No Arabic abstract
The fifth generation (5G) wireless standard will support several new use cases and 10 to 100 times the performance of fourth generation (4G) systems. Because of the diverse applications for 5G, flexible solutions which can address conflicting requirements will be needed. In this paper, we propose a solution which enables the use of discrete Fourier transform spread orthogonal frequency division multiplexing (DFT-s-OFDM) and OFDM, which address different requirements, using a common reference symbol (RS) design. In this solution, the DFT-s-OFDM symbol contains RSs in the frequency domain that may be shared by a subsequent OFDM symbol. The proposed scheme is generated by puncturing the output of a DFT-spread block and replacing the punctured samples with RSs in frequency. We prove that puncturing the interleaved samples at the output of the DFT-spread operation equivalently introduces a periodic interference to the data symbols at the input of the DFT-spread operation. We show that the interference due to the puncturing can be removed with a low-complexity receiver by exploiting the zeros inserted to certain locations before the DFT-spread block at the transmitter. Simulation results support that the proposed scheme removes the error floor caused by the puncturing and achieves lower peak-to-average-power ratio than OFDM.
In this study, we propose a framework for chirp-based communications by exploiting discrete Fourier transform-spread orthogonal frequency division multiplexing (DFT-s-OFDM). We show that a well-designed frequency-domain spectral shaping (FDSS) filter for DFT-s-OFDM can convert its single-carrier nature to a linear combination of chirps circularly translated in the time domain. Also, by exploiting the properties of the Fourier series and Bessel function of the first kind, we analytically obtain the FDSS filter for an arbitrary chirp. We theoretically show that the chirps with low ripples in the frequency domain result in a lower bit-error ratio (BER) via less noise enhancement. We also address the noise enhancement by exploiting the repetitions in the frequency. The proposed framework offers a new way to efficiently synthesize chirps that can be used in Internet-of-Things (IoT), dual-function radar and communication (DFRC) or wireless sensing applications with existing DFT-s-OFDM transceivers.
This paper proposes a novel maximum Doppler spread estimation algorithm for OFDM systems with the comb-type pilot pattern. By tracking the drifting delay subspace of the multipath channel, the time correlation function is measured at a high accuracy, which accordingly improves the estimation accuracy of the maximum Doppler spread considerably.
In this paper, we study how to efficiently and reliably detect active devices and estimate their channels in a multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) based grant-free non-orthogonal multiple access (NOMA) system to enable massive machine-type communications (mMTC). First, by exploiting the correlation of the channel frequency responses in narrow-band mMTC, we propose a block-wise linear channel model. Specifically, the continuous OFDM subcarriers in the narrow-band are divided into several sub-blocks and a linear function with only two variables (mean and slope) is used to approximate the frequency-selective channel in each sub-block. This significantly reduces the number of variables to be determined in channel estimation and the sub-block number can be adjusted to reliably compensate the channel frequency-selectivity. Second, we formulate the joint active device detection and channel estimation in the block-wise linear system as a Bayesian inference problem. By exploiting the block-sparsity of the channel matrix, we develop an efficient turbo message passing (Turbo-MP) algorithm to resolve the Bayesian inference problem with near-linear complexity. We further incorporate machine learning approaches into Turbo-MP to learn unknown prior parameters. Numerical results demonstrate the superior performance of the proposed algorithm over state-of-the-art algorithms.
For DFT-spread-OFDM or OFDM, if the delay spread varies in a wide range and the symbol duration is relatively short, adapting the cyclic prefix (CP) duration rather than using a fixed one may significantly improve the spectral efficiency while preventing inter-symbol interference (ISI). In practice, it may be beneficial to have a constant overall DFT-spread-OFDM/OFDM symbol time, which is the sum of the duration of a CP and the duration of a data portion. We propose to adapt the CP duration to the delay spread without changing the overall symbol time for DFT-spread-OFDM or OFDM, and address implementation challenges. In particular, we propose changing the clocking rate of ADC and DAC or using a Farrow filter to reduce the computational complexity of arbitrary-size DFT/IDFT resulting from the adaptation.
In this study, we compare the single-carrier (SC) waveform adopted in IEEE 802.11ad and unique word discrete Fourier transform spread orthogonal frequency division multiplexing (UW DFT-s-OFDM) waveform. We provide equivalent representations of up-sampling and down-sampling operations of the SC waveform by using discrete Fourier transform (DFT) and inverse DFT to enable explicit comparison of these two similar waveforms. By using this representation, we discuss why the IEEE 802.11ad SC waveform can cause suboptimal performance in multipath channel and discuss how to improve it with UW DFT-s-OFDM. With comprehensive link-level simulations, we show that replacing the 802.11ad SC waveform with UW DFT-spread OFDM can result in 1 dB gain in peak throughput without affecting the IEEE 802.11ad packet structure. We also evaluate the cross links where the transmitter is UW-DFT-s-OFDM and the receiver is traditional SC-FDE or vice versa. We demonstrate that UW DFT-s-OFDM receiver can decode an IEEE 802.11ad SC waveform with a slight SNR loss while IEEE 802.11ad SC receiver can decode a UW DFT-spread OFDM waveform with an interference floor.