In this study, a computational method is proposed for acoustic field analysis tasks that require lengthy observation times. The acoustic fields at a given observation time are obtained using a fast inverse Laplace transform with a finite-difference complex-frequency-domain. The transient acoustic field can be evaluated at arbitrary sampling intervals by obtaining the instantaneous acoustic field at the desired observation time using the proposed method.

Non-orthogonal multiple access (NOMA) allows several users to multiplex in the power-domain to improve spectral efficiency. To further improve its performance, it is desirable to reduce inter-user interference (IUI). In this paper, we propose a downlink asynchronous NOMA (ANOMA) scheme applicable to frequency-selective channels. The proposed scheme introduces an intentional symbol offset between the multiplexed signals to reduce IUI, and it employs cyclic-prefixed single-carrier transmission with frequency-domain equalization (FDE) to reduce inter-symbol interference. We show that the mean square error for the FDE of the proposed ANOMA scheme is smaller than that of a conventional NOMA scheme. Simulation results show that the proposed ANOMA with appropriate power allocation achieves a better sum rate compared to the conventional NOMA.

There are continuous and strong demands for the DC-DC converter to reduce the size of passive components and increase the system power density. Advances in CMOS processes and GaN FETs enabled the switching frequency of DC-DC converters to be beyond 10MHz. The advancements of 3-D integrated magnetics will further reduce the footprint. In this paper, the overview of beyond-10MHz DC-DC converters will be provided first, and our recent achievements are introduced focusing on 3D-integration of Fe-based metal composite magnetic core inductor, and GaN FET control designs.

This paper proposes a novel interference cancellation technique that prevents radio receivers from degrading due to periodic interference signals caused by electromagnetic waves emitted from high power circuits. The proposed technique cancels periodic interference signals in the frequency domain, even if the periodic interference signals drift in the time domain. We propose a drift estimation based on a super resolution technique such as ESPRIT. Moreover, we propose a sequential drift estimation to enhance the drift estimation performance. The proposed technique employs a linear filter based on the minimum mean square error criterion with assistance of the estimated drifts for the interference cancellation. The performance of the proposed technique is confirmed by computer simulation. The proposed technique achieves a gain of more than 40dB at the higher frequency part in the band. The proposed canceler achieves such superior performance, if the parameter sets are carefully selected. The proposed sequential drift estimation relaxes the parameter constraints, and enables the proposed cancellation to achieve the performance upper bound.

In this paper, an experimental method is proposed for extracting the primary and secondary parameters of transmission lines with frequency dispersion. So far, there is no report of these methods being applied to transmission lines with frequency dispersion. This paper provides an experimental evaluation means of transmission lines with frequency dispersion and clarifies the issues when applying the proposed method. In the proposed experimental method, unnecessary components such as connectors are removed by using a simple de-embedding method. The frequency response of the primary and secondary parameters extracted by using the method reproduced all dispersion characteristics of a transmission line with frequency dispersion successfully. It is demonstrated that an accurate RLGC equivalent-circuit model is obtained experimentally, which can be used to quantitatively evaluate the frequency/time responses of shielded-FPC with frequency dispersion and to validate RLGC equivalent-circuit models extracted by using electromagnetic field analysis.

This paper presents a deep neural network (DNN) based symbol detection and modulation classification detector (SDMCD) for mixed blind signals detection. Unlike conventional methods that employ symbol detection after modulation classification, the proposed SDMCD can perform symbol recovery and modulation identification simultaneously. A cumulant and moment feature vector is presented in conjunction with a low complexity sparse autoencoder architecture to complete mixed signals detection. Numerical results show that SDMCD scheme has remarkable symbol error rate performance and modulation classification accuracy for various modulation formats in AWGN and Rayleigh fading channels. Furthermore, the proposed detector has robust performance under the impact of frequency and phase offsets.

Low-hit-zone frequency-hopping sequences (LHZ-FHSs) are frequency-hopping sequences with low Hamming correlation in a low-hit-zone (LHZ), which have important applications in quasi-synchronous communication systems. However, the strict quasi-synchronization may be hard to maintain at all times in practical FHMA networks, it is also necessary to minimize the Hamming correlation for time-shifts outside of the LHZ. The main objective of this letter is to propose a lower bound on the maximum correlation magnitude outside the low-hit-zone for LHZ-FHS sets. It turns out that the proposed bound is tight or almost tight in the sense that it can be achieved by some LHZ-FHS sets.

This paper describes a method to evaluate the modulated waveforms output by a high-speed external phase modulator over a wide wavelength range by using linear optical sampling (LOS) and a wavelength-swept light source. The phase-modulated waveform is sampled by LOS together with the reference signal before modulation, and the modulation waveform is observed by removing the phase noise of the light source extracted from the reference signal. In this process, the frequency offset caused by the optical-path length difference between the measurement and reference interferometers is removed by digital signal processing. A pseudo-random binary-sequence modulated signal is observed with a temporal resolution of 10ps. We obtained a dynamic range of ∼40dB for the measurement bandwidth of 10 nm. When the measurement bandwidth is expanded to entire C-Band (∼35nm), the dynamic ranges of 37∼46dB were observed, depending on the wavelengths. The measurement time was sub-seconds throughout the experiment.

