The millimeter-wave (mm-wave) band will be a key component of fifth-generation (5G) wireless communication systems. This paper presents radio propagation measurements and analysis investigating the wideband directional channel characteristics of the mm-wave transmission for in-building and urban cellular communication systems in the 28-GHz band. Based on the measurements, we analyze and model the spatio-temporal channel characteristics such as multipath delay, angular statistics, and path loss. In particular we investigate the clustering of the multipath components, and investigate both the intra-cluster and inter-cluster distributions. Based on these investigations, we present a complete channel model suitable for system simulations in the in-building and urban environments.

This study presents analyses of the feasibility for the 28 GHz band with a comprehensive overview of important channel parameters. A channel measurement system with a time synchronisation scheme is also introduced which is a sliding correlator channel sounder using 250 Mcps (Mega‐chips‐per‐second) pseudo‐random noise sequences. The system enables the observation of the behaviour of 28 GHz wave propagation not only to use of forming narrow beams in certain directions (classical narrow beam beamforming) but also omni‐likely. This novel synchronised system makes it possible to analyse the wideband channel characteristics. The outdoor channel measurements are conducted considering various features such as foliage effects, signal outage, path loss and outdoor‐to‐indoor conditions. Furthermore, the spatial channel modelling for omni‐like observations with temporal characteristics is firstly interpreted through analysing the essential channel modelling parameters, including the number of clusters, excess delay, root‐mean‐square (RMS) delay spread, power delay spectrum, and angular spread. In the authors’ measurements, the average number of clusters was 2.41 with standard deviation of 1.44. The average RMS delay spread was 36.06 ns with standard deviation of 46.73 ns. Furthermore, the mean values of the RMS azimuth spreads of the angle of departure and arrival were 6.65° and 24.04°, respectively.

This paper investigates a distributive beamforming scheme for the amplify-and-forward (AF) protocol when the second-order statistics, i.e., the mean and variance, of the channel state information (CSI) are available to relay networks. For maximizing the signal-to-noise ratio (SNR) of a destination node, we derive an analytical solution and the maximum achievable SNR when there is an individual power constraint for each relay. Based on the derived results, a greedy algorithm is proposed to sequentially find beamforming weights. It is shown that the complexity is linear to the number of relays per iteration, and the number of iterations is less than or equal to the number of relays. The necessary condition and sufficient condition are analyzed, respectively, for the proposed algorithm to be optimal. The derived analytical solution and the proposed algorithm generalize the previous results in the literature, which are optimal for particular cases. Simulation results show that the performance of the proposed algorithm is near to that achieved using semidefinite programming (SDP).

This paper expands optimal beamforming with combining from the amplify-and-forward (AF) protocol to the non-orthogonal AF (NAF) protocol for environments with perfect channel state information (CSI) and a sum power constraint. After formulating an optimization problem for maximizing the signal-to-noise ratio (SNR), we propose optimal beamforming and combining vectors. After exhaustive comparison of the optimal beamforming weights with those for the previous results in and the characteristics of the beamforming weights are analyzed according to the protocols and the power constraints. Moreover, it is shown that the optimal combining vector is given succinctly with reduced computational complexity, and that the optimal beamforming could be accomplished using partial CSI. Simulation results verify that the proposed schemes enhance performance.

A new template matching method accelerated by an integral image is proposed. In contrast to the conventional winner-update template matching algorithm, the proposed scheme uses an integral image instead of a block sum pyramid to represent the search area. When an integral image is used, block sums on the lowest level are evaluated very fast. As a result, the speed with which nonbest candidates are rejected is nearly double that of the conventional scheme. Moreover, the proposed scheme needs less memory than the conventional approach to maintain block sums of candidates and can be easily extended to nonsquare (rectangular) template matching.

The candidate position subsampling technique (CPST) basically chooses candidates in a search window at a sampling rate. The 2:1 CPST chooses half the candidates, and then selects one or more candidates that are considered as to be close to the optimal motion vector before conducting a fine search. The fine search is conducted by checking four neighbors of the chosen candidate(s) referred to as winner(s). The CPST can be combined with a fast optimal block-matching algorithm, such as the multilevel successive elimination algorithm (MSEA), in order to reduce the number of computations used in rejecting the nonbest candidate. We propose a new 2:1 CPST fitted to the MSEA. The proposed algorithm adopts a new condition for the winner which helps to find the best candidate efficiently. Moreover, a fast motion estimation step is used to reduce the number of computations of the MSEA, and the peak signal-to-noise ratio (PSNR) compensation step is adopted to guarantee that the PSNR performance of the proposed algorithm is very close to that of the full search. Experimental results show that the proposed algorithm reduces the computational loads of the MSEA by 47.26% on average with only -0.027 dB PSNR degradation in the worst case.

