The spectrum sculpting precoder (SSP) is a precoding scheme for sidelobe suppression of frequency division multiplexing (OFDM) signals. It can form deep spectral notches at chosen frequencies and is suitable for cognitive radio systems. However, the SSP degrades the error rate as the number of notched frequencies increases. Orthogonal precoding that improves the SSP can achieve both spectrum notching and the ideal error rate, but its computational complexity is very high since the precoder matrix is large in size. This paper proposes an effective and equivalent decomposition of the precoder matrix by QR-decomposition in order to reduce the computational complexity of orthogonal precoding. Numerical experiments show that the proposed method can drastically reduce the computational complexity with no performance degradation.

A frequently occurring subcircuit consists of a loop of a resistor (R), a field-effect transistor (FET), and a capacitor (C). The FET acts as a switch, controlled at its gate terminal by a clock voltage. This subcircuit may be acting as a sample-and-hold (S/H), as a passive mixer (P-M), or as a bandpass filter or bandpass impedance. In this work, we will present a useful analysis that leads to a simple signal flow graph (SFG), which captures the FET-R-C circuit's action completely across a wide range of design parameters. The SFG dissects the circuit into three filtering functions and ideal sampling. This greatly simplifies analysis of frequency response, noise, input impedance, and conversion gain, and leads to guidelines for optimum design. This paper focuses on the analysis of a single-path FET-R-C circuit's signal transfer characteristics including the reconstruction of the complete waveform from the discrete-time sampled voltage.

This paper presents low-noise amplifier (LNA)-less 300-GHz CMOS receivers that operate above the NMOS unity-power-gain frequency, fmax. The receivers consist of a down-conversion mixer with a doubler- or tripler-last multiplier chain that upconverts an LO1/n signal into 300 GHz. The conversion gain of the receiver with the doubler-last multiplier is -19.5 dB and its noise figure, 3-dB bandwidth, and power consumption are 27 dB, 27 GHz, and 0.65 W, respectively. The conversion gain of the receiver with the tripler-last multiplier is -18 dB and its noise figure, 3-dB bandwidth, and power consumption are 25.5 dB, 33 GHz, and 0.41 W, respectively. The receivers achieve a wireless data rate of 32 Gb/s with 16QAM. This shows the potential of the moderate-fmax CMOS technology for ultrahigh-speed THz wireless communications.

Development of narrowband thermal emitters whose emission wavelengths are dynamically tunable is highly desired for various applications including the sensing of gases and chemical compounds. In this paper, we review our recent demonstration of wavelength-switchable mid-infrared thermal emitters based on multiple quantum wells (MQWs) and photonic crystals (PCs). Through the control of absorptivity by using intersubband transitions in MQWs and optical resonances in PC slabs, we demonstrate novel control of thermal emission, including realization of high-Q (Q>100) thermal emission, dynamic control of thermal emission (∼MHz), and electrical wavelength switching of thermal emission from a single device.

Internal quantum efficiency (IQE) is usually estimated from temperature dependence of photoluminescence (PL) intensity by assuming that the IQE at cryogenic temperature is unity. III-nitride samples, however, usually have large defect density, and the assumption is not necessarily valid. In 2016, we proposed a new method to estimate accurate IQE values by simultaneous PL and photo-acoustic (PA) measurements, and demonstratively evaluated the IQE values for various GaN samples. In this study, we have applied the method to InGaN quantum-well active layers and have estimated the IQE values and their excitation carrier-density dependence in the layers.

We discuss our recent progress in photonic crystal nanocavity quantum dot lasers. We show how enhanced light matter interactions in the nanocavity lead to diverse and fascinating lasing phenomena that are in general inaccessible by conventional bulky semiconductor lasers. First, we demonstrate thresholdless lasing, in which any clear kink in the output laser curve does not appear. This is a result of near unity coupling of spontaneous emission into the lasing cavity mode, enabled by the strong Purcell effect supported in the nanocavity. Then, we discuss self-frequency conversion nanolasers, in which both near infrared lasing oscillation and nonlinear optical frequency conversion to visible light are simultaneously supported in the individual nanocavity. Owing to the tight optical confinement both in time and space, a high normalized conversion efficiency over a few hundred %/W is demonstrated. We also show that the intracavity nonlinear frequency conversion can be utilized to measure the statistics of the intracavity photons. These novel phenomena will be useful for developing various nano-optoelectronic devices with advanced functionalities.

