Aiming at the problem of “energy hole” caused by random distribution of nodes in large-scale wireless sensor networks (WSNs), this paper proposes an adaptive energy-efficient balanced uneven clustering routing protocol (AEBUC) for WSNs. The competition radius is adaptively adjusted based on the node density and the distance from candidate cluster head (CH) to base station (BS) to achieve scale-controlled adaptive optimal clustering; in candidate CHs, the energy relative density and candidate CH relative density are comprehensively considered to achieve dynamic CH selection. In the inter-cluster communication, based on the principle of energy balance, the relay communication cost function is established and combined with the minimum spanning tree method to realize the optimized inter-cluster multi-hop routing, forming an efficient communication routing tree. The experimental results show that the protocol effectively saves network energy, significantly extends network lifetime, and better solves the “energy hole” problem.

This study proposes a Peak-to-Average Power Ratio (PAPR) reduction method using an adaptive Finite Impulse Response (FIR) filter in Orthogonal Frequency Division Multiplexing systems. At the transmitter, an iterative algorithm that minimizes the p-norm of a transmitted signal vector is used to update the weight coefficients of the FIR filter to reduce PAPR. At the receiver, the FIR filter used at the transmitter is estimated using pilot symbols, and its effect can be compensated for by using an equalizer for proper demodulation. Simulation results show that the proposed method is superior to conventional methods in terms of the PAPR reduction and computational complexity. It also shows that the proposed method has a trade-off between PAPR reduction and bit error rate performance.

This paper proposes a partial transmit sequences (PTS)-based PAPR reduction method and a phase factor estimation method without side information for OFDM systems with QPSK and 16QAM modulation. In the transmitter, an iterative algorithm that minimizes the p-norm of a transmitted signal determines phase factors to reduce PAPR. Unlike conventional methods, the phase factors are allowed to take continuous values in a limited range. In the receiver, the phase factor is blindly estimated by evaluating the phase differences between the equalizer's output and its closest constellation points. Simulation results show that the proposed PAPR reduction method is more computationally efficient than the conventional PTS. Moreover, the combined use of the two proposed methods achieves a satisfactory tradeoff between PAPR and BER by limiting the phase factors properly.

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.

This paper proposes an adaptive comb filter with flexible notch gain. It can appropriately remove a periodic noise from an observed signal. The proposed adaptive comb filter uses a simple LMS algorithm to update the notch gain coefficient for removing the noise and preserving a desired signal, simultaneously. Simulation results show the effectiveness of the proposed comb filter.

In this paper, we propose a normalization method dividing the gradient vector by the sum of the diagonal and two adjoining elements of the matrix expressing the correlation between the components of the discrete Fourier transform (DFT) of the reference signal used for the identification of unknown system. The proposed method can thereby improve the estimation speed of coefficients of adaptive filter.

This paper proposes an adaptive algorithm for adaptive arrays that minimizes the bit error rate (BER) of the array output signals in radio communication systems with the use of multilevel modulation signals. In particular, amplitude phase shift keying (APSK) is used as one type of multilevel modulations in this paper. Simultaneous non-linear equations that are satisfied by the optimum weight vector of the proposed algorithm are derived and used for theoretical analyze of the performance of the adaptive array based on the proposed algorithm. As a result of the theoretical analysis, it can be shown that the proposed adaptive array improves the carrier to interference ratio of the array output signal without taking advantage of the nulls. Furthermore, it is confirmed that the result of the theoretical analysis agrees with that of computer simulation. When the number of the received antenna is less than that of the received signals, the adaptive array based on the proposed algorithm is verified to achieve much better performance then that based on the least mean square (LMS) algorithm.

This paper presents an adaptive FFE/DFE receiver with an algorithm that measures the data-dependent jitter. The proposed adaptive algorithm determines the compensation level by measuring the input data-dependent jitter. The adaptive algorithm is combined with a clock and data recovery phase detector. The receiver is fabricated in with 0.13 µm CMOS technology, and the compensation range of equalization is up to 26 dB at 2 GHz. The test chip is verified for a 40 inch FR4 trace and a 53 cm flexible printed circuit channel. The receiver occupies an area of 440 µm 520 µm and has a power dissipation of 49 mW (excluding the I/O buffers) from a 1.2 V supply.

