Conference proceeding
Greedy Channel Selection for Dynamic Spectrum Access Radios
2020 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), pp 1-4
01 Jan 2020
Abstract
Dynamic Spectrum Access (DSA) radios typically select their radio channels according to their data networking goals, a defined DSA spectrum operating policy, and the state of the RF spectrum. RF spectrum sensing can be used to collect information about the state of the RF spectrum and prioritize which channels should be assigned for DSA radio waveform transmission and reception. This paper describes a Greedy Channel Ranking Algorithm (GCRA) used to calculate and rank RF interference metrics for observed DSA radio channels. The channel rankings can then be used to select and/or avoid channels in order to attain a desired DSA radio performance level. Experimental measurements are collected using our custom software-defined radio (SDR) system to quantify the performance of using GCRA for a DSA radio application. Analysis of these results show that both pre and post-detection average interference power metrics are the most accurate metrics for selecting groups of radio channels to solve constrained channel assignment problems in occupied gray space spectrum.
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Details
- Title
- Greedy Channel Selection for Dynamic Spectrum Access Radios
- Creators
- Alex Lackpour - Philadelphia UniversityXaime Rivas Rey - Philadelphia UniversityGeoffrey Mainland - Drexel UniversityKapil R. Dandekar - Philadelphia UniversityIEEE
- Publication Details
- 2020 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), pp 1-4
- Series
- IEEE International Symposium on Circuits and Systems
- Publisher
- IEEE
- Number of pages
- 4
- Grant note
- CNS-1730140; CCF-1717088 / National Science Foundation; National Science Foundation (NSF)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Electrical and Computer Engineering; Computer Science
- Web of Science ID
- WOS:000706854700065
- Other Identifier
- 991019170511904721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Engineering, Electrical & Electronic