This study deals with two linear precoders: the maximization of the minimum Euclidean distance between received symbol-vectors, called here max-dmin, and the maximization of the post-processing signal-to-noise ratio termed max-SNR or beamforming. Both have been designed for reliable MIMO transmissions operating over uncorrelated Rayleigh fading channels. Here, we will explain why performances in terms of bit error rates show a significant enhancement of the max-dmin over the max-SNR whenever the number of antennas is increased. Then, from theoretical developments, we will demonstrate that, like the max-SNR precoder, the max-dmin precoder achieves the maximum diversity order, which is warrant of reliable transmissions. The current theoretical knowledge will be applied to the case-study of a system with two transmit- or two receive-antennas to calculate the probability density functions of two channel parameters directly linked to precoder performances for uncorrelated Rayleigh fading channels. At last, this calculation will allow us to quickly get the BER of the max-dmin precoder further to the derivation of a tight semi-theoretical approximation.

This paper introduces an adaptive low complexity pre-processing filter to improve the coding performance of seriously degraded video sequences that is caused by the additive noise. The additive noise leads to a decrease in coding performance due to the high frequency components. By incorporating local statistics and quantization parameter into filtering process, the spurious noise is significantly attenuated and coding efficiency is improved for given quantization step size. In order to reduce the complexity of the pre-processing filter, the simplified local statistics and quantization parameter are introduced. The simulation results show the capability of the proposed algorithm.

This paper proposes a new partial channel state information (CSI) reporting method for spatial scheduling in TDD/MIMO systems. In the proposed method, a terminal transmits pilot signals using transmit beams which have large channel gains between the base station (BS) and the terminal. Then, the BS can obtain partial CSI through responses of the pilot signals. Furthermore, adaptive allocation of pilot signals is proposed, in which pilot signals for CSI reporting are adaptively allocated to terminals depending on the number of terminals. We evaluate system throughput of spatial scheduling under the partial CSI reporting from multiple terminals. Numerical results show that the proposed method reduces uplink signalling for CSI reporting effectively, keeping high system throughput of spatial scheduling.

We address pilot-aided channel estimation for a flat-fading spatially-correlated MIMO system, which employing Uniform Linear Arrays (ULA) on dual side and working in sparse scattering (multipath) environment. In case of sparse scattering, channel matrix and spatial correlation of flat-fading MIMO systems are parameterized by structure of multipaths, which is represented as Direction of Arrivals (DOAs), Direction of Departures (DODs) and complex path fading of each path. Based on this and block-fading property of channel, we design a channel estimation method via estimating multipath parameters using ESPRIT-like DOA-Matrix method which exploits shift-invariance property of ULA. The proposed method is able to obtain improved Mean-Square-Error performance than Least-Square method without prior information of spatial correlation.

This paper addresses the problem of maximizing the protocol capacity of 802.11e networks, under the assumption that each access category (AC) has the same packet length. We prove that the maximal protocol capacity can be achieved at an optimal operating point with the medium idle probability of , where Tc* is the duration of collision time in terms of slot unit. Our results indicate that the optimal operating point is independent of the number of stations and throughput ratio among ACs, which means the proposed analytical results still hold even when throughput ratio and station number are time-varying. Further, we show that the maximal protocol capacity can be achieved in saturated cases by properly choosing the protocol parameters. We present a parameter configuration algorithm to achieve both efficient channel utilization and proportional fairness in IEEE 802.11e EDCA networks. Extensive simulation and analytical results are presented to verify the proposed ideas.

In this paper, we study multi-collision probability. For a hash function H :D R with |R|=n, it has been believed that we can find an s-collision by hashing Q=n(s-1)/s times. We first show that this probability is at most 1/s! for any s, which is very small for large s (for example, s=n(s-1)/s). Thus the above folklore is wrong for large s. We next show that if s is small, so that we can assume Q-s ≈ Q, then this probability is at least 1/s!-1/2(s!)2, which is very high for small s (for example, s is a constant). Thus the above folklore is true for small s. Moreover, we show that by hashing (s!)1/sQ+s-1 (≤ n) times, an s-collision is found with probability approximately 0.5 for any n and s such that (s!/n)1/s ≈ 0. Note that if s=2, it coincides with the usual birthday paradox. Hence it is a generalization of the birthday paradox to multi-collisions.