Frequency chirp of a semiconductor laser is controlled by using hybrid modulation, which simultaneously modulates intra-cavity loss and injection current to the laser. The positive adiabatic chirp of injection-current modulation is compensated with the negative adiabatic chirp created by intra-cavity-loss modulation, which enhances the chromatic-dispersion tolerance of the laser. A proof-of-concept transmission experiment confirmed that the hybrid modulation laser has a larger dispersion tolerance than conventional directly modulated lasers due to the negative frequency chirp originating from intra-cavity-loss modulation.

This paper focuses mainly on issues related to the pricing of American options under a fuzzy environment by taking into account the clustering of the underlying asset price volatility, leverage effect and stochastic jumps. By treating the volatility as a parabolic fuzzy number, we constructed a Levy-GJR-GARCH model based on an infinite pure jump process and combined the model with fuzzy simulation technology to perform numerical simulations based on the least squares Monte Carlo approach and the fuzzy binomial tree method. An empirical study was performed using American put option data from the Standard & Poor's 100 index. The findings are as follows: under a fuzzy environment, the result of the option valuation is more precise than the result under a clear environment, pricing simulations of short-term options have higher precision than those of medium- and long-term options, the least squares Monte Carlo approach yields more accurate valuation than the fuzzy binomial tree method, and the simulation effects of different Levy processes indicate that the NIG and CGMY models are superior to the VG model. Moreover, the option price increases as the time to expiration of options is extended and the exercise price increases, the membership function curve is asymmetric with an inclined left tendency, and the fuzzy interval narrows as the level set α and the exponent of membership function n increase. In addition, the results demonstrate that the quasi-random number and Brownian Bridge approaches can improve the convergence speed of the least squares Monte Carlo approach.

We have proposed and developed new electro-optic modulators for the pre-equalization of signal distortion caused by the optical fiber chromatic dispersion effect. We found that the synthesis of an almost arbitrary impulse response function is obtainable by utilizing an electro-optic modulator composed of a Mach-Zehnder waveguide and travelling-wave electrodes on a ferro-electric material substrate with polarization-reversed structures. In this paper, the operational principle, design and simulation results of the pre-equalization modulator are presented. Some preliminary experimental results are also shown with future prospects.

This paper enhances the QoE of audio and video multicast transmission over a wireless LAN by means of reliable groupcast schemes. We use GCR (GroupCast with Retries) Unsolicited Retry and GCR Block ACK as reliable groupcast schemes; they are standardized by IEEE 802.11aa. We assume that a wireless access point transmits audio and video streams to several terminals connected to the access point by groupcast. We compare three schemes: Groupcast with EDCA (Enhanced Distributed Channel Access), GCR Unsolicited Retry and GCR Block ACK. We perform computer simulations under various network conditions to assess application-level QoS and evaluate QoE by a subjective experiment. As a result, we find that the most effective scheme depends on network conditions.

A penta-band antenna based on the mu-negative transmission line is presented for radio frequency (RF) energy harvesting application. The antenna utilizes five radiation modes; two quarter wavelength resonances, three quarter wavelength resonance, zeroth order resonance, and first order resonance. The parasitic radiating strip antenna generates quarter wavelength resonance radiation. The dual band antenna based on two unit cell mu-negative (MNG) transmission line gives birth to the zeroth order resonance (ZOR) mode and the first order resonance (FOR) mode. The parasitic radiating strip and dual band antenna based on two unit mu-negative (MNG) transmission line are magnetically coupled by a feed monopole with gap. This feed monopole, simultaneously, radiates at quarter and three quarter wavelength resonance frequency to cover the other bands. The multi-mode coupling mechanism of this penta-band antenna is well modeled by our derived equivalent circuit. The measured radiation efficiencies are more than 87% over the entire penta-band.

