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Scalable Dynamic Spectrum Access with IEEE 1900.5.2 Spectrum Consumption Models
  • +3
  • Prasad Netalkar,
  • Carlos E Caicedo Bastidas,
  • Igor Kadota,
  • Gil Zussman,
  • Ivan Seskar,
  • Dipankar Raychaudhuri
Prasad Netalkar
WINLAB, Rutgers University

Corresponding Author:[email protected]

Author Profile
Carlos E Caicedo Bastidas
School of Information Studies, Syracuse University
Igor Kadota
Department of Electrical Engi-neering, Columbia University
Gil Zussman
Department of Electrical Engi-neering, Columbia University
Ivan Seskar
WINLAB, Rutgers University
Dipankar Raychaudhuri
WINLAB, Rutgers University

Abstract

Dynamic Spectrum Access (DSA) is a key mechanism for meeting the ever-increasing demand for emerging wireless services. DSA involves managing and assigning available spectrum resources in a way that minimizes interference and allows RF coexistence between heterogeneous devices and systems. Spectrum Consumption Models (SCMs)-defined in the IEEE 1900.5.2 standard, offer a mechanism for RF devices to: (i) declare the characteristics of their intended spectrum use and their interference protection needs; and (ii) determine compatibility (non-interference) with existing devices. In this paper, we propose a novel SCM-based Spectrum Deconfliction (SD) algorithm that dynamically configures RF operational parameters (e.g., center frequency and transmission power) of a target transmitter-receiver pair aiming to minimize interference with existing devices/systems. We also propose sequential and distributed DSA methods that use the SD algorithm for assigning spectrum in large-scale networks. To evaluate the performance of our methods in terms of computation time, spectrum assignment efficiency, and overhead, we use two custom-made simulation platforms. Finally, to experimentally demonstrate the feasibility of our methods, we build a proof-of-concept implementation in the NSF PAWR COSMOS wireless testbed. The results reveal the advantages of using SCMs and their capabilities to conduct spectrum assignments in dynamic and congested communication environments.
02 Apr 2024Submitted to TechRxiv
03 Apr 2024Published in TechRxiv