In this paper, we propose an active calibration algorithm to tackle both gain-phase errors and position perturbations. Unlike many other active calibration methods, which fix the array while changing the location of the source, our approach rotates the array but does not change the location of the source, and knowledge of the direction-of-arrival (DOA) of the far-field calibration source is not required. The superiority of the proposed method lies in the fact that measurement of the direction of a far-field calibration source is not easy to carry out, while measurement of the rotation angle via the proposed calibration strategy is convenient and accurate. To obtain the receiving data from different directions, the sensor array is rotated to three different positions with known rotation angles. Based on the eigen-decomposition of the data covariance matrices, we can use the direction of the auxiliary source to represent the gain-phase errors and position perturbations. After that, we estimate the DOA of the calibration source by a one-dimensional search. Finally, the sensor gain-phase errors and position perturbations are calculated by using the estimated direction of the calibration source. Simulations verify the effectiveness and performance of the algorithm.

In this paper, we explore the physical layer security of an Internet of Things (IoT) network comprised of multiple relay-user pairs in the presence of multiple malicious eavesdroppers and channel estimation error (CEE). In order to guarantee secure transmission with channel estimation error, we propose a channel estimation error oriented joint relay-user pair and friendly jammer selection (CEE-JRUPaFJS) scheme to improve the physical layer security of IoT networks. For the purpose of comparison, the channel estimation error oriented traditional round-robin (CEE-TRR) scheme and the channel estimation error oriented traditional pure relay-user pair selection (CEE-TPRUPS) scheme are considered as benchmark schemes. The exact closed-form expressions of outage probability (OP) and intercept probability (IP) for the CEE-TRR and CEE-TPRUPS schemes as well as the CEE-JRUPaFJS scheme are derived over Rayleigh fading channels, which are employed to characterize network reliability and security, respectively. Moreover, the security-reliability tradeoff (SRT) is analyzed as a metric to evaluate the tradeoff performance of CEE-JRUPaFJS scheme. It is verified that the proposed CEE-JRUPaFJS scheme is superior to both the CEE-TRR and CEE-TPRUPS schemes in terms of SRT, which demonstrates our proposed CEE-JRUPaFJS scheme are capable of improving the security and reliability performance of IoT networks in the face of multiple eavesdroppers. Moreover, as the number of relay-user pairs increases, CEE-TPRUPS and CEE-JRUPaFJS schemes offer significant increases in SRT. Conversely, with an increasing number of eavesdroppers, the SRT of all these three schemes become worse.

Inter-channel crosstalk is one of the limiting factors in multichannel optical systems. This paper presents a theoretical analysis of the bit-error-rate (BER) performance of quadrature phase shift keying (QPSK) and quadrature amplitude modulation (QAM) signals influenced by multiple crosstalk channels. The field distribution of multiple crosstalk channels in the constellation map is calculated. The BER of the QPSK/QAM signal, onto which the crosstalk light is superimposed, is then evaluated for a varying number of crosstalk channels under the condition that the total crosstalk power is constant. The results quantitatively confirm that as the channel number increases, the BER degradation caused by crosstalk light approaches that caused by Gaussian noise light. It is also confirmed that the degradations caused by crosstalk light and Gaussian light are similar for QAM signals of high-level modulation.

This paper expands our previously proposed semi-blind uplink interference suppression scheme for multicell multiuser massive MIMO systems to support multi modulus signals. The original proposal applies the channel state information (CSI) aided blind adaptive array (BAA) interference suppression after the beamspace preprocessing and the decision feedback channel estimation (DFCE). BAA is based on the constant modulus algorithm (CMA) which can fully exploit the degree of freedom (DoF) of massive antenna arrays to suppress both inter-user interference (IUI) and inter-cell interference (ICI). Its effectiveness has been verified under the extensive pilot contamination constraint. Unfortunately, CMA basically works well only for constant envelope signals such as QPSK and thus the proposed scheme should be expanded to cover QAM signals for more general use. This paper proposes to apply the multi modulus algorithm (MMA) and the minimum mean square error weight derivation based on data-aided sample matrix inversion (MMSE-SMI). It can successfully realize interference suppression even with the use of multi-level envelope signals such as 16QAM with satisfactorily outage probability performance below the fifth percentile.

