezvous on a new channel. Scenario 2 is a more difficult problem than scenario 1 because of the complexity in negotiating for a common channel. In scenario 2a (high interference), the XG radios operated on a fixed frequency and did not employ DSA. In Scenario 2b (no interference), the XG radios used DSA. In all scenarios there were five pairs of NC DoD and commercial radios operating in the area. Each of these radios used a different channel that overlapped with the six channels the XG radio was allowed to use. The NC radios were instrumented for measurement of either the bit error rate (BER) or packet acceptance rate. Additional interference-to-noise ratio (INR) tests were conducted using commercial radios. NC radios were stationary, while XG radio networks were tested in both stationary and mobile scenarios. The test area was a 1 km × 4 km open area at Fort A. P. Hill. The terrain had small rolling hills and gullies that created a complex propagation environment.
TEST METRICS AND RESULTS This section describes the test metrics and the results. There were three fundamental criteria for test success: That XG “causes no harm” (avoids causing interference), that XG “works” (forms and maintains connected networks), and that XG “adds value” (efficiently uses spectrum). For each of these criteria there are two or three metrics, for a total of eight system metrics. In the list below, DARPA requirements are given, with their corresponding metrics. For DARPA-mandated metrics, criterion of success is given (in parentheses). Criterion 1: Must do no harm • Channel abandonment time (< 500 ms) • Interference-to-noise ratio Criterion 2: Must work • Network join time ( 50 available channels.
Channel re-establishment time — cumulative distribution function 2006-09-25, lab test, re-establish network of X nodes, six available channels 1 “Kink” in the two-node case is caused when the base station detects non-cooperative and then has a delay after change frequency command to allow subscriber queues to empty
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Link uptime is defined as the percentage of time a network maintains its connection to all nodes in the network. Optimally, this should be 100 percent, but is reduced because of several factors. • Link closure is not possible when all nodes are not radio-reachable. If an XG node is out of radio range, no amount of networking protocol can overcome the issue of insufficient signal strength. • Link closure is also not possible if there is no available channel for communication. • Link closure may not be possible when the XG algorithms do not operate properly. The goal here is to judge the performance of XG algorithms, but we are not able to separate out the other two factors. Therefore, the link downtimes reported in this section are not exclusively results of undesirable XG behavior, but influenced by these other factors. A summary figure representing the overall link uptime statistics of all experiments performed in three days of August at Fort A. P. Hill is shown in Fig. 4. It is seen from Fig. 4 that for 15 cases out of 34, the link up time is more than 95 percent, and for 20 cases out of 34, the link uptime meets the “at least 90 percent connectivity” criterion. Several of the cases of lower connectivity are instances of hardware and software crashes, and
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■ Figure 4. Summary of link uptime. do not meaningfully represent XG behavior. Also, as noted earlier, the radios may have gone out of range. This is very probable as the experimental terrain is hilly, and the XG vehicles did not strictly maintain low internode distances. Second, no channel may have been available for XG to use. This is also very probable because the experiments were performed with five other legacy radios in operation and provided a dense spectral environment for XG radios. This second reason is a demonstrable detail that is shown in the next section with further data analysis. Thus, the fact that XG connectivity exceeded 90 percent for 20 cases can be viewed as an important indicator of success, notwithstanding the outlier cases of lesser performance.
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XG ADDS VALUE: SUCCESS IN CHANNEL USE Success in channel use is defined as the percentage of time a channel is found when needed. If the number of XGs exceeds the number of channels in a small area, more XGs could contend for those channels, and success in channel use is reduced. Factors that limit this metric are: • No channel was available. • A channel was available, but the XG could not find it. • The link could not be closed because of propagation loss. We are able to separate some of these factors because the XG log files contain a history of what the detector observed and what the XG node did. Three mobile XG networks drove through the Fort A. P. Hill drop zone area and (scenario 1B) contended for a number of available channels. Spectrum occupancy was measured with XG sensors. The number of available channels varied from 0 (0 percent) to 6 (100 percent), as shown in Fig. 5. An available channel was defined to be simultaneously available for both the XG nodes in the net. Figure 5 shows that most of the route is either pink (67–100 percent or four to six channels remained busy) or green
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(34–67 percent or two to four channels remained busy) of the total six available channels. Therefore, the XGs did operate in a dense spectral environment and faced challenges of low channel availability. Figure 6 shows the success in spectrum use metric vs. the number of available channels (as determined by the XG sensor in each node). When the channels were available, XG was able to efficiently use the available channels 90 percent of the time for both experiment scenarios. In fact, as more channels became available, there was increased efficiency of channel use by XG. This clearly makes sense and encourages the hypothesis that channel unavailability was a more probable cause for the cases of link outages than undesirable XG behavior reported in Fig. 4 in the previous section.
XG ADDS VALUE: WHITE SPACE FILL FACTOR The white space fill factor represents the percentage of time that modem air time is actually available to a user’s XG modem to transmit (or receive) its data. XG reduces the air time because it uses a gap in transmit time for the detector to sense unused spectrum (referred to as look-through). The XG’s 802.16 WiMAX modem frame
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structure is TDMA, with the base station having a long downlink burst to a number of different subscribers, followed by a gap, followed by a number of different uplink bursts from the subscribers back to the base station, followed by another gap. The medium access control (MAC) layer efficiency is 100 percent – 26.3 percent = 73.7 percent. Thus, white space fill factor = link uptime percent • MAC efficiency percent = 0.95 • (1 – 0.263) = 70 percent. This metric clearly needs improvement. This is being mitigated in hardware design improvements, presently underway.
