Is this project an undergraduate, graduate, or faculty project?
Faculty
Project Type
group
Campus
Daytona Beach
Authors' Class Standing
Levi Lingsch, Senior
Lead Presenter's Name
Sirani M. Perera
Faculty Mentor Name
Sirani M. Perera
Abstract
Digital beamformers are popular due to the extensive usage in digital signal processing, including applications in radar, cellular networks, microwave imaging, and radio astronomy. When digital beamformers are considered, characteristics of the analog to digital converters e.g., dynamic range and instantaneous bandwidth, and the number of complex operations performed are of paramount importance in wireless communications. In here, we observe a hybrid of discrete transform matrices as the beam digitization transform matrix and present its sparse factorization. Next, the proposed factorization will be utilized to derive a fast algorithm while reducing the arithmetic complexity. Finally, the language of signal flow graphs will be utilized to connect the algebraic operations associated with the proposed algorithm to realize the system as an integrated circuit.
This work is supported by the Faculty Innovative Research in Science and Technology, ERAU, Grant 13221.
Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?
No
A Fast Discrete Transform for Beam Digitization
Digital beamformers are popular due to the extensive usage in digital signal processing, including applications in radar, cellular networks, microwave imaging, and radio astronomy. When digital beamformers are considered, characteristics of the analog to digital converters e.g., dynamic range and instantaneous bandwidth, and the number of complex operations performed are of paramount importance in wireless communications. In here, we observe a hybrid of discrete transform matrices as the beam digitization transform matrix and present its sparse factorization. Next, the proposed factorization will be utilized to derive a fast algorithm while reducing the arithmetic complexity. Finally, the language of signal flow graphs will be utilized to connect the algebraic operations associated with the proposed algorithm to realize the system as an integrated circuit.
This work is supported by the Faculty Innovative Research in Science and Technology, ERAU, Grant 13221.