A regulated charge pump (CP) with an extended range of load current is presented. A power-efficient adaptive feedback controller is adopted. Verified by a 0.18µm CMOS technology with a power supply of 3.3V, the measured output voltage of the CP is regulated above 5V when the load current is varied from 2.5mA to 50mA. The measured power efficiency spans from 81.7% at lighter load to 75.2% when load current is 50mA. The measured output ripples are small and below 24mV.

The Lyapunov stability theory-based adaptive filter (LST-AF) is a robust filtering algorithm which the tracking error quickly converges to zero asymptotically. Recently, the software module of the LST-AF algorithm is effectively used in engineering applications such as tracking, prediction, noise cancellation and system identification problems. Therefore, hardware implementation becomes necessary in many cases where real time procedure is needed. In this paper, an implementation of the LST-AF algorithm on Field Programmable Gate Arrays (FPGA) is realized for the first time to our knowledge. The proposed hardware implementation on FPGA is performed for two main benchmark problems; i) tracking of an artificial signal and a Henon chaotic signal, ii) estimation of filter parameters using a system identification model. Experimental results are comparatively presented to test accuracy, performance and logic occupation. The results show that our proposed hardware implementation not only conserves the capabilities of software versions of the LST-AF algorithm but also achieves a better performance than them.

This paper proposes a method of watermarking for digital audio signals based on adaptive phase modulation. Audio signals are usually non-stationary, i.e., their own characteristics are time-variant. The features for watermarking are usually not selected by combining the principle of variability, which affects the performance of the whole watermarking system. The proposed method embeds a watermark into an audio signal by adaptively modulating its phase with the watermark using IIR all-pass filters. The frequency location of the pole-zero of an IIR all-pass filter that characterizes the transfer function of the filter is adapted on the basis of signal power distribution on sub-bands in a magnitude spectrum domain. The pole-zero locations are adapted so that the phase modulation produces slight distortion in watermarked signals to achieve the best sound quality. The experimental results show that the proposed method could embed inaudible watermarks into various kinds of audio signals and correctly detect watermarks without the aid of original signals. A reasonable trade-off between inaudibility and robustness could be obtained by balancing the phase modulation scheme. The proposed method can embed a watermark into audio signals up to 100 bits per second with 99% accuracy and 6 bits per second with 94.3% accuracy in the cases of no attack and attacks, respectively.

This letter proposes a situation-adaptive detection algorithm for the improved efficiency of the detection performance and complexity in the MIMO-OFDM system. The proposed algorithm adaptively uses the QRD-M, DFE, and iterative detection scheme in according to the detection environment. Especially, the proposed algorithm effectively reduces the occurrence probability of error in the successive interference cancellation procedure by the unit of the spatial stream. The simulations demonstrate that the adaptive detection method using the proposed algorithm provides a better trade-off between detection performance and complexity in the MIMO-OFDM system.

This study improves the compression efficiency of Lee's colorization-based coding framework by introducing a novel colorization matrix construction and an adaptive color conversion. Colorization-based coding methods reconstruct color components in the decoder by colorization, which adds color to a base component (a grayscale image) using scant color information. The colorization process can be expressed as a linear combination of a few column vectors of a colorization matrix. Thus it is important for colorization-based coding to make a colorization matrix whose column vectors effectively approximate color components. To make a colorization matrix, Lee's colorization-based coding framework first obtains a base and color components by RGB-YCbCr color conversion, and then performs a segmentation method on the base component. Finally, the entries of a colorization matrix are created using the segmentation results. To improve compression efficiency on this framework, we construct a colorization matrix based on a correlation of base-color components. Furthermore, we embed an edge-preserving smoothing filtering process into the colorization matrix to reduce artifacts. To achieve more improvement, our method uses adaptive color conversion instead of RGB-YCbCr color conversion. Our proposed color conversion maximizes the sum of the local variance of a base component, which resulted in increment of the difference of intensities at region boundaries. Since segmentation methods partition images based on the difference, our adaptive color conversion leads to better segmentation results. Experiments showed that our method has higher compression efficiency compared with the conventional method.

In this letter, a new subband adaptive filter (SAF) which is robust against impulsive noise in system identification is presented. To address the vulnerability of adaptive filters based on the L2-norm optimization criterion to impulsive noise, the robust SAF (R-SAF) comes from the L1-norm optimization criterion with a constraint on the energy of the weight update. Minimizing L1-norm of the a posteriori error in each subband with a constraint on minimum disturbance gives rise to robustness against impulsive noise and the capable convergence performance. Simulation results clearly demonstrate that the proposal, R-SAF, outperforms the classical adaptive filtering algorithms when impulsive noise as well as background noise exist.

