Results 21 to 30 of about 86 (72)
A Deep Learning‐Aided Detection Method for FTN‐Based NOMA
Wireless Communications and Mobile Computing, Volume 2020, Issue 1, 2020., 2020 The rapid booming of future smart city applications and Internet of things (IoT) has raised higher demands on the next‐generation radio access technologies with respect to connection density, spectral efficiency (SE), transmission accuracy, and detection latency.
Jianxiong Pan +4 more
wiley +1 more source
IEEE Access, 2017 This paper deals with low-complexity joint channel estimation and decoding for faster-than-Nyquist (FTN) signaling over frequency selective fading channels.
Nan Wu +3 more
doaj +1 more source
IEEE Access, 2020 This study measured the achievable performance of the recently developed precoded faster-than-Nyquist (FTN) signaling scheme with truncated power allocation from an information-theoretic perspective.
Keita Masaki +2 more
doaj +1 more source
Low Complexity Message Passing Receiver for Faster-Than-Nyquist Signaling in Nonlinear Channels
IEEE Access, 2018 The modern and future communication systems demand higher data rate exceeds current capabilities. Faster-than-Nyquist (FTN) signaling is a promising technique for the reason it can improve the spectral efficiency.
Xiaojie Wen +4 more
doaj +1 more source
Faster-than-Nyquist signaling: value and challenges of 6G-oriented applications
Dianxin kexue, 2021 The faster-than-Nyquist (FTN) signaling technology overlaps multiple streams of data within a symbol period by compressing the transmit symbol time/frequency-domain interval, thus breaking the orthogonality of the Nyquist pulse waveform and achieving the
Xin SU +4 more
doaj +2 more sources
FTN Signal Carrier Synchronization Based on DFT and Quadratic Polynomial Fitting [PDF]
Jisuanji gongcheng, 2018 Faster-than-Nyquist(FTN) signaling,which is promising in 5G mobile communication,has higher information rate and spectrum efficiency.However,symbol interval’s compression resulted in infinite Inter-Symbol Interferences (ISI),which would deteriorate the ...
CHENG Peng,LIU Aijun,LIANG Xiaohu,WANG Ke,CAI Biao
doaj +1 more source
Receiver Design for Faster-Than-Nyquist Signaling: Deep-Learning-Based Architectures
IEEE Access, 2020 Faster-than-Nyquist (FTN) is a promising paradigm to improve bandwidth utilization at the expense of additional intersymbol interference (ISI). In this paper, we apply state-of-the-art deep learning (DL) technology into receiver design for FTN signaling ...
Peiyang Song +4 more
doaj +1 more source
Differential Faster-Than-Nyquist Signaling
IEEE Access, 2018 In this paper, we propose a novel differential faster-than-Nyquist (DFTN) signaling concept that allows us to dispense with any channel estimation at the receiver, while benefiting from a rate boost specific to faster-than-Nyquist (FTN) signaling.
Takumi Ishihara, Shinya Sugiura
doaj +1 more source
Advanced Functional Materials, Volume 29, Issue 51, December 19, 2019., 2019 Cyanographene (G‐CN), a densely functionalized but conductive graphene derivative, bypasses the need for aqueous electrolytes and for high areal‐mass current collectors, and also overcomes previous synthetic limitations toward seamless organic/inorganic hybrids for supercapacitors.
Smita V. Talande +5 more
wiley +1 more source
Superposition Coded Modulation Based Faster‐Than‐Nyquist Signaling
Wireless Communications and Mobile Computing, Volume 2018, Issue 1, 2018., 2018 A structure of faster‐than‐Nyquist (FTN) signaling combined with superposition coded modulation (SCM) is considered. The so‐called FTN‐SCM structure is able to achieve the constrained capacity of FTN signaling and only requires a low detection complexity. By deriving a new observation model suitable for FTN‐SCM, we offer the power allocation based on a
Shuangyang Li +5 more
wiley +1 more source