At present, the application of different types of memristors in electronics is being deeply studied. Given the nonlinearity characterizing memristors, a circuit with memristors cannot be treated by classical circuit analysis. In this paper, memristor is equivalent to a nonlinear dynamic system composed of linear dynamic system and nonlinear static system by Volterra series. The nonlinear transfer function of memristor is derived. In the complex frequency domain, the n-order complex frequency response of memristor is established by multiple Laplace transform, and the response of MLC parallel circuit is taken as an example to verify. Theoretical analysis shows that the complex frequency domain analysis method of memristor transforms the problem of solving nonlinear circuit in time domain into n times complex frequency domain analysis of linear circuit, which provides an idea for nonlinear dynamic system analysis.

This paper proposes a novel maximum Doppler frequency detection technique for user moving velocity estimation. The maximum Doppler frequency is estimated in the proposed detection technique by making use of the fact that user moving velocity is not distributed continuously. The fluctuation of the channel state information during a packet is applied for the proposed detection, in which likelihood estimation is performed by comparing the fluctuation with the thresholds. The thresholds are theoretically derived on the assumption that the fluctuation is distributed with an exponential function. An approximated detection technique is proposed to simplify the theoretical threshold derivation. The performance of the proposed detection is evaluated by computer simulation. The proposed detection accomplishes better detection performance as the fluctuation values are summed over more packets. The proposed detection achieves about 90% correct detection performance in a fading channel with the Eb/N0 = 35dB, when the fluctuation values are summed over only three packets. Furthermore, the approximated detection also achieves the same detection performance.

A periodic array of InSb spheres on a substrate is numerically analyzed at terahertz frequencies. The incident field is shown to be coupled to the substrate due to the guided-mode resonance. The effect of the background refractive index on the transmission characteristics is investigated for sensor applications.

Speech separation is the task of extracting target speech while suppressing background interference components. In applications like video telephones, visual information about the target speaker is available, which can be leveraged for multi-speaker speech separation. Most previous multi-speaker separation methods are mainly based on convolutional or recurrent neural networks. Recently, Transformer-based Seq2Seq models have achieved state-of-the-art performance in various tasks, such as neural machine translation (NMT), automatic speech recognition (ASR), etc. Transformer has showed an advantage in modeling audio-visual temporal context by multi-head attention blocks through explicitly assigning attention weights. Besides, Transformer doesn't have any recurrent sub-networks, thus supporting parallelization of sequence computation. In this paper, we propose a novel speaker-independent audio-visual speech separation method based on Transformer, which can be flexibly applied to unknown number and identity of speakers. The model receives both audio-visual streams, including noisy spectrogram and speaker lip embeddings, and predicts a complex time-frequency mask for the corresponding target speaker. The model is made up by three main components: audio encoder, visual encoder and Transformer-based mask generator. Two different structures of encoders are investigated and compared, including ResNet-based and Transformer-based. The performance of the proposed method is evaluated in terms of source separation and speech quality metrics. The experimental results on the benchmark GRID dataset show the effectiveness of the method on speaker-independent separation task in multi-talker environments. The model generalizes well to unseen identities of speakers and noise types. Though only trained on 2-speaker mixtures, the model achieves reasonable performance when tested on 2-speaker and 3-speaker mixtures. Besides, the model still shows an advantage compared with previous audio-visual speech separation works.

High Frequency Surface Wave Radar (HFSWR) can achieve over-the-horizon detection, which can effectively detect and track the ships and ultra-low altitude aircrafts, as well as the acquisition of sea state information such as icebergs and ocean currents and so on. However, HFSWR is seriously affected by the clutters, especially sea clutter and ionospheric clutter. In this paper, we propose a deep learning image semantic segmentation method based on optimized Deeplabv3+ network to achieve the automatic detection of sea clutter and ionospheric clutter using the measured R-D spectrum images of HFSWR during the typhoon as experimental data, which avoids the disadvantage of traditional detection methods that require a large amount of a priori knowledge and provides a basis for subsequent the clutter suppression or the clutter characteristics research.

In the upcoming Internet of Things era, reducing energy consumption of embedded processors is highly desired. Minimum Energy Point Tracking (MEPT) is one of the most efficient methods to reduce both dynamic and static energy consumption of a processor. Previous works proposed a variety of MEPT methods over the past years. However, none of them incorporate their algorithms with practical real-time operating systems, although edge computing applications often require low energy task execution with guaranteeing real-time properties. The difficulty comes from the time complexity for identifying an MEP and changing voltages, which often prevents real-time task scheduling. The conventional Dynamic Voltage and Frequency Scaling (DVFS) only scales the supply voltage. On the other hand, MEPT needs to adjust the body bias voltage in addition. This additional tuning knob makes MEPT much more complicated. This paper proposes an approximate MEPT algorithm, which reduces the complexity of identifying an MEP down to that of DVFS. The key idea is to linearly approximate the relationship between the processor frequency, supply voltage, and body bias voltage. Thanks to the approximation, optimal voltages for a specified clock frequency can be derived immediately. We also propose a task scheduling algorithm, which adjusts processor performance to the workload and then provides a soft real-time capability to the system. The operating system stochastically adjusts the average response time of the processor to be equal to a specified deadline. MEPT will be performed as a general task, and its overhead is considered in the calculation of the frequency. The experiments using a fabricated test chip and on-chip sensors show that the proposed algorithm is a maximum of 16 times more energy-efficient than DVFS. Also, the energy loss induced by the approximation is only 3% at most, and the algorithm does not sacrifice the fundamental real-time properties.