The phaseless antenna measurement technique is advantageous for high-frequency near-field measurements in which the uncertainty of the measured phase is a problem. In the phaseless measurement, which is expected to be used in the frequency band with a short wavelength, a slight positional deviation error of the probe greatly deteriorates the measurement result. This paper proposes a phase retrieval method that can compensate the measurement errors caused by misalignment of a probe and its jig. And this paper proposes a far-field estimation method by phase resurrection that incorporated the compensation techniques. We find that the positioning errors are due to the random errors occurring at each measurement point because of minute vibrations of the probe; in addition, we determine that the stationary depth errors occurring at each measurement surface as errors caused by improper setting of the probe jig. The random positioning error is eliminated by adding a low-pass filter in wavenumber space, and the depth positioning error is iteratively compensated on the basis of the relative residual obtained in each plane. The validity of the proposed method is demonstrated by estimating the far-field patterns using the results from numerical simulations, and is also demonstrated using measurement data with probe-positioning error. The proposed method can reduce the probe-positioning error and improve the far-field estimation accuracy by more over than 10 dB.

A robust adaptive beamforming algorithm is proposed based on the precise interference-plus-noise covariance matrix reconstruction and steering vector estimation of the desired signal, even existing large gain-phase errors. Firstly, the model of array mismatches is proposed with the first-order Taylor series expansion. Then, an iterative method is designed to jointly estimate calibration coefficients and steering vectors of the desired signal and interferences. Next, the powers of interferences and noise are estimated by solving a quadratic optimization question with the derived closed-form solution. At last, the actual interference-plus-noise covariance matrix can be reconstructed as a weighted sum of the steering vectors and the corresponding powers. Simulation results demonstrate the effectiveness and advancement of the proposed method.

Stochastic computing (SC), which is an approximate computation with probabilities, has attracted attention owing to its small area, small power consumption and high fault tolerance. In this paper, we focus on the transient fault tolerance of SC based on linear finite state machines (linear FSMs). We show that state assignment of FSMs considerably affects the fault tolerance of linear FSM-based SC circuits, and present a Markov model for representing the impact of the state assignment on the behavior of faulty FSMs and estimating the expected error significance of the faulty FSM-based SC circuits. Furthermore, we propose a heuristic algorithm for appropriate state assignment that can mitigate the influence of transient faults. Experimental analysis shows that the state assignment has an impact on the transient fault tolerance of linear FSM-based SC circuits and the proposed state assignment algorithm can achieve a quasi-optimal state assignment in terms of high fault tolerance.

We propose a coding/decoding strategy that surpasses the symmetric information rate of a binary insertion/deletion (ID) channel and approaches the Markov capacity of the channel. The proposed codes comprise inner trellis codes and outer irregular low-density parity-check (LDPC) codes. The trellis codes are designed to mimic the transition probabilities of a Markov input process that achieves a high information rate, whereas the LDPC codes are designed to maximize an iterative decoding threshold in the superchannel (concatenation of the ID channels and trellis codes).

For insertion and deletion channels, there are many coding schemes based on low-density parity-check (LDPC) codes, such as spatially coupled (SC) LDPC codes and concatenated codes of irregular LDPC codes and markers. However, most of the previous works have problems, such as poor finite-length performance and unrealistic settings for codeword lengths and decoding iterations. Moreover, when using markers, the decoder receives log-likelihood (LLR) messages with different statistics depending on code bit position. In this paper, we propose a novel concatenation scheme using protograph-based LDPC code and markers that offers excellent asymptotic/finite-length performance and a structure that controls the irregularity of LLR messages. We also present a density evolution analysis and a simple optimization procedure for the proposed concatenated coding scheme. For two decoding scenarios involving decoding complexity, both asymptotic decoding thresholds and finite-length performance demonstrate that the newly designed concatenated coding scheme outperforms the existing counterparts: the irregular LDPC code with markers, the SC-LDPC code, and the protograph LDPC code, which is optimized for an additive white Gaussian noise channel, with markers.