For the reconstruction of the feedback polynomial of a synchronous scrambler placed after a convolutional encoder, the existing algorithms require the prior knowledge of a dual word of the convolutional code. To address the case of a dual word being unknown, a new algorithm for the reconstruction of the feedback polynomial based on triple correlation characteristic of an m-sequence is proposed. First, the scrambled convolutional code sequence is divided into bit blocks; the product of the scrambled bit blocks with a dual word is proven to be an m-sequence with the same period as the synchronous scrambler. Second, based on the triple correlation characteristic of the generated m-sequence, a dual word is estimated; the generator polynomial of the generated m-sequence is computed by two locations of the triple correlation peaks. Finally, the feedback polynomial is reconstructed using the generator polynomial of the generated m-sequence. As the received sequence may contain bit errors, a method for detecting triple correlation peaks based on the constant false-alarm criterion is elaborated. Experimental results show that the proposed algorithm is effective. Ulike the existing algorithms available, there is no need to know a dual word a priori and the reconstruction result is more accurate. Moreover, the proposed algorithm is robust to bit errors.

Location information is meaningful information for future ITS (Intelligent Transport Systems) world. Especially, the accuracy of the information is required because the accuracy decides the quality of ITS services. For realization of high precision positioning, Kinematic positioning technique has been attracting attention. The Kinematic positioning requires the configuration of many positioning parameters. However, the configuration is difficult because optimal parameter differs according to user's environment. In this paper, we will propose an estimation method of optimal parameter according to the environment. Further, we will propose an elimination method of unreliable positioning results. Hereby, we can acquire extensively only the reliable positioning results. By using the actual vehicle traveling data, the ability and the applicable range of the proposed method will be shown. The result will show that our proposed method improves the acquision rate of reliable positioning results and mitigates the acquision rate of the unreliable positioning results.

Most conventional research on target motion analysis (TMA) based on least squares (LS) has focused on performing asymptotically unbiased estimation with inaccurate measurements. However, such research may often yield inaccurate estimation results when only a small set of measurement data is used. In this paper, we propose an accurate TMA method even with a small set of bearing measurements. First, a subset of measurements is selected by a random sample consensus (RANSAC) algorithm. Then, LS is applied to the selected subset to estimate target motion. Finally, to increase accuracy, the target motion estimation is refined through a bias compensation algorithm. Simulated results verify the effectiveness of the proposed method.

Geosocial networking allows users to interact with respect to their current locations, which enables a group of users to determine where to meet. This calls for techniques that support processing of Multiple-user Location-based Keyword (MULK) queries, which return a set of Point-of-Interests (POIs) that are 'close' to the locations of the users in a group and can provide them with potential options at the lowest expense (e.g., minimizing travel distance). In this paper, we formalize the MULK query and propose a dynamic programming-based algorithm to find the optimal result set. Further, we design two approximation algorithms to improve MULK query processing efficiency. The experimental evaluations show that our solutions are feasible and efficient under various parameter settings.

By interleaving known Z-periodic complementary (ZPC) sequence set, a new ZPC sequence set is constructed with multiple ZPC sequence subsets based on an orthogonal matrix in this work. For this novel ZPC sequence set, which refer to as asymmetric ZPC (AZPC) sequence set, its inter-subset zero cross-correlation zone (ZCCZ) is larger than intra-subset zero correlation zone (ZCZ). In particular, if select a periodic perfect complementary (PC) sequence or PC sequence set and a discrete Fourier transform (DFT) matrix, the resultant sequence set is an inter-group complementary (IGC) sequence set. When a suitable shift sequence is chosen, the obtained IGC sequence set will be optimal in terms of the corresponding theoretical bound. Compared with the existing constructions of IGC sequence sets, the proposed method can provide not only flexible ZCZ width but also flexible choice of basic sequences, which works well in both synchronous and asynchronous operational modes. The proposed AZPC sequence sets are suitable for multiuser environments.

