Generalized Frequency Division Multiplexing: A Flexible Multicarrier Waveform

Nimr, Ahmad; Ehsanfar, Shahab; Michailow, Nicola; Danneberg, Martin; Zhang, Dan; Rodrigues, Henry Douglas; Mendes, Luciano Leonel; Fettweis, Gerhard

doi:10.1007/978-3-319-92090-0_4

Cited by 5 publications

(2 citation statements)

References 37 publications

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“…The next-generation advanced communication techniques face different challenges when used in new applications. Nimr et al [ 16 ] demonstrated that the OFDM scheme has difficulty fulfilling demanding requirements. Synchronization, channel estimation algorithms and MIMO techniques for GFDM were demonstrated in detail, and were found to be a suitable transmission method for advanced communication technologies of the future.…”

Section: Introductionmentioning

confidence: 99%

Generalized Frequency Division Multiplexing-Based Low-Power Underwater Acoustic Image Transceiver

Lin

Hsieh

et al. 2021

Sensors

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In this paper, a low-power underwater acoustic (UWA) image transceiver based on generalized frequency division multiplexing (GFDM) modulation for underwater communication is proposed. The proposed transceiver integrates a low-density parity-check code error protection scheme, adaptive 4-quadrature amplitude modulation (QAM) and 16-QAM strategies, GFDM modulation, and a power assignment mechanism in an UWA image communication environment. The transmission bit error rates (BERs), the peak signal-to-noise ratios (PSNRs) of the received underwater images, and the power-saving ratio (PSR) of the proposed transceiver obtained using 4-QAM and 16-QAM, with perfect channel estimation, and channel estimation errors (CEEs) of 5%, 10%, and 20% were simulated. The PSNR of the received underwater image is 44.46 dB when using 4-QAM with a CEE of 10%. In contrast, PSNR is 48.79 dB when using 16-QAM with a CEE of 10%. When BER is 10−4, the received UW images have high PSNR values and high resolutions, indicating that the proposed transceiver is suitable for underwater image sensor signal transmission.

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Section: Introductionmentioning

confidence: 99%

Generalized Frequency Division Multiplexing-Based Low-Power Underwater Acoustic Image Transceiver

Lin

Hsieh

et al. 2021

Sensors

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“…Another feature of GFDM is the tail biting cyclic prefix (CP). This feature makes GFDM suitable in cyclostationary spectrum sensing algorithms [8]- [10].…”

Section: Introductionmentioning

confidence: 99%

Sub-Nyquist Cyclostationary Detection of GFDM for Wideband Spectrum Sensing

2019

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Spectrum scarcity is a challenging problem in wireless communications: high data rates are needed to support 5G new technologies. However, the spectrum is underutilized. To address this problem, cognitive radio (CR) is proposed to exploit the underutilized spectrum. The main requirement for the future CR networks is wideband spectrum sensing, which provides secondary users with the available frequency bands across a wide frequency range. Secondary users should fill these bands without causing interference to licensed users. Thus, new waveforms are proposed for the 5G physical layer. Generalized frequency division multiplexing (GFDM) is considered to be a contender for the 5G new physical layer. The GFDM is a block-based waveform that is suitable for fragmented spectrum scenarios and is designed to overcome the drawbacks of orthogonal frequency-division multiplexing (OFDM) used in 4G. The GFDM is the perfect candidate for 5G and CR technologies. Considering the cyclostationarity properties of modulated signals, we propose an optimized recovery method for the GFDM signals in the wideband regime. By exploiting the signal sparsity, we can recover the spectral correlation function (SCF) of the GFDM from digital samples of the GFDM taken at a sub-Nyquist rate to reduce the sampling time. Furthermore, a generalized likelihood ratio test is applied to the recovered function to detect multiple signal sources and identify the spectrum occupancy. The numerical results show that our method achieves a high probability of detection at a low signal-to-noise ratio (SNR) with robustness in terms of rate reduction in wireless networks. INDEX TERMS Cognitive radio, compressive sampling, cyclostationarity, generalized frequency division multiplexing (GFDM), wideband spectrum sensing.

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