Over the past two decades, irregular low-density parity-check (LDPC) codes have not been able to decode information corrupted by insertion and deletion (ID) errors without markers. In this paper, we bring to light the existence of irregular LDPC codes that approach the symmetric information rates (SIR) of the channel with ID errors, even without markers. These codes have peculiar shapes in their check-node degree distributions. Specifically, the check-node degrees are scattered and there are degree-2 check nodes. We propose a code construction method based on the progressive edge-growth algorithm tailored for the scattered check-node degree distributions, which enables the SIR-approaching codes to progress in the finite-length regime. Moreover, the SIR-approaching codes demonstrate asymptotic and finite-length performance that outperform the existing counterparts, namely, concatenated coding of irregular LDPC codes with markers and spatially coupled LDPC codes.

In the typical unmanned aircraft system (UAS), several unmanned aerial vehicles (UAVs) traveling at a velocity of 40-100km/h and with altitudes of 150-1,000m will be used to cover a wide service area. Therefore, Doppler shifts occur in the carrier frequencies of the transmitted and received signals due to changes in the line-of-sight velocity between the UAVs and the terrestrial terminal. By observing multiple Doppler shift values for different UAVs or observing a single UAV at different local times, it is possible to detect the user position on the ground. We conducted computer simulations for evaluating user position detection accuracy and Doppler shift distribution in several flight models. Further, a positioning accuracy index (PAI), which can be used as an index for position detection accuracy, was proposed as the absolute value of cosine of the inner product between two gradient vectors formed by Doppler shifts to evaluate the relationship between the location of UAVs and the position of the user. In this study, a maximum positioning error estimation method related to the PAI is proposed to approximate the position detection accuracy. Further, computer simulations assuming a single UAV flying on the curved routes such as sinusoidal routes with different cycles are conducted to clarify the effectiveness of the flight route in the aspects of positioning accuracy and latency by comparing with the conventional straight line fight model using the PAI and the proposed maximum positioning error estimation method.

For automotive millimeter radar, a method using a multi-input multi-output (MIMO) array antenna is essential for high angle resolution with module miniaturization. MIMO enables us to extend an antenna array with virtual antennas, and a large antenna array aperture enables high resolution angle estimation. Time division multiplex (TDM) MIMO, which is a method to generate virtual array antennas, makes it easy to design radar system integrated circuits. However, this method leads to two issues in signal processing; the phase error reduces the accuracy of angle estimation of a moving target, and the maximum detectable velocity decreases in inverse proportion to the number of Tx antennas. We analytically derived this phase error and proposed a method to correct the error. Because the phase error of TDM-MIMO is proportional to the target velocity, accurate estimation of the target velocity is an important issue for phase error correction. However, the decrease of the maximum detectable velocity in TDM-MIMO reduces the accuracy of both velocity estimation and angle estimation. To solve these issues, we propose new signal processing for range-velocity estimation for TDM-MIMO radar. By using the feedback result of the estimated direction of arrival (DoA), we can avoid decreasing the maximum detectable velocity. We explain our method with our simulation results.

The recent development of semiconductor technology has led to downsized, large-scaled and low-power VLSI systems. However, the incidence of soft errors has increased. Soft errors are temporary events caused by striking of α-rays and high energy neutron radiation. Since the scale of VLSI has become smaller in recent development, it is necessary to consider the occurrence of not only single node upset (SNU) but also double node upset (DNU). The existing High-performance, Low-cost, and DNU Tolerant Latch design (HLDTL) does not completely tolerate DNU. This paper presents a new design of a DNU tolerant latch to resolve this issue by adding some transistors to the HLDTL latch.

A method of determining emission limits was studied by using the amplitude probability distribution (APD) for low-probability pulsed electromagnetic disturbances due to discharge. The features of this method are 1) without using the previously reported relationship between APD and bit error rate, the limits are derived using the measured impact of a pulsed disturbance on various wireless communication systems having different bandwidths, and 2) disturbances caused by discharge with poor reproducibility are simulated by regularly repeated pulse-modulated sine waves to enable stable evaluation of the communication quality. APD-based limits are determined from the pulse repetition frequency of the simulated disturbance such that the block error rate (BLER) is less than a certain limit in wireless systems that are most sensitive to the pulsed disturbance. In the international standard CISPR 32 regulating electromagnetic disturbance, radiated disturbance due to discharge is excluded from the application of peak detection limits because of its low occurrence probability. In this paper we quantitatively determine appropriate criteria of the probability for the exclusion. Using the method, we measured the impact of low-probability pulsed interference on major wireless systems and found that GSM and Wi-Fi systems were the most sensitive. New APD-based limits were derived on the basis of these findings. The APD-based limits determined by the proposed method enable a valid evaluation of low-occurrence-probability pulsed disturbances without unconditionally excluding the measurement.