This study presents a limited feedback codebook design for a multiple-input single-output (MISO) beamforming system in a Rician fading channel. To support the Rician fading channel, the physical characteristics of the channel are exploited in designing the codebook by Grassmannian line packing (GLP). To this end, a portion of the total codewords is allocated for supporting the line-of-sight (LOS) channel. By a proposed design procedure, it is possible to design a codebook which can increase the system capacity in a large K-factor region without any capacity loss in a Rayleigh fading channel. The simulation results show that the overall capacity can be remarkably increased by the proposed codebook.

In order to improve bandwidth efficiency and PAPR performance, a new hidden pilot scheme using a precoder is proposed for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. Based on the hidden pilot scheme, it is possible to estimate the channel and reduce the PAPR without bandwidth consumption. We show that the inevitable unknown data interference of the hidden pilot, which degrades the performance of channel estimation, can be successively reduced by the precoder design for each antenna with the aid of an iterative scheme. Computer simulations are presented where the proposed scheme is compared with conventional methods using channel estimation, BER, bandwidth efficiency and PAPR performance.

The successive elimination technique is used widely in the successive elimination algorithm (SEA), the multilevel successive elimination algorithm (MSEA), and the fine granularity successive elimination (FGSE) for fast optimal block-matching motion estimation. The computational cost of a series of these algorithms is primarily affected by a set of lower bounds. In this paper, an efficient scheme to build a set of lower bounds is proposed. This scheme efficiently produces the same set of lower bounds as those of MSEA. Moreover, the optimal number and positions of checking the validity of a candidate block using the proposed scheme is studied. Based on our study, a new algorithm is proposed: the effective successive elimination algorithm (ESEA). Experimental results are given to show the superiority of the proposed algorithm over previous approaches.

In this paper, a new preamble which is constructed with only one OFDM symbol is proposed. Moreover, novel synchronization and cell searching techniques based on the proposed preamble are developed. In proposed algorithm, frame timing and fractional frequency offset estimation are performed in the time domain while the integer frequency offset and cell identification (ID) are estimated in the frequency domain. Each algorithm is designed under a consideration of the estimation error such as the timing error and the residual frequency offset. From the simulation results, it is verified that the proposed synchronization and cell searching schemes are robust to the estimation error and show reliable performance even in a harsh environment.

We study distributed cooperative communication systems in which a single source transmits its information with the help of multiple relays to a destination. Specifically, we consider decode and forward relay networks based on orthogonal frequency division multiplexing (OFDM). Most previous work needs a priori information for antenna allocation to obtain cooperative diversity advantages. A randomized cyclic delay code does not require additional information in order to coordinate relay transmission. We applied randomized cyclic delay code to relay protocols and analyzed its performance. Simulation results show that considerable diversity gain is obtained in cooperative communication systems.

In this paper, we propose a new MIMO-OFDM channel estimator with a phase-shifted pilot (PSP) sequence to enhance the performance and overcome the problems of conventional schemes. The proposed scheme overcomes conventional PSP estimator's limitation of requiring a uniformly distributed pilot position and performs better by adopting a minimum mean square error criterion that cannot be applied to conventional schemes. The proposed PSP channel estimator can perfectly separate multiple channel impulse responses, even though all transmit antennas use the same pilot position. Furthermore, the simulation results show that the performance of the proposed scheme is close to lower bound of the mean square error.

Erasure selection for errors-and-erasures decoding algorithms is investigated and analyzed, where declaring erasures provides additional gain for hard decision decoding. To derive an analytical criterion for optimal erasure selection, we first investigate erasure effects on decoding performance, by which a metric function for erasure selection is derived. From the derived metric, a suboptimal threshold is defined, which can be used for errors and erasures decoding of large code-distance channel codes. Moreover, application to M-ary (M>2) PAM constellation is also described. For verification of the proposed erasure threshold, simulation results with popular channel codes are included.

This paper considers the problem of channel estimation for OFDM systems, where the channels are frequency-and time-selective. Incorporating a Markov model for the time-correlation property of the channel, we propose three optimal channel estimation algorithms in the sense of MMSE; preamble-aided scheme, pilot-symbol-aided modulation (PSAM) scheme and combination of these two schemes. In addition, the reliable decision feedback symbols (RDFS) are exploited to refine the channel estimate, where the RDFS is a decision symbol experiencing a low symbol error rate. Three proposed algorithms taking advantage of RDFS give a more accurate channel estimate and a lower bit error rate. Simulation results verify the proposed algorithms under several channel conditions.

