Non-Intrusive Wireless Networks for Opportunistic Spectrum Utilization

1. Research and Test of Non-Intrusive Wireless Networks for Opportunistic Spectrum Utilization Univeristy Of California Davis PI: Zhi Ding (ECE) and Xin Liu (CS) Subaward: I-Jeng Wang, APL, Johns Hopkins Univ 2006@UCLA NSF NeTS Workshop

2. Project Goals and Scope • Investigating opportunistic access networks that can provide secondary service and are • spectrally-agile • non-instrusive to primary or legacy networks • low cost and broadly applicable • Collaborating with APL (JHU) to measure spectral activity of key target areas of the secondary network

3. ESCAPE: Embedded SpeCtrally Agile radio Protocol for Evacuation • Problem: • One or more users in a group may detect the return of primaries • To disseminate such information fast and reliably • Interference from primary transmission • Interference from regular secondary transmission • No simultaneous transmission and reception • In-band signaling • ESCAPE: • PHY: predefined evacuation message using a given spreading code • MAC: transmit as soon as the warning message is received • Routing: flooding • Performance metrics • Evacuation time, success probability, peak and average interference during evacuation, false-alarm rate • Design parameters • Spreading code length, power, number of repetition for a given objective • X. Liu, Z, Ding, Embedded SpeCtrally Agile radio Protocol for Evacuation, under submission.

4. Sensing-based Opportunistic Channel Access • To collaboratively detect whether a channel is idle and is a good opportunity • Is the channel “idle”? • Three proposed algorithms to make sensing decision so that the outage probability is below a certain threshold • Observation: collaborative sensing is very helpful • To do: more robust fading model and measurements with spatial correlation • Is the channel a good one; i.e., to finish a transmission? • An algorithm based on channel sensing statistics. • X. Liu and S. Shankar, “Sensing-based opportunistic channel access”, ACM MONET, vol. 11, no. 4, August, 2006.

5. Data Collection at JHU/APL • Public safety band at Howard County, MD • Two measurements suites, set at 5, 200, 600 meters apart • Forward and reverse channels • Objective: temporal and spatial correlation • System setup: • The spectral data are sampled with 14 bits at 64 MS/s. • The samples are collected in snapshots of 16384 each, covering ~20 MHz every 100 ms. • This snapshot size allows for DFT bins of ~ 3.9 kHz, which is enough resolution to discriminate between adjacent forward or reverse channels as their centers are never closer than 25 kHz.

6. 5 meters apartfixed – site 1 mobile – site 1

7. 10 dB thresholdfixed – site 1 mobile – site 1

8. Side-by-side – distance = 5 metersfixed - site 1 mobile - site 1

9. Current and Future Research Emphasis • Integrative studies of physical layer, MAC layer, and network layer • Performance evaluation and model validation. • Data collection, analysis, and public distribution • Feasibility and capacity analysis of 2ndary network interacting with both non-interactive and interactive primary systems • Compatibility with CSMA-based primary users • Quantification of capacity and interference tradeoff

10. Links to other projects • Xin Liu (University of California, Davis) CAREER: Smart-Radio-Technology-Enabled Opportunistic Spectrum Utilization • Dirk Grunwald, Doug Sicker, John Black (University of Colorado), NeTS-ProWIN: Topology And Routing With Steerable Antennas • Uf Turelli, Kevin Ryan (Stevens Institute of Tech), Milind M. Buddhikot, Scott Miller (Lucent Bell Lab), Dynamic Intelligent Management of Spectrum for Ubiquitous Mobile Network (DIMSUMnet) • Kang G. Shin, University of Michigan, Efficient Wireless Spectrum Utilization with Adaptive Sensing and Spectral Agility • Qing Zhao, UC Davis, An Integrated Approach to Opportunistic Spectrum Access • Randall Berry, Michael Honig and Rakesh Vohra, Northwestern University, Smart Markets for Smart Radios • Mario Gerla, Stefano Soatto, Michael Fitz, Giovanni Pau, UCLA, Emergency Ad Hoc Networking Using Programmable Radios and Intelligent Swarms • Saswati Sarkar, University of Pennsylvania, Dynamic Spectrum MAC with Multiparty Support in Adhoc Networks • Marwan Krunz, Shuguang Cui, University of Arizona Resource Management and Distributed Protocols for Heterogeneous Cognitive-Radio Networks • Dennis Roberson, Cindy Hood, Joe LoCicero, Don Ucci (Illionis Institute of Technology), Uf Tureli (Stevens Institute of Technology) Wireless Interference and Characterization on Network Performance • Narayan Mandayam, Christopher Rose, Predrag Spasojevic, Roy Yates, WINLAB Rutgers University, Cognitive Radios for Open Access to Spectrum

11. Links to other projects • Platform/Testbed projects • Dirk Grunwald (U. Colorado), John Chapin (Vanu, Inc), Joe Carey (Fidelity Comtech) A Programmable Wireless Platform For Spectral, Temporal and Spatial Spectrum Management • Jeffrey H. Reed, William H. Tranter, and R. Michael Buehrer, Virginia Tech, An Open Systems Approach for Rapid Prototyping Waveforms for Software Defined Radio • D. Raychaudhuri (WINLAB, Rutgers University) ORBIT: Open Access Research Testbed for Next-Generation Wireless Networks • B. Ackland, I. Seskar & D. Raychaudhuri, (WINLAB, Rutgers University), T. Sizer (Lucent Technologies), J. Laskar(GA Tech) High Performance Cognitive Radio Platform with Integrated Physical and Network Layer Capabilities • Babak Daneshrad, University of California, Los Angeles, Programmable/Versatile Radio Platforms for the Networking Research Community • Prasant Mohapatra, University of California, Davis, Quail Ridge Wireless Mesh Networks: A Wide Area Test-bed