Let G(s)=C(sI - A)-1B+D be a given system where entries of A,B,C,D are polynomials in a parameter k. Then H∞ norm || G(s) ||∞ of G(s) is a function of k, and [9] presents an algorithm to express 1/(||G(s) ||∞)2 as a root of a bivariate polynomial, assuming feedthrough term D to be zero. This paper extends the algorithm in two ways: The first extension is the form of the function to be expressed. The extended algorithm can treat, not only H∞ norm, but also functions that appear in the celebrated KYP Lemma. The other extension is the range of the frequency. While H∞ norm considers the supremum of the maximum singular value of G(i ω) for the infinite range 0 ≤ω ≤ ∞ of ω, the extended algorithm treats the norm for the finite frequency range ω ≤ ω ≤ ω- (ω, ω- ∈ R ∪ ∞). Those two extensions allow the algorithm to be applied to wider area of control problems. We give illustrative numerical examples where we apply the extended algorithm to the computation of the frequency-restricted norm, i.e., the supremum of the maximum singular value of G(i ω) (ω- ≤ ω ≤ ω-).

According to a new kind of permanent contactor, this paper analyses the dynamic behavior of the contactor with and without current-feedback system. And it presents a method to obtain the dynamic characteristics of the contactor with current-feedback system. The experiments prove that the method is correct. Then, it compares the contactor without current-feedback system with the one with current-feedback system. The result shows that the contactor with current-feedback system can avoid this flaw of the contactor without current-feedback system.

This paper considers a two-echelon repair model where several series systems comprising multiple items are operated in each base. We propose a basic model and two modified models. For two models, approximation methods are developed to derive the system availability. The difference between the basic model and the first modified model is whether the normal items in failed series systems are available as spare or not. The second modified model relaxes the assumptions of the first modified model to reflect more realistic situation. We perform numerical analysis for the models to compare their system availabilities and verify the accuracy of the approximation methods.

In this paper, first, we propose a new recursive algorithm for evaluating generalized multi-state k-out-of-n:F systems. This recursive algorithm can be applied to the systems even though the states of all components in the system are assumed to be non-i.i.d. random variables. Our algorithm is useful for any multi-state k-out-of-n:F system, including the decreasing, increasing and constant multi-state k-out-of-n:F system. Furthermore, our algorithm can evaluate the state distributions of the other non-monotonic multi-state k-out-of-n:F systems. Next, we calculate the order of computing time and memory capacity of the proposed algorithm. We perform numerical experiments in the non-i.i.d. case. The results show that the proposed algorithm is efficient for evaluating the system state distribution of multi-state k-out-of-n:F system when n is large and kl are small.

In this paper, the performance of multiuser MIMO E-SDM systems in downlink transmission is evaluated in both uncorrelated and correlated time-varying fading environments. In the ideal case, using the block diagonalization scheme, inter-user interference can be completely eliminated at each user; and using the E-SDM technique for each user, optimal resource allocation can be achieved, and spatially orthogonal substreams can be obtained. Therefore, a combination of the block diagonalization scheme and the E-SDM technique applied to multiuser MIMO systems gives very good results. In realistic environments, however, due to the dynamic nature of the channel and processing delay at both the transmitter and the receiver, the channel change during the delay may cause inter-user interference even if the BD scheme is used. In addition, the change may also result in large inter-substream interference and prevent optimal resource allocation from being achieved. As a result, system performance may be degraded seriously. To overcome the problem, we propose a method of channel extrapolation to compensate for the channel change. Applying our proposed method, simulation results show that much better system performance can be obtained than the conventional case. Moreover, it also shows that the system performance in the correlated fading environments is much dependent on the antenna configuration and the angle spread from the base station to scatterers.

Nonbinary M-ary data processed by data entry systems, such as keyboard devices and character recognition systems, often have various types of error, such as symbol-substitution errors, deletion errors, insertion errors, and adjacent-symbol-transposition errors. This paper proposes nonsystematic M-ary codes capable of correcting these errors. The code is defined as a set of codewords that satisfy three conditions required to correct substitution, deletion/insertion, and adjacent-symbol-transposition errors. Since symbol-substitution errors in data entry systems are usually asymmetric, this paper also presents asymmetric-symbol-substitution error correcting codes capable of correcting deletion, insertion, and adjacent-symbol-transposition errors. For asymmetric-symbol-substitution error correction, we employ a mapping derived from the vertex coloring in an error directionality graph. The evaluation shows that the asymmetric codes have three to five times larger number of codewords than the symmetric codes.

