In mobile phone systems, the 4th generation is widely prevailing in 2017, and in 2020, it is expected that the 5th generation (5G) will start to prevail. In both generations, a linear power amplifier (PA) is used. In case of 4G, in addition, such as the envelope tracking (ET) and the digital predistortion (DPD) systems are applied to improve efficiency and linearity. In case of 5G, because of wider modulation band width and parallel operation under the multiple-input and multiple output (MIMO) mode, it might be difficult to apply all systems as those of 4G. Therefore linear PA for 5G will require higher performance with standalone operation. The linear amplifier, in spite of its name, operates non-linearly. In this paper, the non-linear operations of the linear amplifier and their effects on the linearity characteristics are reviewed. After that, impacts of non-linear elements of a hetero junction bipolar transistor (HBT), by analyzing single stage amplifier, are stated. In addition, major PA architectures including ET and DPD systems are reviewed.

A compact uniplanar antenna design for tablet/laptop applications is proposed. The main design principle of this antenna is the use of the coupling-feed mechanism. The proposed antenna is composed of an inverted L-shaped parasitic element, T-shaped feeding strip, parasitic shorted strip, and a step tuning stub. With its small size of 55mm × 15mm × 0.8mm, the proposed antenna is able to excite dual wideband transmission over the full LTE/WWAN operation ranges of 698-960MHz and 1710-2690MHz. Furthermore, the proposed antenna also exhibits reduced ground effects, such that reducing the ground size of the proposed antenna will not affect its performance.

Three-dimensional (3-D) scattering center models use a finite number of point scatterers to efficiently represent complex radar target signature. Using the CLEAN algorithm, 3-D scattering center model is extracted from the inverse synthetic aperture radar (ISAR) image, which is generated based on the shooting and bouncing ray (SBR) technique. The conventional CLEAN extracts the strongest peak iteratively based on the assumption that the scattering centers are isolated. In a realistic target, however, both interference from the closely spaced points and additive noise distort the extraction process. This paper proposes a matched filter-based CLEAN algorithm to improve accuracy efficiently. Using the matched filtering of which impulse response is the known point spread function (PSF), a point most correlated with the PSF is extracted. Thus, the proposed method optimally enhances the accuracy in the presence of massive distortions. Numerical simulations using canonical and realistic targets demonstrate that the extraction accuracy is improved without loss of time-efficiency compared with the existing CLEAN algorithms.

Wireless Sensor Networks (WSNs) are randomly deployed in a hostile environment and left unattended. These networks are composed of small auto mouse sensor devices which can monitor target information and send it to the Base Station (BS) for action. The sensor nodes can easily be compromised by an adversary and the compromised nodes can be used to inject false vote or false report attacks. To counter these two kinds of attacks, the Probabilistic Voting-based Filtering Scheme (PVFS) was proposed by Li and Wu, which consists of three phases; 1) Key Initialization and assignment, 2) Report generation, and 3) En-route filtering. This scheme can be a successful countermeasure against these attacks, however, when one or more nodes are compromised, the re-distribution of keys is not handled. Therefore, after a sensor node or Cluster Head (CH) is compromised, the detection power and effectiveness of PVFS is reduced. This also results in adverse effects on the sensor network's lifetime. In this paper, we propose a Fuzzy Rule-based Key Redistribution Method (FRKM) to address the limitations of the PVFS. The experimental results confirm the effectiveness of the proposed method by improving the detection power by up to 13.75% when the key-redistribution period is not fixed. Moreover, the proposed method achieves an energy improvement of up to 9.2% over PVFS.

In this paper, we propose a new structure for a compact matched filter bank (MFB) for an optical zero-correlation zone (ZCZ) sequence set with Zcz=2z. The proposed MFB can reduces operation elements such as 2-input adders and delay elements. The number of 2-input adders decrease from O(N2) to O(N log2 N), delay elements decrease from O(N2) to O(N). In addition, the proposed MFBs for the sequence of length 32, 64, 128 and 256 with Zcz=2,4 and 8 are implemented on a field programmable gate array (FPGA). As a result, the numbers of logic elements (LEs) of the proposed MFBs for the sequences with Zcz=2 of length 32, 64, 128 and 256 are suppressed to about 76.2%, 84.2%, 89.7% and 93.4% compared to that of the conventional MFBs, respectively.

To support the rapid increase of mobile traffic, the LTE-based air interface is expected to be employed in the unlicensed spectrum known as “Licensed-Assisted Access (LAA).” The LAA terminal, which employs an LTE-based air interface, suffers from interference from WiFi access points as well as the LAA base station. The interference rejection combining (IRC) receiver, which employs a linear minimum mean square error (MMSE) filter, can suppress this interference from WiFi access points in addition to that of the LAA base station. The IRC receiver is effective, since it requires no knowledge of the interference, which is generally difficult to obtain for different systems. In this paper, we use a link-level simulation to evaluate the performance of the IRC receiver in suppressing the interference from WiFi access points, and show that the IRC receiver can effectively cancel the interference from WiFi systems as well as LTE systems, although we observed a slight performance degradation due to the covariance matrix estimation error caused by the WiFi interference fluctuation in the frequency-domain.