The conventional pilot-aided orthogonal frequency division multiplexing (OFDM) systems use the fixed number of pilots to estimate the channel. In this paper, we propose a new channel estimation scheme that exploits reliable decision-feeback symbols in the OFDM systems. The reliable symbols having low symbol error rate can be used to refine the channel estimate again. The resultant algorithm gives a more accurate channel estimate and lower bit error rate (BER) than the conventional method. The analysis of Cramér Rao lower bound (CRLB) and simulation results verify our claims that the enhanced channel estimation and lower BER can be achieved.

We introduce a new synchronization scheme to improve the synchronization performance in a ultra-wideband (UWB) non-coherent energy collection receiver. Our proposed scheme exploits the mean normalized energy profile, which is known at the receiver, to acquire synchronization. The synchronization process is performed through comparing the energy collected from the received signal with the mean normalized energy profile and correcting the timing error. The synchronization performance is investigated in terms of the normalized mean squared synchronization error (NMSSE) in IEEE 802.15.3a UWB indoor channel environment. Through simulation results, we show that the proposed scheme enhances the synchronization performance.

This paper considers the problem of synchronization in frequency hopping systems. A simple digital signal processing block along with the existing RF circuits forms a phase detector that generates a signal corresponding to the phase difference between the hop timings of the local and received signals. The two hop-timing acquisition algorithms proposed in this paper - based on energy detection - utilize the phase detector and result in low-complexity implementations. In the first one, a simple cost function relying on the power sum definition estimates the hop timing. This estimator allows for only a limited acquisition range. Based on this study, we propose a hop-timing estimator with a full acquisition range which still maintains low-complexity. Furthermore, this paper analyzes the optimal threshold to detect the signal existence based on the maximum likelihood detection rule.

Low-complexity rapid timing acquisition is one of the most pivotal challenges in ultra-wideband (UWB) wireless technology whose short duration pulse results in high resolution in time. In this paper, we propose a new preamble which can reduce the performance degradation caused by diminishing the operational complexity of the coarse timing acquisition. In the reduced-complexity acquisition algorithm, the received preamble is shortened by summing its elements group-by-group and correlated with the known PN sequence having reduced length to find the maximum output value of the correlators. This acquisition algorithm introduces performance deterioration since it loses the impulsive autocorrelation property of the PN sequence after summation. Therefore, we judiciously design a new preamble sequence whose slide correlator output function shows a distinct peak at zero delay and the symmetry even after summation. Simulation results demonstrate that the reduced-complexity acquisition algorithm exploiting the proposed preamble outperforms the algorithm using the PN sequence as the preamble, while the amount of computational reduction remains the same

A new scheme is proposed to optimally reduce the modulation modes for bit and power allocation algorithm in multi-carrier transmissions. By reducing the modulation modes, computational load and hardware complexity can be reduced without any performance degradation. When modulation modes for rectangular QAM are available at a transmitter, it is shown that the modulation modes for rectangular QAM can be reduced to those for square QAM which is the subset of rectangular QAM. After identifying a power allocation property of rectangular QAM, it is proved that the optimal allocation with square QAM has exactly the same performance as that with rectangular QAM. Numerical results show the reduction of computational load and verify our theoretic presentations.

In this paper, we propose a new antenna selection algorithm with low complexity for multiple-input multiple-output (MIMO) wireless systems. We consider the selection only at the receiver (i.e., the transmitter employs the same number of RF chains as antenna elements, whereas the receiver utilizes a reduced number of RF chains). The selection goal is to maximize the channel capacity. We present the selection algorithm based on the norm and uncorrelation between rows of the channel matrix. Our algorithm requires low computational complexity and provides excellent performance. In the specific case, the proposed scheme shows near-optimal performance. We present simulation results that validate our algorithm and analysis.

We design pilot-symbol-assisted modulation for carrier frequency offset (CFO) and channel estimation in orthogonal frequency-division multiplexing transmissions over multi-input multi-output frequency-selective fading channels. The CFO and channel-estimation tasks rely on null-subcarrier and nonzero pilot symbols that we insert and hop from block to block. Because we separate CFO and channel estimation from symbol detection, the novel training patterns lead to further decoupled CFO and channel estimators. The performance of our algorithms is investigated analytically, and then compared with an existing approach by simulations.