This paper introduces several design techniques to improve the performance of CMOS frequency multipliers that operate at the sub-THz band without increasing the complexity and the power consumption of the circuit. The proposed techniques are applied to a device nonlinearity-based frequency tripler and to a push-push frequency doubler. By utilizing the fundamental and second harmonic feedback cancellation, the tripler achieves -2.9dBm output power with a simple single-ended circuit architecture reducing the required area and power consumption. The tripler operates at frequencies from 103GHz to 130GHz. The introduced modified push-push doubler provides 2.3dB conversion gain including the balun losses and it has good tolerance against balun mismatches. The output frequency of the doubler is from 118GHz to 124GHz. Both circuits were designed and fabricated using CMOS 65nm technology.

The newly proposed orthogonal time frequency space (OTFS) system exhibits excellent error performance on high-Doppler fading channels. However, the rectangular prototype window function (PWF) inherent in OTFS leads to high out-of-band emission (OOBE), which reduces the spectral efficiency in multi-user scenarios. To this end, this paper presents an OTFS system based on bi-orthogonal frequency division multiplexing (OTFS-BFDM) modulation. In OTFS-BFDM systems, PWFs with bi-orthogonal properties can be optimized to provide lower OOBE than OTFS, which is a special case with rectangular PWF. We further derive that the OTFS-BFDM system is sparsely-connected so that the low-complexity message passing (MP) decoding algorithm can be adopted. Moreover, the power spectral density, peak to average power ratio (PAPR) and bit error rate (BER) of the OTFS-BFDM system with different PWFs are compared. Simulation results show that: i) the use of BFDM modulation significantly inhibits the OOBE of OTFS system; ii) the better the frequency-domain localization of PWFs, the smaller the BER and PAPR of OTFS-BFDM system.

A line display that utilizes saccade has been proposed. When an observer moves his or her eyes on a one-dimensional fixed line display, two-dimensional information is perceived on the retina. In this paper, a high speed flashing line display was developed using a CPLD and PIC microcontroller. The flashing period was reduced to 20 µs, which was less than half that of our previous system. The relationship between the flashing frequency and the optimum distance that can be perceived with the least distortion was clarified. The results show that the higher the flashing frequency is, the more information can be perceived from a farther position. Calculated values, which were based on the relationship between the flashing period and the width of the light source, were almost identical with measured values at the flashing frequencies from 3.3 kHz to 10 kHz. Due to short flashing period, the developed line display not only was visible at distance of 15 m or more, which is suitable for outdoor use, but also realized 16 gray levels.

Frequency-hopping sequence (FHS) sets with low-hit-zone (LZH) can be well applied in quasi-synchronous (QS) frequency-hopping multiple-access (FHMA) systems to reduce the mutual interference among different users. On the other hand, LHZ-FHS sets with wide-gap (WG) property can effectively resist the broadband blocking interference, the single frequency narrowband interference, the multipath fading and the tracking interference. In this letter, a new family of WG-LHZ-FHS sets is constructed. Besides, these new WG-LHZ-FHS sets possess optimal average periodic Hamming correlation (APHC) properties.

This paper investigates an adaptive notch digital filter that employs normal state-space realization of a single-frequency second-order IIR notch digital filter. An adaptive algorithm is developed to minimize the mean-squared output error of the filter iteratively. This algorithm is based on a simplified form of the gradient-decent method. Stability and frequency estimation bias are analyzed for the adaptive iterative algorithm. Finally, a numerical example is presented to demonstrate the validity and effectiveness of the proposed adaptive notch digital filter and the frequency-estimation bias analyzed for the adaptive iterative algorithm.

A method for runtime energy optimization based on the supply voltage (Vdd) and the threshold voltage (Vth) scaling is proposed. This paper refers to the optimal voltage pair, which minimizes the energy consumption of LSI circuits under a target delay constraint, as a Minimum Energy Point (MEP). The MEP dynamically fluctuates depending on the operating conditions determined by a target delay constraint, an activity factor and a chip temperature. In order to track the MEP, this paper proposes a closed-form continuous function that determines the MEP over a wide operating performance region ranging from the above-threshold region down to the sub-threshold region. Based on the MEP determination formula, an MEP tracking algorithm is also proposed. The MEP tracking algorithm estimates the MEP even though the operating conditions widely change. Measurement results based on a 32-bit RISC processor fabricated in a 65-nm Silicon On Thin Buried oxide (SOTB) process technology show that the proposed method estimates the MEP within a 5% energy loss in comparison with the actual MEP operation.