Spectral estimation for long‐term evolution transceivers using low‐complex filter banks

Schlechter, Thomas; Juritsch, Christoph; Huemer, Mario

doi:10.1049/joe.2014.0102

Cited by 2 publications

(2 citation statements)

References 45 publications

(57 reference statements)

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“…The HDL designs use Xilinx specific components (DSP and blocks), which are identical in all Xilinx 7 series FPGAs 4 . Hence, the designs can be moved between different Xilinx chips without modifying the code.…”

Section: Scalability and Portabilitymentioning

confidence: 99%

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FPGA Realization of the Observer-Based Sliding Discrete Fourier Transform

2022

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Discrete Fourier transform (DFT) is a widely used method of signal analysis in digital signal processing. The DFT converts a signal from time domain to frequency domain for further processing. For fixed-size sliding window applications of the DFT, the observer-based sliding DFT (oSDFT) algorithm has been shown to be stable, accurate, and theoretically faster, than the well-known block-oriented fast Fourier transforms (FFT). However, no hardware implementation of the oSDFT has been proposed yet. In this paper, a hardware optimized implementation of two variants of the algorithm for FPGA is presented. Such implementation is compared with the Xilinx FFT Intellectual Property in terms of processing speed and hardware requirements. The structure is implemented in Verilog HDL using Vivado IDE, with the aim of maximizing the processing speed and minimizing the required hardware resources. The analysis of the FPGA-based oSDFT and FFT circuits in a sample-by-sample processing scenario, reveals, that the latency and energy usage of the oSDFT are smaller relative to the FFT. The latency and energy usage per sample processed of the implemented structures are up to 9 and 10 times lower than those of FFT respectively. The required resources for these methods are also presented and analyzed.

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Section: Scalability and Portabilitymentioning

confidence: 99%

“…For synchronization purposes, such an application was given in [3]. Methods for spectrum VOLUME 4, 2016 estimation and spectrum sensing in wireless communication systems were reported in [4], [5]. Furthermore, a method for decoding data transmission using SDFT was presented in [6].…”

Section: Introductionmentioning

confidence: 99%