This paper proposes a sampling strategy for bandlimited graph signals over perturbed graph, in which we assume the edge between any pair of the nodes may be deleted randomly. Considering the mismatch between the true graph and the presumed graph, we derive the mean square error (MSE) of the reconstructed bandlimited graph signals. To minimize the MSE, we propose a greedy-based algorithm to obtain the optimal sampling set. Furthermore, we use Neumann series to avoid the pseudo-inverse computing. An efficient algorithm with low-complexity is thus proposed. Finally, numerical results show the superiority of our proposed algorithms over the other existing algorithms.

An offline sensor gain-phase errors calibration method for a linear array using a source in unknown location is proposed. The proposed method is realized through three steps. First, based on the observed covariance matrix, we construct a function related to direction, and it is proved that when the function takes the minimum value, the corresponding value should be the direction of the calibration source. Second, the direction of calibration source is estimated by locating the valley from the constructed function. Third, the gain-phase errors are obtained based on the estimated direction. The proposed method offers a number of advantages. First, the accurate direction measurement of the calibration source is not required. Second, only one calibration source needs to be arranged. Third, it does not require an iterative procedure or a two-dimensional (2D) spectral search. Fourth, the method is applicable to linear arrays, not only to uniform linear arrays (ULAs). Numerical simulations are presented to verify the efficacy of the proposed method.

This study presents a method for improving the heartbeat interval accuracy of photoplethysmographic (PPG) sensors at ultra-low sampling rates. Although sampling rate reduction can extend battery life, it increases the sampling error and degrades the accuracy of the extracted heartbeat interval. To overcome these drawbacks, a sampling-error compensation method is proposed in this study. The sampling error is reduced by using linear interpolation and autocorrelation based on the waveform similarity of heartbeats in PPG. Furthermore, this study introduces two-line approximation and first derivative PPG (FDPPG) to improve the waveform similarity at ultra-low sampling rates. The proposed method was evaluated using measured PPG and reference electrocardiogram (ECG) of seven subjects. The results reveal that the mean absolute error (MAE) of 4.11ms was achieved for the heartbeat intervals at a sampling rate of 10Hz, compared with 1-kHz ECG sampling. The heartbeat interval error was also evaluated based on a heart rate variability (HRV) analysis. Furthermore, the mean absolute percentage error (MAPE) of the low-frequency/high-frequency (LF/HF) components obtained from the 10-Hz PPG is shown to decrease from 38.3% to 3.3%. This error is small enough for practical HRV analysis.

The aim of this paper is to show an upper bound for finding defective samples in a group testing framework. To this end, we exploit minimization of Hamming weights in coding theory and define probability of error for our decoding scheme. We derive a new upper bound on the probability of error. We show that both upper and lower bounds coincide with each other at an optimal density ratio of a group matrix. We conclude that as defective rate increases, a group matrix should be sparser to find defective samples with only a small number of tests.

The packet error rate (PER) performance of multi-hop STBC based cooperative and diversity relaying systems are studied. These systems consist of a source, a destination, and two relay stations in each hop. From in-lab experiments, it is confirmed that the cooperative relaying system has better PER performance than the diversity relaying system with highly correlated channels.

This paper presents a successive cancellation (SC) decoding of polar codes modified for insertion/deletion/substitution (IDS) error channels, in which insertions and deletions are described by drift values. The recursive calculation of the original SC decoding is modified to include the drift values as stochastic variables. The computational complexity of the modified SC decoding is O (D3) with respect to the maximum drift value D, and O (N log N) with respect to the code length N. The symmetric capacity of polar bit channel is estimated by computer simulations, and frozen bits are determined according to the estimated symmetric capacity. Simulation results show that the decoded error rate of polar code with the modified SC list decoding is lower than that of existing IDS error correction codes, such as marker-based code and spatially-coupled code.