Software rejuvenation is a preventive and proactive solution that is particularly useful for counteracting the phenomenon of software aging. In this article, we consider periodic software rejuvenation models based on the expected cost per unit time in the steady state under discrete-time operation circumstance. By applying the discrete renewal reward processes, we describe the stochastic behavior of a telecommunication billing application with a degradation mode, and determine the optimal periodic software rejuvenation schedule minimizing the expected cost. Similar to the earlier work by the same authors, we develop a statistically non-parametric algorithm to estimate the optimal software rejuvenation schedule, by applying the discrete total time on test concept. Numerical examples are presented to estimate the optimal software rejuvenation schedules from the simulation data. We discuss the asymptotic behavior of estimators developed in this paper.

Visual tracking is required by many vision applications such as human-computer interfaces and human-robot interactions. However, in daily living spaces where such applications are assumed to be used, stable tracking is often difficult because there are many objects which can cause the visual occlusion. While conventional tracking techniques can handle, to some extent, partial and short-term occlusion, they fail when presented with complete occlusion over long periods. They also cannot handle the case that an occluder such as a box and a bag contains and carries the tracking target inside itself, that is, the case that the target invisibly moves while being contained by the occluder. In this paper, to handle this occlusion problem, we propose a method for visual tracking by a particle filter, which switches tracking targets autonomously. In our method, if occlusion occurs during tracking, a model of the occluder is dynamically created and the tracking target is switched to this model. Thus, our method enables the tracker to indirectly track the "invisible target" by switching its target to the occluder effectively. Experimental results show the effectiveness of our method.

Image Registration can be seen as an optimization problem to find a cost function and then use an optimization method to get its minimum. Normalized mutual information is a widely-used robust method to design a cost function in medical image registration. Its calculation is based on the joint histogram of the fixed and transformed moving images. Usually, only a discrete joint histogram is considered in the calculation of normalized mutual information. The discrete joint histogram does not allow the cost function to be explicitly differentiated, so it can only use non-gradient based optimization methods, such as Powell's method, to seek the minimum. In this paper, a parzen-window based method is proposed to estimate the continuous joint histogram in order to make it possible to derive the close form solution for the derivative of the cost function. With this help, we successfully apply the gradient-based optimization method in registration. We also design a new kernel for the parzen-window based method. Our designed kernel is a second order polynomial kernel with the width of two. Because of good theoretical characteristics, this kernel works better than other kernels, such as a cubic B-spline kernel and a first order B-spline kernel, which are widely used in the parzen-window based estimation. Both rigid and non-rigid registration experiments are done to show improved behavior of our designed kernel. Additionally, the proposed method is successfully applied to a clinical CT-MR non-rigid registration which is able to assist a magnetic resonance (MR) guided microwave thermocoagulation of liver tumors.

This paper presents batch processing protocols for efficiently proving a great deal of partial knowledge. These protocols reduce the computation and communication costs for a MIX-net and secure circuit evaluation. The efficiency levels of the proposed protocols are estimated based on the implementation results of a secure circuit evaluation with batch processing.

Let G =(V, E) be an undirected simple graph with u ∈ V. If there exist any two vertices in G whose distance becomes longer when a vertex u is removed, then u is defined as a hinge vertex. Finding the set of hinge vertices in a graph is useful for identifying critical nodes in an actual network. A number of studies concerning hinge vertices have been made in recent years. In a number of graph problems, it is known that more efficient sequential or parallel algorithms can be developed by restricting classes of graphs. In this paper, we shall propose a parallel algorithm which runs in O(log n) time with O(n/log n) processors on EREW PRAM for finding all hinge vertices of a circular-arc graph.

This paper presents a self-reconfigurable adaptive FIR filter system design using dynamic partial reconfiguration, which has flexibility, power efficiency, advantages of configuration time allowing dynamically inserting or removing adaptive FIR filter modules. This self-reconfigurable adaptive FIR filter is responsible for providing the best solution for realization and autonomous adaptation of FIR filters, and processes the optimal digital signal processing algorithms, which are the low-pass, band-pass and high-pass filter algorithms with various frequencies, for noise removal operations. The proposed stand-alone self-reconfigurable system using Xilinx Virtex4 FPGA and Compact-Flash memory shows the improvement of configuration time and flexibility by using the dynamic partial reconfiguration techniques.

Assuming there are short time periods in which only one source is active, a new approach for source separation is proposed. An affine projection adaptation algorithm with a non-orthogonal constraint shows excellent noise immunity, a high convergence rate, and good tracking capability to efficiently obtain a solution to the separation filters.

A parametric linear filter for a linear observation model usually requires a parameter selection process so that the filter achieves a better filtering performance. Generally, criteria for the parameter selection need not only the filtered solution but also the filter itself with each candidate of the parameter. Obtaining the filter usually costs a large amount of calculations. Thus, an efficient algorithm for the parameter selection is required. In this paper, we propose a fast parameter selection algorithm for linear parametric filters that utilizes a joint diagonalization of two non-negative definite Hermitian matrices.