In this paper, we first propose ten new discrimination features of SAR images in the moving and stationary target acquisition and recognition (MSTAR) database. The Ada_MCBoost algorithm is then proposed to classify multiclass SAR targets. In the new algorithm, we introduce a novel large-margin loss function to design a multiclass classifier directly instead of decomposing the multiclass problem into a set of binary ones through the error-correcting output codes (ECOC) method. Finally, experiments show that the new features are helpful for SAR targets discrimination; the new algorithm had better recognition performance than three other contrast methods.

This paper proposes the concept of adaptive multi-rate (AMR), which jointly employs switching between two links and adaptive rate on each link, for hybrid free-space optical/radio-frequency (FSO/RF) systems. Moreover, we present the cross-layer design of AMR switching, which is based on both the physical and link layers with an automatic-repeat request (ARQ) scheme. We develop an analytical framework based on a Markov chain model for system performance analysis. System performance metrics, including frame-error rate, goodput and link switching probability, are analytically studied over fading channels. Numerical results quantitatively show how the proposal significantly outperforms conventional ones with physical layer-based design and/or fixed-rate switching operation.

For systems with a delay in the input, the predictor method has been often used in state feedback controllers for system stabilization or regulation. In this letter, we show that for a chain of integrators with even an unknown input delay, a much simpler and memoryless controller is a good candidate for system regulation. With an adaptive gain-scaling factor, the proposed state feedback controller can deal with an unknown time-varying delay in the input. An example is given for illustration.

In this paper, we propose Affine Combination Lattice Algorithm (ACLA) as a new lattice-based adaptive notch filtering algorithm. The ACLA makes use of the affine combination of Regalia's Simplified Lattice Algorithm (SLA) and Lattice Gradient Algorithm (LGA). It is proved that the ACLA has faster convergence speed than the conventional lattice-based algorithms. We conduct this proof by means of theoretical analysis of the mean update term. Specifically, we show that the mean update term of the ACLA is always larger than that of the conventional algorithms. Simulation examples demonstrate the validity of this analytical result and the utility of the ACLA. In addition, we also derive the step-size bound for the ACLA. Furthermore, we show that this step-size bound is characterized by the gradient of the mean update term.

With the development of wireless technologies, wireless relay systems have become a popular topic. To design practical wireless relay systems, link adaptation is an important technique. Because there are both broadcast and multiple access channels in wireless relay systems, link adaptation is difficult to design and hence the optimal throughput is hard to achieve. In this study, a novel method is proposed to maximize the system throughput of wireless relay systems by utilizing the most popular link adaptation methods, adaptive modulation and coding (AMC) and hybrid automatic repeat request (HARQ). The proposed method utilizes the characteristics and operations of AMC and HARQ to adaptively adjust the thresholds for selecting modulation and coding scheme (MCS) to be used. Thus the system can keep tracking the optimal values of the thresholds. Therefore, the system throughput can be maximized. We set up simulations for different relay environment settings, such as different relay HARQ protocols, placements, and multiplexing schemes, to verify the capability of the proposed method. The simulation results show that, compared to the existing method, the proposed method indeed improves system throughput under a variety of relay settings and can be easily applied to different system platforms.

This paper presents a novel CMOS bias topology serving as not only a bias circuit but also an adaptive linearizer for SiGe HBT power amplifier (PA) IC. The novel bias circuit can well keep the base-to-emitter voltage (Vbe) of RF amplifying HBT constant and adaptively increase the base current (Ib) with the increase of the input power. Therefore, the gain compression and phase distortion performance of the PA is improved. A three-stage 5-GHz band PA IC with the novel bias circuit for WLAN applications is designed and fabricated in IBM 0.35µm SiGe BiCMOS technology. Under 54Mbps OFDM signal at 5.4GHz, the PA IC exhibits a measured small-signal gain of 29dB, an EVM of 0.9% at 17dBm output power and a DC current consumption of 284mA.

We address a robust algorithm for the interference-plus-noise covariance matrix reconstruction (RA-INCMR) against random arbitrary steering vector mismatches (RASVMs) of the interferences, which lead to substantial degradation of the original INCMR beamformer performance. Firstly, using the worst-case performance optimization (WCPO) criteria, we model these RASVMs as uncertainty sets and then propose the RA-INCMR to obtain the robust INCM (RINCM) based on the Robust Capon Beamforming (RCB) algorithm. Finally, we substitute the RINCM back into the original WCPO beamformer problem for the sample covariance matrix to formulate the new RA-INCM-WCPO beamformer problem. Simulation results demonstrate that the performance of the proposed beamformer is much better than the original INCMR beamformer when there exist RASVMs, especially at low signal-to-noise ratio (SNR).

This paper describes an evaluation of a temporally stable spectral envelope estimator proposed in our past research. The past research demonstrated that the proposed algorithm can synthesize speech that is as natural as the input speech. This paper focuses on an objective comparison, in which the proposed algorithm is compared with two modern estimation algorithms in terms of estimation performance and temporal stability. The results show that the proposed algorithm is superior to the others in both aspects.