Based on the known binary and quaternary zero correlation zone (ZCZ) sequence sets, a class of 16-QAM sequence sets with ZCZ is presented, where the term “QAM sequence” means the sequence over the quadrature amplitude modulation (QAM) constellation. The sequence sets obtained by this method achieve an expansion in the number of 16-QAM sequence sets with ZCZ. The proposed sequence sets can be applied to quasi-synchronous code division multiple access (QS-CDMA) systems to eliminate the multiple access interference (MAI) and multipath interference (MPI) and improve the transmission data rate (TDR).

The combination of GPS measurements with the dynamic model via a Kalman filter or an extended Kalman filter, also known as GPS based reduced dynamic orbit determination (RDOD) techniques, have been widely used for accurate and real time navigation of satellites in low earth orbit (LEO). In previous studies, the GPS measurement noise variance is empirically taken as a constant, which is not reasonable because of insufficient prior information or dynamic environment. An improper estimate of the measurement noise may lead to poor performance or even divergence of the filter. In this letter, an adaptive extended Kalman filter (AEKF)-based approach using GPS dual-frequency pseudo-range measurements is presented, where the GPS pseudo-range measurement noise variance is adaptively estimated by the Carrier to Noise Ratio (C/N0) from the tracking loop of GPS receiver. The simulation results show that the proposed AEKF approach can achieve apparent improvements of the position accuracy and almost brings no extra computational burdens for satellite borne processor.

A Tikhonov regularized RLS algorithm with an exponential weighting factor, i.e., a leaky RLS (LRLS) algorithm was proposed by the author. A quadratic version of the LRLS algorithm also exists in the literature of adaptive filters. In this letter, a cubic version of the LRLS filter which is computationally efficient is proposed when the length of the adaptive filter is short. The proposed LRLS filter includes only a divide per iteration although its multiplications and additions increase in number. Simulation results show that the proposed LRLS filter is faster for its short length than the existing quadratic version of the LRLS filter.

This paper presents an extremely low-profile front-end configuration for a base station at quasi-millimeter wave band. It consists of integrated modules of patch antennas and substrate integrated waveguide filters using two printed circuit boards, and transmitter modules using compact GaAs pHEMT three-dimensional monolithic millimeter-wave integrated circuits. The transmitter modules are located around the integrated modules. This is because the proposed front-end configuration can attain extremely low profile, and band-pass filtering performance at quasi-millimeter wave band. As a demonstration of the proposed configuration, 26-GHz-band 4-by-4 elements front-end module is fabricated and tested. The fabricated module has the thickness of about 1 cm, while that offers the attenuation of more than 30 dB with 2 GHz offset from 26 GHz. The proposed configuration can provide base station that can be effective in offering sub-millimeter wave and millimeter-wave bands broadband services for 5G mobile communications systems.

In this paper, we propose filter-and-forward beamforming (FF-BF) for cognitive two-way relay networks in which secondary users employ an orthogonal frequency-division multiplexing (OFDM) system. Secondary transceivers communicate with each other through multiple relays to obtain BF gain as well as to suppress the interference between the primary and secondary users who share the same spectrum. We consider two FF-BF design methods to optimize the relay filter. The first method enhances the quality of service of the secondary network by maximizing the worst subcarrier signal-to-interference-plus-noise ratio (SINR) subject to transmit power constraints. The second method suppresses the interference from the secondary network to the primary network through the minimization of the relay transmission power subject to subcarrier SINR constraints. Simulation results show that the proposed FF-BF improves system performance in comparison to amplify-and-forward relay BF.

Nonnegative Matrix Factorization (NMF) with sparseness and smoothness constraints has attracted increasing attention. When these properties are considered, NMF is usually formulated as an optimization problem in which a linear combination of an approximation error term and some regularization terms must be minimized under the constraint that the factor matrices are nonnegative. In this paper, we focus our attention on the error measure based on the Euclidean distance and propose a new iterative method for solving those optimization problems. The proposed method is based on the Hierarchical Alternating Least Squares (HALS) algorithm developed by Cichocki et al. We first present an example to show that the original HALS algorithm can increase the objective value. We then propose a new algorithm called the Gauss-Seidel HALS algorithm that decreases the objective value monotonically. We also prove that it has the global convergence property in the sense of Zangwill. We finally verify the effectiveness of the proposed algorithm through numerical experiments using synthetic and real data.

Extreme learning machine (ELM) has recently attracted many researchers' interest due to its very fast learning speed, good generalization ability, and ease of implementation. However, it has a linear output layer which may limit the capability of exploring the available information, since higher-order statistics of the signals are not taken into account. To address this, we propose a novel ELM architecture in which the linear output layer is replaced by a Volterra filter structure. Additionally, the principal component analysis (PCA) technique is used to reduce the number of effective signals transmitted to the output layer. This idea not only improves the processing capability of the network, but also preserves the simplicity of the training process. Then we carry out performance evaluation and application analysis for the proposed architecture in the context of supervised classification and unsupervised equalization respectively, and the obtained results either on publicly available datasets or various channels, when compared to those produced by already proposed ELM versions and a state-of-the-art algorithm: support vector machine (SVM), highlight the adequacy and the advantages of the proposed architecture and characterize it as a promising tool to deal with signal processing tasks.