We aim at increasing the throughput of the hybrid automatic retransmission request (HARQ) protocol in space-time (ST) coded multi-antenna transmission systems. By utilizing reliability information at the decoder, we obtain an improved probability of successful decoding, which enhances the overall system throughput at low complexity. Simulations and analytical results demonstrate the performance of our scheme in AWGN and fading multi-input multi-output (MIMO) channels.

In this paper, a novel profile verification scheme based on the ear, contour lines and feature points from head profile images is proposed. From the side image of a human head taken by a CCD camera, the contour line of the image is extracted by the simple filling method and morphological filtering. Based on the reference coordinate set by using ear images enrolled in the database a priori, the features of the contour line such as the tip of the nose, bottom of the nose, eye point and so on are extracted. The contour of the given image is divided into segments by utilizing the extracted feature points. The directional code of each segment is proposed and the length of the segment is computed for generating the feature vector. The verification of the given profile is performed by matching these feature vectors with those of the enrolled database. The experimental results show validity of the developed method for feature extraction and profile verification.

We design pilot symbol assisted modulation for carrier frequency offset (CFO) and channel estimation in orthogonal frequency division multiplexing (OFDM) transmissions over multiinput multioutput (MIMO) frequency-selective fading channels. By separating CFO and channel estimation from symbol detection, the novel training patterns lead to low-complexity CFO and channel estimators. The performance of our algorithms is investigated analytically, and then compared with an existing approach by simulations.

Using a Kalman filter, we estimate a DS-CDMA channel described by Rayleigh fading. A Kalman filter is proposed for the time varying channel estimation. The proposed scheme is constructed without bit estimation, that is, neither training sequence nor estimated bit symbol is used for channel estimation. We verify the performance of the channel estimation scheme with simulation results.

We propose a new intelligent blind source separation algorithm for the mixture of sub-Gaussian and super-Gaussian sources. The algorithm consists of an update equation of the separating matrix and an adjustment equation of nonlinear functions. The weighted sum of two nonlinear functions is adapted to obtain the proper nonlinear function for each source. To verify the validity of the proposed algorithm, we compare the result with that of algorithms with one fixed nonlinear function, and that of the extant methods.

In the speech processing system, detection of a single speech from composite signals is required. To obtain the single speech, we propose an algorithm which can detect multi-pitch in the frame processing. The algorithm does not require the condition that the overlapped peaks should be analyzed into each speaker's peaks. The proposed algorithm produces pitch candidates for each speech such that the pitches are not correlated and are accurate below the FFT frequency unit. We show that the proposed algorithm works properly in the case of two speaker speech signals.

We propose a novel fast learning algorithm in neural networks. The conventional backpropagation algorithm suffers from slow convergence due to weight oscillations at a narrow valley in the error surface. To overcome this difficulty we derive a new gradient term by modifying the original gradient term with an estimated downward direction at a valley. Simulation results show that the proposed method reduces oscillations considerably and achieves fast convergence.

A generalized diagonal recurrent neural network (GDRNN) and its learning algorithm for dynamic systems are proposed. The hidden nodes of the GDRNN have recurrent weights to capture the dynamic characteristics of the given nonlinear systems. The GDRNN with the proposed learning algorithm gives faster learning speed and better convergence properties than the conventional diagonal recurrent neural network (DRNN). In computer simulations, the performance of the GDRNN is compared with that of the conventional neural network.

An adaptive fuzzy logic controller (FLC) is designed for plants with unknown and/or time-varying dead zones. The steady-state control resolutions with perturbing action, which are different from the ones in the transient states, are used to cancel out the unknown and/or time-varying dead-zone effects. Automatically adjusted control resolutions play a key role as a fuzzy dead-zone inverse. The control resolutions of the control input variables are dependent on the scaling gains of the variables. Therefore, we can develop the fuzzy dead-zone inverse by reperturbing and adjusting the scaling gains adequately in the steady-states. The developed fuzzy logic controllers that are applied to the plants with unknown dead zones ensure their effectiveness even though the dead-zone characteristics are time varying.

This paper presents a statistical behavior analysis of a sign-sign least mean square algorithm, which is obtained by clipping both the reference input signal and the estimation error, for adaptive filters with correlated Gaussian data. The study focuses on the derivation of expressions for the first and second moment behavior of the filter coefficient vector and analysis of the filter mean square error. The previous analysis of this type for the sign-sign algorithm is based on the assumption that the input sequence to the adaptive filter is independent, identically distributed Gaussian, but this restriction is removed in our analysis. Theoretical expressions derived are verified numerically through computer simulations for an example of system identification.