Numerous noise suppression methods for speech signals have been developed up to now. In this paper, a new method to suppress noise in speech signals is proposed, which requires a single microphone only and doesn't need any priori-information on both noise spectrum and pitch. It works in the presence of noise with high amplitude and unknown direction of arrival. More specifically, an adaptive noise suppression algorithm applicable to real-life speech recognition is proposed without assuming the Gaussian white noise, which performs effectively even though the noise statistics and the fluctuation form of speech signal are unknown. The effectiveness of the proposed method is confirmed by applying it to real speech signals contaminated by noises.

We study problems in computational geometry from the viewpoint of adaptive algorithms. Adaptive algorithms have been extensively studied for the sorting problem, and in this paper we generalize the framework to geometric problems. To this end, we think of geometric problems as permutation (or rearrangement) problems of arrays, and define the "presortedness" as a distance from the input array to the desired output array. We call an algorithm adaptive if it runs faster when a given input array is closer to the desired output, and furthermore it does not make use of any information of the presortedness. As a case study, we look into the planar convex hull problem for which we discover two natural formulations as permutation problems. An interesting phenomenon that we prove is that for one formulation the problem can be solved adaptively, but for the other formulation no adaptive algorithm can be better than an optimal output-sensitive algorithm for the planar convex hull problem. To further pursue the possibility of adaptive computational geometry, we also consider constructing a kd-tree.

We provide an efficient transmission scheme which embeds a pilot signal in the data signal for channel state information (CSI) based on the configuration of a multiple-input multiple-output (MIMO) system using space-time block coding (STBC) with an adaptive array (AA). A computer simulation and analysis show that the proposed scheme, which combines the advantage of an Alamouti-like STBC scheme and the pilot-based AA, can suppress the irreducible error due to random FM noise. The proposed scheme using a pilot minimizes the decoding delay, and is highly robust against fast fading. We show that the proposed scheme can significantly increase the data transmission rate by using the transmitter diversity based on STBC, and the accuracy of the proposed technique is exemplified by a computer simulation.

We propose the multi-domain adaptive learning that enables us to find a point meeting possibly time-varying specifications simultaneously in multiple domains, e.g. space, time, frequency, etc. The novel concept is based on the idea of feasibility splitting -- dealing with feasibility in each individual domain. We show that the adaptive projected subgradient method (Yamada, 2003) realizes the multi-domain adaptive learning by employing (i) a projected gradient operator with respect to a ‘fixed’ proximity function reflecting the time-invariant specifications and (ii) a subgradient projection with respect to ‘time-varying’ objective functions reflecting the time-varying specifications. The resulting algorithm is suitable for real-time implementation, because it requires no more than metric projections onto closed convex sets each of which accommodates the specification in each domain. A convergence analysis and numerical examples are presented.

We introduce a novel configuration for a multi-user Multiple-Input Multiple-Output (MIMO) system in mobile communication over fast fading channels using space-time block coding (STBC) and adaptive array. The proposed scheme adopts the simultaneous transmission of data and pilot signals which reduces control errors caused by delay of obtaining channel state information (CSI). Data and pilot signals are then encoded using a space-time block code and are transmitted from two transmit antennas. In order to overcome the fast fading problem, implementation of adaptive array using recursive least squares (RLS) algorithms is considered at the base station. Through computer simulation, it is shown that the proposed scheme in this way can overcome Doppler spread in higher frequencies and suppress co-channel interference up to N-1 users for N receiving antennas.

MC-CDMA is an attractive multi-access method for the next generation high-speed mobile communication systems. The uplink transmission performance is limited by the multi-access interference (MAI) from other users since all users share the same bandwidth. Adaptive antenna array can be used to suppress the MAI and to improve the uplink transmission performance. In this paper, we propose a frequency-domain adaptive antenna array for multi-code MC-CDMA. The proposed frequency-domain adaptive antenna array uses a simple normalized LMS (NLMS) algorithm. Although the NLMS algorithm is used, very fast weight convergence within one MC-CDMA symbol duration is achieved since the weight updating is possible as many times as the number of subcarriers within one MC-CDMA symbol duration.