Most large-scale distributed file systems decouple a metadata operation from read and write operations for a file. In the distributed file systems, a certain server named a metadata server (MDS) is responsible for maintaining the metadata information of the file systems. In this paper, we propose a new metadata management scheme in order to provide the high metadata throughput and scalability for a cluster of MDSs. First, we derive a new metadata distribution technique. Then, we present a load balancing technique based on the distribution technique. Several experiments show that our scheme outperforms existing metadata management scheme in terms of scalability and load balancing.

A linear consecutive-k-out-of-n: F system is an ordered sequence of n components. This system fails if, and only if, k or more consecutive components fail. Optimal arrangement is one of the main problems for such kind of system. In this problem, we want to obtain an optimal arrangement of components to maximize system reliability, when all components of the system need not have equal component failure probability and all components are mutually statistically independent. As n becomes large, however, the amount of calculation would be too much to solve within a reasonable computing time even by using a high-performance computer. Hanafusa and Yamamoto proposed applying Genetic Algorithm (GA) to obtain quasi optimal arrangement in a linear consecutive-k-out-of-n: F system. GA is known as a powerful tool for solving many optimization problems. They also proposed ordinal representation, which produces only arrangements satisfying the necessary conditions for optimal arrangements and eliminates redundant arrangements with same system reliabilities produced by reversal of certain arrangements. In this paper, we propose an efficient GA. We have modified the previous work mentioned above to allocate components with low failure probabilities, that is to say reliable components, at equal intervals, because such arrangements seem to have relatively high system reliabilities. Through the numerical experiments, we observed that our proposed GA with interval k provides better solutions than the previous work for the most cases.

A parallel multiplexing scheduling (PMS) scheme is proposed for distributed antenna systems (DAS), which greatly improves average system throughput due to multi-user diversity and multi-user multiplexing. However, PMS has poor fairness because of the use of the "best channel selection" criteria in the scheduler. Thus we present a parallel proportional fair scheduling (PPFS) scheme, which combines PMS with proportional fair scheduling (PFS) to achieve a tradeoff between average throughput and fairness. In PPFS, the "relative signal to noise ratio (SNR)" is employed as a metric to select the user instead of the "relative throughput" in the original PFS. And only partial channel state information (CSI) is fed back to the base station (BS) in PPFS. Moreover, there are multiple users selected to transmit simultaneously at each slot in PPFS, while only one user occupies all channel resources at each slot in PFS. Consequently, PPFS improves fairness performance of PMS greatly with a relatively small loss of average throughput compared to PFS.

Checker synthesis for assertion based verification becomes popular because of the recent progress on the FPGA prototyping environment. In the paper, we propose a checker synthesis method based on the finite input-memory automaton suitable for embedded RAM modules in FPGA. There are more than 1 Mbit memories in medium size FPGA's and such embedded memory cells have the capability to be used as the shift registers. The main idea is to construct a checker circuit using the finite input-memory automata and implement shift register chain by logic elements or embedded RAM modules. When using RAM module, the method does not consume any logic element for storing the value. Note that the shift register chain of input memory can be shared with different assertions and we can reduce the hardware resource significantly. We have checked the effectiveness of the proposed method using several assertions.

This letter focuses on the simplified capacity evaluation for the downlink of a distributed antenna system (DAS) with random antenna layout. Based on system scale-up, we derive a good approximation of the downlink capacity by developing the results from random matrix theory. We also propose an iterative method to calculate the unknown parameters in the approximated expression of the downlink capacity. The approximation is illustrated to be quite accurate and the iterative method is shown to be quite efficient by Monte Carlo simulations.

