Boston C. Terry
Neal Patwari
ABSTRACT
Current software-defined radio systems enable transmission at nearly arbitrary frequencies, presenting the possibility of harmful interference to existing communication services when broadcasting over-the-air. The Platform for Open Wireless Data-driven Experimental Research (POWDER) provides software radios whose output can be amplified and transmitted over-the-air. POWDER must include a spectrum monitoring system that can identify users who are transmitting outside allowed frequency bands to ensure wireless spectrum license holders do not experience harmful interference.
Power amplifiers in the transmit signal path can create emissions at center frequency harmonics and other spurious emissions. A spectrum monitoring system, coupled with signal paths after all amplifiers in the transmit chain, can detect these emissions. However, incident radio frequency energy combines with the output signal, which is no longer buffered by the amplifier. Incident and transmitted signals must be separated and isolated. The monitor can then analyze the isolated transmitted signal for out-of-band energy. This paper presents a system that can achieve isolation and identify users that broadcast out-of-band.
- J. Breen, E. Eide, E. Lewis, D. Reading, A. Buffmire, M. Hibler, D. Maas, R. Ricci, J. Duerig, D. Johnson, A. Orange, D. Schurig, K. Dutt, S. K. Kasera, N. Patwari, L. B. Stoller, J. Van der Merwe, K. Webb, and G. Wong. Powder: Platform for Open Wireless Data-driven Experimental Research. In ACM WiNTECH proceedings, September 2020.Google Scholar
- J.-T. Chien. Source Separation and Machine Learning. Academic Press, 2018.Google Scholar
- M. Cotton, J. Wepman, J. Kub, S. Engelking, Y. Lo, H. Ottke, R. Kaiser, and D. Anderson. An Overview of the NTIA / NIST Spectrum Monitoring Pilot Program. 2015.Google ScholarCross Ref
- M. Ettus and M. Braun. The universal software radio peripheral (usrp) family of low-cost sdrs. Opportunistic Spectrum Sharing and White Space Access: The Practical Reality, pages 3--23, 2015.Google ScholarCross Ref
- Y. Guddeti, U. C. S. Diego, R. Subbaraman, I. I. T. Madras, M. Khazraee, A. Schulman, D. Bharadia, U. C. S. Diego, and I. Nsdi. SweepSense: Sensing 5 GHz in 5 Milliseconds with Low-cost Radios This paper is included in the Proceedings of the. Proc. of NSDI, 2019.Google Scholar
- A. Hyvarinen, J. Karhunen, and E. Oja. Independent component analysis and blind source separation, 2001.Google ScholarCross Ref
- A. Milewski. Periodic sequences with optimal properties for channel estimation and fast start-up equalization. IBM Journal of Research and Development, 27(5):426--431, 1983.Google ScholarDigital Library
Index Terms
- Spectrum Monitoring and Source Separation in POWDER
Recommendations
Spectrum borrowing balancing-based spectrum management in cognitive radio
In Cognitive radio (CR) systems, the spectrum management of spectrum sensing and sharing for secondary users (SUs) affects the performance of secondary users and primary user. In this paper, we develop a spectrum sensing model for SUs who belong to ...
Proactive detection of spectrum opportunities in primary systems with power control
Spectrum sensing finds spectrum opportunities for cognitive radio (CR) and enables CR users to work without harmful interference to primary users. Most of existing contributions on spectrum sensing detect whether a primary signal is present or absent. ...
Spectrum sensing in cognitive radio networks: the cooperation-processing tradeoff
Cognitive Radio, Software Defined Radio And Adaptive Wireless SystemsOpportunistic unlicensed access to the (temporarily) unused frequency bands across the licensed radio spectrum is currently being investigated as a means to mitigate the spectrum scarcity. Such opportunistic access calls for the implementation of ...
Comments