In these days, many dynamically reconfigurable architectures have been introduced to fill the gap between ASICs and software-programmed processors such as GPPs and DSPs. These reconfigurable architectures have shown to achieve higher performance compared to software-programmed processors. However, reconfigurable architectures suffer from a significant reconfiguration overhead and a speedup limitation. By reducing the reconfiguration overhead, the overall performance of reconfigurable architectures can be improved. Therefore, we will describe temporal partitioning, which are able to amortize the reconfiguration overhead at synthesis phase or compilation time. Our temporal partitioning methodology splits a configuration context into temporal partitions to amortize reconfiguration overhead. And then, we will present benchmark results to demonstrate the effectiveness of our methodology.

In this paper, we propose a new code set which has very low spectral peak to average ratio (SPAR) and good correlation properties for DS-UWB. The codes which have low SPAR are suitable for DS-UWB system which operates in UWB (3.110.4 GHz) because they can utilize more power than high SPAR codes can do. And, in order to reduce inter symbol interference (ISI) and inter piconet interferences, the codes which have good auto- and cross-correlation properties must be used. In this paper, we propose three items; (1) a new code generation method which can generate good SPAR and auto-correlation codes, (2) code selection criteria, and (3) a code set, which has been selected according to the proposed selection criteria. The proposed code set has SPAR reduced about 0.22 dB and GMF improved by 30% compared to the previous code set while it is maintaining almost same cross-correlation properties. Each code of the proposed code set, therefore, has gained 1.43 dB SIR on an average compared to that of the previous code set.

This study presents a class of miniature parallel-coupled bandpass filters with good selectivity and stopband rejection. Capacitive terminations are introduced to the conventional anti-parallel coupled-lines, and lumped-element K-inverters are employed, to achieve both size reduction and spurious suppression. Additionally, the capacitive cross-coupling effect can be introduced to obtain three transmission zeros to enhance the selectivity. Suitable equivalent-circuit models, along with design formulae, are also established. Specifically, via design examples, this work demonstrates the feasibility of proposed filter structures in microstrip configuration. Compared to the conventional parallel-coupled filters, the proposed filters exhibit over 60% size reduction, improved selectivity, and wider stopbands up to four times the center frequency.

Extracting frequently executed (hot) portions of the application and executing their corresponding data flow graph (DFG) on the hardware accelerator brings about more speedup and energy saving for embedded systems comprising a base processor integrated with a tightly coupled accelerator. Extending DFGs to support control instructions and using Control DFGs (CDFGs) instead of DFGs results in more coverage of application code portion are being accelerated hence, more speedup and energy saving. In this paper, motivations for extending DFGs to CDFGs and handling control instructions are introduced. In addition, basic requirements for an accelerator with conditional execution support are proposed. Then, two algorithms are presented for temporal partitioning of CDFGs considering the target accelerator architectural constraints. To demonstrate effectiveness of the proposed ideas, they are applied to the accelerator of a reconfigurable processor called AMBER. Experimental results approve the remarkable effectiveness of covering control instructions and using CDFGs versus DFGs in the aspects of performance and energy reduction.

This paper addresses parallel prefix adder synthesis which targets area minimization under given bitwise timing constraints. This problem is treated as a problem to synthesize prefix graphs which represent global structures of parallel prefix adders at technology-independent level, and a two-folded algorithm to minimize area of prefix graphs is proposed. The first process is dynamic programming based area minimization (DPAM), which focuses on a specific subset of prefix graphs and finds an exact minimum solution for the subset by dynamic programming. The subset is defined by imposing some restrictions on structures of prefix graphs. By utilizing these restrictions, DPAM can find the minimum solutions efficiently for practical bit width. The second process is area reduction with re-structuring (ARRS), which removes the imposed restrictions on structures, and restructures the result of DPAM for further area reduction while satisfying timing constraints. Experimental results show that smaller area can be achieved compared to existing methods both at prefix graph level and at gate level.

FeedForward (FF-) Blind Source Separation (BSS) systems have some degree of freedom in the solution space. Therefore, signal distortion is likely to occur. First, a criterion for the signal distortion is discussed. Properties of conventional methods proposed to suppress the signal distortion are analyzed. Next, a general condition for complete separation and distortion-free is derived for multi-channel FF-BSS systems. This condition is incorporated in learning algorithms as a distortion-free constraint. Computer simulations using speech signals and stationary colored signals are performed for the conventional methods and for the new learning algorithms employing the proposed distortion-free constraint. The proposed method can well suppress signal distortion, while maintaining a high source separation performance.