Mixed noise removal is a major problem in image processing. Different noises have different properties and it is required to use an appropriate removal method for each noise. Therefore, removal of mixed noise needs the combination of removal algorithms for each contained noise. We aim at the removal of the mixed noise composed of Additive White Gaussian Noise (AWGN) and Random-Valued Impulse Noise (RVIN). Many conventional methods cannot remove the mixed noise effectively and may lose image details. In this paper, we propose a new mixed noise removal method utilizing Direction Weighted Median filter (DWM filter) and Block Matching and 3D filtering method (BM3D). Although the combination of the DWM filter for RVIN and BM3D for AWGN removes almost all the mixed noise, it still loses some image details. We find the cause in the miss-detection of the image details as RVIN and solve the problem by re-detection with the difference of an input noisy image and the output by the combination. The re-detection process removes only salient noise which BM3D cannot remove and therefore preserves image details. These processes lead to the high performance removal of the mixed noise while preserving image details. Experimental results show our method obtains denoised images with clearer edges and textures than conventional methods.

This paper presents convex filter networks that are obtained from extensions of morphological filters. The proposed filter network consists of a convex and concave filter that are extensions of the dilation and erosion of mathematical morphology with the maxout activation function. Maxout can approximate arbitrary convex functions as piecewise linear functions, including the max function. The class of the convex function hence includes the morphological dilation and can be trained for specific image processing tasks. In this paper, the closing filter is extended to a convex-concave filter network with maxout. The convex-concave filter is trained by the stochastic gradient method for noise and mask removal. The examples of noise and mask removal show that the convex-concave filter can obtain a recovered image, whose quality is comparable to inpainting by using the total variation minimization with reduced computational cost without mask information of the corrupted pixels.

Magnetic Anomaly Detection (MAD) is a passive method for the detection of ferromagnetic objects. Currently, the performance of a MAD system is limited by the magnetic background noise that is non-stationary and shows self-similarity and long-range correlation. In this paper, we propose an empirical mode decomposition (EMD) trend filtering based energy detector for adaptively detecting the magnetic anomaly signal from the background noise. The input data is first detrended adaptively with the energy-ratio trend filtering approach. Then, the magnetic anomaly signal is detected using an energy detector. The proposed detector does not need any a priori knowledge about the target or assumptions regarding the background noise. Experiments also prove that the proposed detector shows a more stable performance than the existing undecimated discrete wavelet transform (UDWT) based energy detector.

In this letter, we propose a robust and fast tracking framework by combining local and global appearance models to cope with partial occlusion and pose variations. The global appearance model is represented by a correlation filter to efficiently estimate the movement of the target and the local appearance model is represented by local feature points to handle partial occlusion and scale variations. Then global and local appearance models are unified via the Bayesian inference in our tracking framework. We experimentally demonstrate the effectiveness of the proposed method in both terms of accuracy and time complexity, which takes 12ms per frame on average for benchmark datasets.

We present dynamic mode switching characteristic by using a 2 × 2 optical mode switch based on silicon waveguide. The configuration of optical mode switch is similar to MZI where the width of input and output ports are designed to permit the combining of the fundamental mode and the first order mode. We designed the symmetrical arms with phase shifter based on p-i-n structure in one arm to generate a π-phase difference between each arm. As a result, mode switching with the injection current of 60mA (5.7V) was successfully achieved with the mode crosstalk of -10dB at λ=1550nm. A minimum of less than 60ns and 40ns mode switching time for the fundamental mode to first order mode and first order mode to fundamental mode, was achieved respectively in this time.

With the expected increase in popularity of device-to-device (D2D) services, the importance of implementing an LTE simulator that enables fast and accurate evaluations of D2D related technologies is clear. In this paper, we report on a network simulator, D2dSim, with the aim of realizing an LTE-Advanced network that utilizes the D2D feature, i.e., in which direct transmission between mobile stations (MSs) is enabled. Using NS-3, one of the most popular network simulation platforms, D2dSim could become one of the first realistic open-source D2D-capable environments, providing realistic and standard-compliant implementations of a subset of Proximity-based Services complying with the LTE-A standard.

This paper presents a programmable wideband low pass filter (LPF) with Continuous-Time (CT)/Discrete-Time (DT) hybrid architecture. Unlike the conventional DT LPF, the proposed LPF eliminates sample & hold circuits, enabling to expand available bandwidth. The transfer function and the influence of the circuit imperfection are derived from CT/DT hybrid analysis. A prototype has been fabricated in 40 nm CMOS process. The proposed LPF achieves 2.5 GHz bandwidth by wideband equalization, which offers capacitance ratio (Cratio) and clock frequency (fCK) programmability. The proposed LPF occupies only 0.048 mm2 of active area.