In this paper, we propose an adaptive algorithm based on accumulated signal processing, which could be applicable to Post-FFT-type OFDM adaptive array antennas. Proposed scheme calculates the weight of each element at a particular instant t, by considering both post- and pre-received symbols. Because of the use of additional forthcoming information on channel behavior in the weight calculation scheme, one can expect an improved performance in fast fading conditions by using the proposed adaptive algorithm. This paper also discusses the application of the proposed adaptive algorithm to OFDM adaptive array. In OFDM application, a few subchannels are being used to transmit pilot symbols, and at the receiver, the proposed adaptive algorithm is applied to those pilot subchannels, and interpolates the weights for the data subchannels which are allocated between the pilot subchannels. Finally, the system performance improvement with the application of the proposed adaptive algorithm is verified by computer simulation.

This paper proposes a simple method for estimation and compensation of signal direction, to deal with relative change of sound source location caused by the movements of a microphone array and a sound source. This method introduces a delay filter that has shifted and sampled sinc functions. This paper presents a concept for the joint optimization of arrival time differences and of the coordinate system of a mobile microphone array. We use the LMS algorithm to derive this method by maintaining a certain relationship between the directions of the microphone array and the sound source directions. This method directly estimates the relative directions of the microphone array to the sound source directions by minimizing the relative differences of arrival time among the observed signals, not by estimating the time difference of arrival (TDOA) between two observed signals. This method also compensates the time delay of the observed signals simultaneously, and it has a feature to maintain that the output signals are in phase. Simulation results support effectiveness of the method.

In this paper, we propose a robust adaptive algorithm for impulsive noise suppression. The perturbation of the input signal as well as the perturbation of the estimation error are restricted by M-estimation. The threshold used in M-estimation is obtained from the proposed adaptive variance estimation. Simulations show that the proposed algorithm is less vulnerable to the impulsive noise than the conventional algorithm.

The main issue in real time voice applications over Internet is to investigate a lossless playout without jitter while maintaining playout delay as small as possible. Existing playout algorithms estimate network delay by using timestamps and determine the playout schedule only at the beginning of each talkspurt. Also their scheduled playout time is determined based on a fixed upper playout delay bound over a talkspurt. The sliding adaptive playout algorithm we propose can estimate jitter without using timestamps and its playout time is allowed to slide to a certain extent. The aim of sliding playout schedule is to determine the scheduled playout time at the beginning of each talkspurt based on the playout delay expected under the normal condition where the degree of actual jitter is below the magnitude which is not quite large in relation to variations in the "baseline" delays. Then the proposed algorithm can be effectively applied to minimize the scheduled playout delay while improving the voice quality against a spike which may occur at the beginning of a talkspurt as well as a spike which occurs in the middle of a talkspurt. We develop an analytical model of the general adaptive playout algorithms and analyze the playout buffer performance for different degrees of jitter, different values of the scheduled playout delay, different maximum lengths of delay spikes, and arbitrary tolerable ranges of sliding. Based on the analytical results, we suggest the specific values of parameters used in the sliding algorithm.

OFDM is a good scheme to transmit high rate data under a multi-path environment. With a sufficiently long guard interval (GI), it is possible to totally eliminate interference between symbols or carriers with OFDM. However, long guard intervals reduce the spectrum efficiency of OFDM. Thus, shortening the guard interval as much as possible is highly desirable. As short guard intervals will usually result in interference in an OFDM system, an interference canceller would be necessary to enable the use of short guard intervals without unduly degrading system performance. This paper presents a possible adaptive interference cancellation scheme for OFDM to help attain this objective.

Weight divided adaptive control method for a microwave FeedForward Power Amplifier (FFPA) is presented. In this adaptive controller, an output signal of a power amplifier is used as reference signal. Additionally, reference signal is divided by the weight of adaptive filter, so that characteristics of the power amplifier, such as temperature dependence, do not have influence on the convergence performances. The proposed adaptive algorithm and the convergence condition are derived analytically and we clarify that the proposed weight divided adaptive algorithm is more stable than the conventional Normalized Least Mean Square (NLMS) algorithm. Then, the convergence condition considering phase calibration error is discussed. The effectiveness of the proposed algorithm are also verified by the nonlinear simulations of the FFPA having AM-AM and AM-PM nonlinearity of GaAsFET.