CONCLUSIONS The XG Fort A. P. Hill tests were one of the first if not the first large-scale field demonstration of dynamic spectrum access. All of the test goals were achieved. The small (500 ms) channel abandonment times and low INR values show that the XG system “causes no harm.” XG technology was proven to provide robust networking with excellent QoS in RF challenging mobile scenarios. The 5 s network join time, < 200 ms network re-establishment time, and lack of pre-assigned frequencies demonstrate that a dynamic spectrum access system can effectively network with multiple nodes (i.e., “it works”). The > 95 percent link uptime, 70 percent white space fill factor, and ~90 percent success in channel use metrics show that XG “adds value” to users. The metric needing improvement most is the 70 percent white space fill factor. This was caused by a large gap in the detection window required to accommodate hardware limitations related to timing. This is being mitigated in hardware design improvements.
ACKNOWLEDGMENTS The authors acknowledge financial support from DARPA for this project and technical input from Preston Marshall, DARPA Program Manager. The authors also acknowledge the support of the XG government team (Joint Spectrum Center, Air Force Rome Labs, Johns Hopkins University Applied Physics Laboratory, and Alion).
REFERENCES [1] M. McHenry, “Frequency Agile Spectrum Access Technologies,” Proc. FCC Wksp. Cognitive Radio, May 2003. [2] G. Staple and K. Werbach, “The End of Spectrum Scarcity,” IEEE Spectrum, vol. 41, no. 3, Mar. 2004, pp. 48–52. [3] S. Haykin, “Cognitive Radio: Brain-Empowered Wireless Communications,” IEEE JSAC, vol. 23, no. 2, Feb. 2005, pp. 201–20. [4] J. Mitola and, G. Q. Maguire, “Cognitive Radio: Making Software Radios More Personal,” IEEE Pers. Commun., vol. 6, no. 4, Aug. 1999, pp. 13–18. [5] T. K. Fong et al., “Radio Resource Allocation in Fixed Broadband Wireless Networks,” IEEE Trans. Commun., vol. 46, no. 6, 1998, pp. 806–18. [6] B. Wild and K. Ramchandran, “Detecting Primary Receivers for Cognitive Radio Applications,” Proc. IEEE DySPAN, Nov. 2005. [7] “The Next Generation Program,” http://www.darpa.mil/ sto/smallunitops/xg.html [8] A. E. Leu, M. McHenry, and B. L. Mark, “Modeling and Analysis of Listen-Before-Talk Spectrum Access Scheme,” Int’l. J. Network Mgmt., vol. 16, no. 2, Mar. 2006, pp. 131–47. [9] A. E. Leu et al., “Ultra Sensitive TV Detector Measurements,” Proc. IEEE DySPAN, Nov. 2005, pp. 30–36.
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■ Figure 6. Channel occupancy vs. channel availability in scenarios 1 and 2. [10] M. McHenry et al., “XG Dynamic Spectrum Sharing Field Test Results,” Proc. IEEE DySPAN, Apr. 2007. [11] F. W. Seelig, “A Description of the August 2006 DARPA XG Phase III Demonstrations at Ft. A. P. Hill,” Proc. IEEE DySPAN, Apr. 2007.
BIOGRAPHIES MARK A. MCHENRY (
[email protected]) has experience in military and commercial communication systems design, wireless networks, and high dynamic range multi-band transceivers. In 2000 he founded Shared Spectrum Company (SSC). Previously he was a program manager at DARPA. He was appointed by Secretary of Commerce Carlos Gutierrez to serve as a member of the Commerce Spectrum Advisory Committee in December 2006. He was named Engineer of the Year by the DC Council of Engineering and Architectural Societies in February 2006. He graduated with a B.S. in engineering and applied science from the California Institute of Technology in 1980, and received an M.S. in electrical engineering from the University of Colorado and a Ph.D. in electrical engineering from Stanford University. JEVGENIJS “EUGENE” L IVSICS (
[email protected]) received his M.S. degree from George Mason University, Fairfax, Virginia, in 2003. He studied electrical engineering at George Mason University and Riga Technical University from 1997 to 2003. He joined SSC as an engineer in 2003. As an active contributor to the DARPA XG project, he was deeply involved in the prototype development, field trials, and the following analysis. THAO NGUYEN (
[email protected]) received her B.S.E.E. and M.S.E.E. in 2004 and 2006 from George Mason University with honors, respectively. She is currently an engineer at SSC, where she has been working in the fields of wireless communication and radio frequency. Her specialties include system analysis, simulation, and data processing. N IVEDITA M AJUMDAR (
[email protected]) received a B.E. in computer engineering from Bengal Engineering College, India, in 2000 and an M.S. in mathematical sciences, summa cumma laude, from the University of Memphis, Tennessee, in 2002. She is currently working with SSC as a systems engineer. She is also pursuing a Ph.D. in computational science and informatics at George Mason University, Fairfax, Virginia, and expects to graduate in August 2007. Her interests are in signal analysis and data visualization.
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