This paper derives highly accurate and effective closed-form formulas for the average upper bound on the pairwise error probability (PEP) of the multi-carrier index keying orthogonal frequency division multiplexing (MCIK-OFDM) system with low-complexity detection (i.e., greedy detection) in two-wave with diffuse power (TWDP) fading channels. To be specific, we utilize an exact moment generating function (MGF) of the signal-to-noise ratio (SNR) under TWDP fading to guarantee highly precise investigations of error probability performance; existing formulas for average PEP employ the approximate probability density function (PDF) of the SNR for TWDP fading, thereby inducing inherent approximation error. Moreover, some special cases of TWDP fading are also considered. To quantitatively reveal the achievable modulation gain and diversity order, we further derive asymptotic formulas for the upper bound on the average PEP. The obtained asymptotic expressions can be used to rapidly estimate the achievable error performance of MCIK-OFDM with the greedy detection over TWDP fading in high SNR regimes.

Stereoscopic vision technology is applied in a wide range of fields, from 3D movies to medical care. Stereoscopic vision makes it possible to observe images in parallax between both eyes. However, parallax images cannot be used all the time due to a situation called “occlusion”, in which an object is hidden in the depths by another object. In this case, different images are projected on the right and left retina. Here, we propose a psychology experiment to elucidate the function of parvocellular cells in the LGN of the visual cortex of the brain using occlusion perception. As a new psychology experiment to clarify whether parvocellular cells in the LGN of the visual cortex, said to process chromatic and luminance information, can detect a disagreement between the retinal images produced by each eye, we measured convergence eye movement when gazing at the rim of a column under occlusion using an equiluminance random dot pattern. When eye movement prevented the disagreement of the retinal images caused by occlusion, we thought that convergence eye movement to move both eyes in front of the rim or divergence eye movement to move them behind the rim would occur. In other words, we thought that we could clarify whether there was parvocellular system process agreement or disagreement between the right and left retinal images under equiluminance. Therefore, we examined whether a system to detect disagreement between the retinal images exists in the brain when gazing at the rim of a column onto which an equiluminance random dot texture was mapped. Results suggested that the mechanism to avoid disagreement between the retinal images of the eyes caused by occlusion occurs in the parvocellular cells, which mainly process color information, as well as in the magnocellular cells, which process binocular disparity.

An accurate but energy-efficient estimation of a position is important as the number of mobile computing systems grow rapidly. A challenge is to develop a highly accurate but energy efficient estimation method. A particle filter is a key algorithm to estimate and track the position of an object which exhibits non-linear movement behavior. However, it requires high usage of computation resources and energy. In this paper, we propose a scheme which can dynamically adjust the number of particles according to the accuracy of the reference signal for positioning and reduce the energy consumption by 37% on Cortex A7.

Efficiently locating nodes and allocating demand has been a significant problem for telecommunication network carriers. Most of location models focused on where to locate nodes and how to assign increasing demand with optical access networks. However, the population in industrialized countries will decline over the coming decades. Recent advance in the optical amplifier technology has enabled node integration; an excess telecommunication node is closed and integrated to another node. Node integration in low-demand areas will improve the efficiency of access networks in this approaching age of depopulation. A dynamic node integration problem (DNIP) has been developed to organize the optimal plan for node integration. The problem of the DNIP was that it cannot consider the requirements of network carriers. In actual situations, network carriers often want to specify the way each node is managed, regardless of the mathematical optimality of the solution. This paper proposes a requirement modeling language (RML) for the DNIP, with which the requirements of network carriers can be described. The described statements are used to solve the DNIP, and consequently the calculated optimal solution always satisfies the requirements. The validity of the proposed method was evaluated with computer simulations in a case study.