skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


  • NSF Public Access
  • Search Results
  • Design of Multichannel Spectrum Intelligence Systems Using Approximate Discrete Fourier Transform Algorithm for Antenna Array-Based Spectrum Perception Applications
Title: Design of Multichannel Spectrum Intelligence Systems Using Approximate Discrete Fourier Transform Algorithm for Antenna Array-Based Spectrum Perception Applications
The radio spectrum is a scarce and extremely valuable resource that demands careful real-time monitoring and dynamic resource allocation. Dynamic spectrum access (DSA) is a new paradigm for managing the radio spectrum, which requires AI/ML-driven algorithms for optimum performance under rapidly changing channel conditions and possible cyber-attacks in the electromagnetic domain. Fast sensing across multiple directions using array processors, with subsequent AI/ML-based algorithms for the sensing and perception of waveforms that are measured from the environment is critical for providing decision support in DSA. As part of directional and wideband spectrum perception, the ability to finely channelize wideband inputs using efficient Fourier analysis is much needed. However, a fine-grain fast Fourier transform (FFT) across a large number of directions is computationally intensive and leads to a high chip area and power consumption. We address this issue by exploiting the recently proposed approximate discrete Fourier transform (ADFT), which has its own sparse factorization for real-time implementation at a low complexity and power consumption. The ADFT is used to create a wideband multibeam RF digital beamformer and temporal spectrum-based attention unit that monitors 32 discrete directions across 32 sub-bands in real-time using a multiplierless algorithm with low computational complexity. The output of this spectral attention unit is applied as a decision variable to an intelligent receiver that adapts its center frequency and frequency resolution via FFT channelizers that are custom-built for real-time monitoring at high resolution. This two-step process allows the fine-gain FFT to be applied only to directions and bands of interest as determined by the ADFT-based low-complexity 2D spacetime attention unit. The fine-grain FFT provides a spectral signature that can find future use cases in neural network engines for achieving modulation recognition, IoT device identification, and RFI identification. Beamforming and spectral channelization algorithms, a digital computer architecture, and early prototypes using a 32-element fully digital multichannel receiver and field programmable gate array (FPGA)-based high-speed software-defined radio (SDR) are presented.  more » « less
Award ID(s):
2329012 2229471
PAR ID:
10541273
Author(s) / Creator(s):
; ; ; ; ; ;
Publisher / Repository:
MDPI
Date Published:
Journal Name:
Algorithms
Volume:
17
Issue:
8
ISSN:
1999-4893
Page Range / eLocation ID:
338
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ; (, CS&IT)
    Wyld, David C; Nagamalai, Dhinaharan (Ed.)
    The proliferation of 5G technologies and the vast deployment of Internet of Things (IoT) devices have heightened the demand for optimal spectrum utilization, necessitating robust spectrum management strategies. In this context, an efficient energy detector employing wideband spectrum sensing within a 5G environment is essential for identifying underutilized frequency bands suitable for cognitive radio applications across multiple subbands. While cooperative spectrum sensing (CSS) can enhance the detection capabilities of energy detectors amidst noise uncertainty, its performance often deteriorates under low signal-to-noise ratio (SNR) conditions. This study proposes an improved CSS framework that combines Maximal Ratio Combining (MRC) with the K-out-of-N fusion rule to address noise uncertainty in a complex Gaussian environment across multiple sub-bands in cooperative wideband spectrum sensing. Comparative performance analysis confirms that this integrated approach enhances detection probability and maintains a low false alarm rate across various low SNR scenarios, significantly outperforming traditional cooperative and non-cooperative wideband spectrum sensing methods. These results highlight the potential for advancing cognitive radio technologies by optimizing detection algorithms to improve performance under challenging conditions. 
    more » « less
  2. ; ; ; (, in WiOpt 2025 Workshop on Resource Allocation and Cooperation in Wireless Networks (RAWNET), 2025.)
    The management of RF spectrum resources between heterogeneous RF devices has become more challenging with the advent of 5G, 6G and the desire to enable more spectrum sharing interactions in different bands. Most of the research on Dynamic Spectrum Access (DSA) algorithms considers non-cooperative scenarios with RF devices using omnidirectional antennas. In this paper, we study the effects of antenna directionality on cooperative DSA. Specifically, we develop a custom simulator for large-scale DSA networks that leverages IEEE 1900.5.2 Spectrum Consumption Models (SCMs) to enable coordination and computation of aggregate interference to deconflict spectrum use in large scale scenarios. SCMs offer a mechanism for RF devices to describe the characteristics of their use of spectrum and their needs in terms of interference protection. We create SCMs for RF systems with directional antennas based on measurements from a directional mmWave antenna and from the operational characteristics defined by the European Telecommunications Standards Institute (ETSI). We leverage these SCMs to perform a comparative analysis of spectrum use efficiency in cooperative DSA networks with up-to 300 links of transmitter-receiver RF devices using omnidirectional antennas vs similar networks using directional antennas with different half-power beam widths. The simulation results show the benefits to spectrum use efficiency that can be achieved with directional antennas and how largescale DSA methods can be studied and designed with the use of SCMs that incorporate detailed characteristics of directional antennas. 
    more » « less
  3. ; ; ; ; ; ; (, Telecommunications policy)
    Bohlin, E (Ed.)
    Future G networks will require more dynamic, agile support for the management of radio spectrum on a fine-grained basis. The radio access network (RAN) technologies necessary to enable Dynamic Spectrum Access (DSA) have progressed significantly over the past 20 years, but the challenges of realizing the potential for DSA requires the co-evolution of technologies, business models, and regulatory policy. This paper presents a multidisciplinary research effort to develop the building blocks needed to advance DSA. In particular, we focus on the use of standards-based Spectrum Consumption Models (SCMs) and review on-going research to incorporate SCMs in an automated management framework based on incentive-compatible, technically-sound spectrum access contracts referred to as Spectrum Access Agreements (SAAs). This paper introduces the core concepts of the SCM/SAA framework, project goals, and preliminary insights into how the framework can help improve spectrum management. The research on SCM/SAA represents a bottom-up effort to develop the techno-economic building blocks or tools to facilitate marketbased experimentation and development of DSA based spectrum sharing markets, business models, and applications. 
    more » « less
  4. ; ; ; (, 2020 IEEE International Symposium on Circuits and Systems)
    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. 
    more » « less
  5. ; ; ; ; ; ; (, SSRN)
    Future G networks will require more dynamic, agile support for the management of radio frequency spectrum on a fine-grained basis. The radio access network (RAN) technologies necessary to enable Dynamic Spectrum Access (DSA) have progressed significantly over the past 20 years, but the challenges of realizing the potential for DSA requires the co-evolution of the technologies, business models/market structures, and regulatory policy for wireless networks. This paper discusses a bottom-up, multi-disciplinary approach to DSA. In particular, we focus on the use of standards-based Spectrum Consumption Models (SCMs), and review on-going research to incorporate SCMs in an automated management framework based on incentive-compatible, technically-sound spectrum access contracts, or Spectrum Access Agreements (SAAs). This work is being undertaken as part of the NSF National Radio Dynamic Zone (NRDZ) research initiative and this paper provides an introduction to the core concepts of the SCM/SAA framework, project goals, and preliminary insights into how the SCM/SAA can help improve spectrum management and advance R&D efforts to enable the transition to a shared spectrum future. The SCM/SAA research represents a bottom-up effort to develop the techno-economic tools to facilitate market-based experimentation and development of spectrum sharing markets, business models, and applications to complement and render more economically viable and relevant emerging DSA technologies and top-down regulatory reforms aimed at lowering spectrum sharing barriers. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email