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The detection of all the symbols transmitted simultaneously in multiuser systems using limited wireless resources is challenging. Traditional model‐based methods show high performance with perfect channel state information (CSI); however, severe performance degradation will occur if perfect CSI cannot be acquired. In contrast, data‐driven methods perform slightly worse than model‐based methods in terms of symbol error ratio performance in perfect CSI states; however, they are also able to overcome extreme performance degradation in imperfect CSI states. This study proposes a novel deep learning‐based method by improving a state‐of‐the‐art data‐driven technique called deep soft interference cancellation (DSIC). The enhanced DSIC (EDSIC) method detects multiuser symbols in a fully sequential manner and uses an efficient neural network structure to ensure high performance. Additionally, error‐propagation mitigation techniques are used to ensure robustness against channel uncertainty. The EDSIC guarantees a performance that is very close to the optimal performance of the existing model‐based methods in perfect CSI environments and the best performance in imperfect CSI environments. [ABSTRACT FROM AUTHOR]

HfO2-based ferroelectric tunnel junctions (FTJs) are promising nonvolatile memory types for neural network applications because of their speed, low power, and excellent complementary metal-oxide semiconductor compatibility. Specifically, HfAlOx (HAO) has led to extensive research efforts owing to its outstanding ferroelectric performance. This is a result of the fact that the atomic radius of Al is smaller than that of Hf. In this study, we investigate the metal–ferroelectric–semiconductor device with an Al doping concentration of 2% that was annealed at 900 °C. A high-remnant polarization (Pr) value of 39.85 µC/cm2 and endurance were achieved by using the polarization switching positive-up-negative-down measurement method at this annealing condition. Our device shows long-term potentiation and depression properties, including high linearity and multiple conductance states for neuromorphic applications. Moreover, paired-pulse facilitation was implemented to mimic human synaptic functions. The construction of 16 states comprising four bits was achieved by employing reservoir computing with the FTJ device functioning as a physical reservoir. Finally, the results obtained from the experiment show promising outcomes for the ferroelectric memory characteristics and synaptic properties of the manufactured HAO device. [ABSTRACT FROM AUTHOR]

Since HfOx‐based ferroelectric tunnel junctions (FTJs) are attractive compared to perovskite‐based FTJs and other emerging memory devices, they are being actively studied recently. They have advantages such as a simple metal–insulator–metal structure, complementary metal oxide semiconductor (CMOS) compatibility, non‐destructive operation, and low power consumption. Moreover, doped HfOx‐based FTJs are in the spotlight in terms of neuromorphic engineering as a way of advancing from the von Neumann structure. In particular, Al dopant is effective for inducing ferroelectric properties due to its smaller radius than that of Hf. The optimal concentration of Al varies depending on the device materials and the annealing conditions during deposition. Therefore, in‐depth research is required for neuromorphic applications. Herein, the properties of FTJ devices according to Al doping concentrations are analyzed. Subsequently, using the device with the highest remanent polarization, neuromorphic applications are implemented, including spike‐timing‐dependent plasticity (STDP), paired‐pulse facilitation (PPF), long‐term potentiation, and depression. The characteristics in different frequency regions are also studied to satisfy the demand for fast switching. Finally, the FTJ device is used as a physical reservoir in reservoir computing for efficient processing of time‐dependent inputs. [ABSTRACT FROM AUTHOR]

In this work, we fabricated an ITO/WOX/TaN memristor device by reactive sputtering to investigate resistive switching and conduct analog resistive switching to implement artificial synaptic devices. The device showed good pulse endurance (104 cycles), a high on/off ratio (>10), and long retention (>104 s) at room temperature. The conduction mechanism could be explained by Schottky emission conduction. Further, the resistive switching characteristics were performed by additional pulse-signal-based experiments for more practical operation. Lastly, the potentiation/depression characteristics were examined for 10 cycles. The results thus indicate that the WOX-based devices are appropriate candidates for synaptic devices as well as next-generation nonvolatile memory. [ABSTRACT FROM AUTHOR]