We propose a novel bias-free adaptive beamformer employing an affine projection algorithm with the optimal regularization parameter. The generalized sidelobe canceller affine projection algorithm suffers from a bias of a weight vectors under the condition of no reference signals for output of an array in the beamforming application. First, we analyze the bias in the algorithm and prove that the bias can be eliminated through a large regularization parameter. However, this causes slow convergence at the initial state, so the regularization parameter should be controlled. Through the optimization of the regularization parameter, the proposed method achieves fast convergence without the bias at the steady-state. Experimental results show that the proposed beamformer not only removes the bias but also achieves both fast convergence and high steady-state output signal-to-interference-plus-noise ratio.

This paper proposes a novel blind adaptive array scheme with subcarrier transmission power assignment (STPA) for spectrum superposing in cognitive radio networks. The Eigenvector Beamspace Adaptive Array (EBAA) is known to be one of the blind adaptive array algorithms that can suppress inter-system interference without any channel state information (CSI). However, EBAA has difficulty in suppressing interference signals whose Signal to Interference power Ratio (SIR) values at the receiver are around 0dB. With the proposed scheme, the ST intentionally provides a level difference between subcarriers. At the receiver side, the 1st eigenvector of EBAA is applied to the received signals of the subcarrier assigned higher power and the 2nd eigenvector is applied to those assigned lower power. In order to improve interference suppression performance, we incorporate Beamspace Constant Modulus Algorithm (BSCMA) into EBAA (E-BSCMA). Additionally, STPA is effective in reducing the interference experienced by the primary system. Computer simulation results show that the proposed scheme can suppress interference signals received with SIR values of around 0dB while improving operational SIR for the primary system. It can enhance the co-existing region of 2 systems that share a spectrum.

This paper analyzes the performance of a mobile multihop relay (MMR) system which uses intermediate mobile relay stations (RSs) to increase service coverage area and capacity of a communication system. An analytical framework for an MMR system is introduced, and a scheme for allocating the optimum radio resources to an MMR system is presented. It is very challenging to develop an analytical framework for an MMR system because more than two wireless links should be considered in analyzing the performance of such a system. Here, the joint effect of a finite queue length and an adaptive modulation and coding (AMC) scheme in both a base station (BS) and an RS are considered. The traffic characteristics from BS to RS are analyzed, and a three-dimensional finite-state Markov chain (FSMC) is built for the RS which considers incoming traffic from the BS as well. The RS packet loss rate and the RS average throughput are also derived. Moreover, maximum throughput is achieved by optimizing the amount of radio resources to be allocated to the wireless link between a BS and an RS.

An on-channel repeater (OCR) performing simultaneous reception and transmission at the same frequency is beneficial to improve spectral efficiency and coverage. In an OCR, it is important to cancel the feedback interference caused by imperfect isolation between the transmit and receive antennas, and least mean square (LMS) based adaptive filters are commonly used for this purpose. In this paper, we analyze the performance of the LMS based adaptive feedback canceller in terms of its transient behavior and the steady-state mean square error (MSE). Through a theoretical analysis, we derive iterative equations to compute transient MSEs and provide a procedure to simply evaluate steady-state MSEs for the adaptive feedback canceller. Simulation results performed to verify the theoretical MSEs show good agreement between the proposed theoretical analysis and the empirical results.

Monopulse is a classical technique for radar angle estimation and still adopted for fast angle estimation in phased array antenna. The classical formula can be applied to a 2-dimentional phased array antenna if two conditions---the unbiasedness and the independence of the azimuth and the elevation estimate---are satisfied. However, if the sum and difference beams are adapted to suppress the interference under jamming condition, they can be severely distorted. Thus the difference beams become highly correlated and violate the conditions. In this paper, we show the numerical implementation of the generalized monopulse estimation using the distorted and correlated beams, especially for a subarray configured antenna. Because we use the data from the measured subarray patterns rather than the mathematical model, this numerical method can be easily implemented for the complex array configuration and gives good performance for the uncertainty of the real system.

We aim at constructing adaptive oblivious transfer protocols, enjoying fully simulatable security, from various well-known assumptions such as DDH, d-Linear, QR, and DCR. To this end, we present two generic constructions of adaptive OT, one of which utilizes verifiable shuffles together with threshold decryption schemes, while the other uses permutation networks together with what we call loosely-homomorphic key encapsulation schemes. The constructions follow a novel designing approach called “blind permutation”, which completely differs from existing ones. We then show that specific choices of the building blocks lead to concrete adaptive OT protocols with fully simulatable security in the standard model under the targeted assumptions. Our generic methods can be extended to build universally composable (UC) secure OT protocols, with a loss in efficiency.