In this work, we evaluate the resistive switching (RS) and synaptic characteristics of a fully transparent resistive random-access memory (T-RRAM) device based on indium-tin-oxide (ITO) electrodes. Here, we fabricated ITO/WOX/ITO capacitor structure and incorporated DC-sputtered WOX as the switching layer between the two ITO electrodes. The device shows approximately 77% (including the glass substrate) of optical transmittance in visible light and exhibits reliable bipolar switching behavior. The current-voltage (I–V) curve is divided into two types: partial and full curves affected by the magnitude of the positive voltage during the reset process. In the partial curve, we confirmed that the retention could be maintained for more than 104 s and the endurance for more than 300 cycles could be stably secured. The switching mechanism based on the formation/rupture of the filament is further explained through the extra oxygen vacancies provided by the ITO electrodes. Finally, we examined the responsive potentiation and depression to check the synaptic characteristics of the device. We believe that the transparent WOX-based RRAM could be a milestone for neuromorphic devices as well as future non-volatile transparent memory. [ABSTRACT FROM AUTHOR]

This paper presents an optical see-through head-mounted display (OST-HMD) that can provide a highly immersive augmented reality (AR) environment. Because visibility of objects is degraded by external light and because projection optics cannot represent black color, the reality of AR content is reduced. To solve this problem, we adopted an additional transparent display to adjust the transmittance of exterior light. This adjustment is achieved using a guest–host liquid crystal (GHLC) to provide transparency in the initial state and opacity when voltage is applied. To verify the display's usefulness, we measured ambient contrast ratio (ACR) and color gamut under various ambient light conditions after attaching the GHLC panel to the existing OST-HMD (Microsoft HoloLens). Under typical office illumination, use of the GHLC panel increased the ACR by 4.67 times, and the color gamut by 2.87 times compared to the OST-HMD without it. Under high illumination the panel increased the ACR by 1.54 times and the color gamut by 16.16 times. The proposed method significantly improved the ambient contrast ratio and color expression, and yielded a flexible way to customize existing OST-HMDs by adding a detachable display. [ABSTRACT FROM AUTHOR]

This paper presents a channel estimation scheme using a new jammed pilot detection algorithm for orthogonal frequency-division multiplexing (OFDM) systems under narrow-band jamming (NBJ). The jammed pilot subcarrier can be detected and excised by using the proposed algorithm after least squares estimation. The average mean square error (mse) on one OFDM symbol both under a jammed and a removed pilot subcarrier are derived analytically. Moreover, the symbol error rate (SER) performance for the channel estimation scheme using the proposed algorithm is evaluated by simulation. From the results, we can show that the channel estimator with the proposed algorithm improves the mse and SER performances at a low signal-to-jamming ratio. Index Terms--Channel estimation, least squares (LS), linear interpolation, narrow-band jamming (NBJ), orthogonal frequency-division multiplexing (OFDM) systems.

In time-varying fading channels, orthogonal frequency division multiplexing systems suffer severe performance degradation caused by interchannel interference (ICI). We utilize this ICI as a source of diversity by using a new ICI-cancellation algorithm and Wiener filter. The proposed algorithm can support joint Doppler-frequency diversity gain. In addition, both the computational complexity and total detection time are reduced. Index Terms--Hybrid interference cancellation (HIC), joint Doppler-frequency diversity, orthogonal frequency division multiplexing (OFDM), parallel interference cancellation (PIC), successive interference cancellation, Wiener filter (WF).

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death. FGFR4 has been implicated in HCC progression, making it a promising therapeutic target. We introduce an approach for identifying novel FGFR4 inhibitors by sequentially adding fragments to a common warhead unit. This strategy resulted in the discovery of a potent inhibitor, 4c , with an IC 50 of 33 nM and high selectivity among members of the FGFR family. Although further optimisation is required, our approach demonstrated the potential for discovering potent FGFR4 inhibitors for HCC treatment, and provides a useful method for obtaining hit compounds from small fragments.