Time-interleaved (TI) analog-to-digital converters (ADCs) are frequently advocated as a power-efficient solution to realize the high sampling rates required in single-chip transceivers for the emerging communication schemes: ultra-wideband, fast serial links, cognitive-radio and software-defined radio. However, the combined effects of multiple distortion sources due to channel mismatches (bandwidth, offset, gain and timing) severely affect system performance and power consumption of a TI ADC and need to be accounted for since the earlier design phases. In this paper, system-level design of TI ADCs is addressed through a platform-based methodology, enabling effective investigation of different speed/resolution scenarios as well as the impact of parallelism on accuracy, yield, sampling-rate, area and power consumption. Design space exploration of a TI successive approximation ADC is performed top-down via Monte Carlo simulations, by exploiting behavioral models built bottom-up after characterizing feasible implementations of the main building blocks in a 90-nm 1-V CMOS process. As a result, two implementations of the TI ADC are proposed that are capable to provide an outstanding figure-of-merit below 0.15 pJ/conversion-step.

This paper presents a robust reduced order observer for a class of Lipschitz nonlinear systems with external disturbance. Sufficient conditions on the existence of the proposed observer are characterized by linear matrix inequalities. It is also shown that the proposed observer design can reduce the effect on the estimation error of external disturbance up to the prescribed level. Finally, a numerical example is provided to verify the proposed design method.

The wireless sensor network is a resource-constrained self-organizing system that consists of a large number of tiny sensor nodes. Due to the low-cost and low-power nature of sensor nodes, sensor nodes are failure-prone when sensing and processing data. Most presented fault-tolerant research for wireless sensor networks focused on crash faults or power faults and less on Byzantine faults. Hence, in this paper, we propose a power-saving data aggregation algorithm for Byzantine faults to provide power savings and high success rates even in the environment with high fault rates. The algorithm utilizes the concept of Byzantine masking quorum systems to mask the erroneous values and to finally determine the correct value. Our simulation results demonstrate that when the fault rate of sensor nodes is up to 50%, our algorithm still has 48% success rate to obtain the correct value. Under the same condition, other fault-tolerant algorithms are almost failed.

In recent years, the space-time block coding (STBC) method has attracted attention to provide transmission diversity in mobile communication systems. Although the STBC method is very effective in slow fading environments, its performance in fast fading environments has yet to be clearly verified. In this paper we propose a railway radio communication system using space-time coding in cooperation with two base stations. Here, we considered the differential STBC (D-STBC) method in railway communication system to overcome difficulties caused by the fast fading environment. We have compared the performance of STBC and D-STBC method where there is frequency offset between two base stations. Moreover, we have presented the simulation result of overall performance of the system including frequency offset and transmission time delay when operating D-STBC method. The overall evaluation on this paper shows that the D-STBC method is suitable for realizing highly reliable railway communication systems.

We address the problem of multiuser co-channel interference scheduling in multicell interference-limited networks. Our target is to optimize the network capacity under the SIR-balanced power control policy. Since it's difficult to optimize the original problem, we derive a new problem which maximizes the lower bound of the network capacity. Based on the analysis of this new problem, we propose an interference matched scheduling algorithm. This algorithm considers the caused co-channel interference and the channel conditions to schedule the "matched" users at the same time. We prove that this interference matched scheduling algorithm optimizes the lower bound of the network capacity for any arbitrary numbers of cells and users. Moreover, this scheduling method is low-complexity and can be implemented in a fully distributed fashion. Simulation results reveal that the performance of the proposed algorithm achieves near optimal capacity, even though it does not optimize the network capacity directly. Finally, the proposed algorithm holds a great gain over formerly proposed round robin and power matched scheduling method, especially when the scale of the network is large.

In this paper, we solve the call admission control (CAC) and routing problem in an integrated network that handles several classes of calls of different values and with different resource requirements. The problem of maximizing the average reward (or cost) of admitted calls per unit time is naturally formulated as a semi-Markov Decision Process (SMDP) problem, but is too complex to allow for an exact solution. Thus in this paper, a policy gradient algorithm, together with a decomposition approach, is proposed to find the dynamic (state-dependent) optimal CAC and routing policy among a parameterized policy space. To implement that gradient algorithm, we approximate the gradient of the average reward. Then, we present a simulation-based algorithm to estimate the approximate gradient of the average reward (called GSMDP algorithm), using only a single sample path of the underlying Markov chain for the SMDP of CAC and routing problem. The algorithm enhances performance in terms of convergence speed, rejection probability, robustness to the changing arrival statistics and an overall received average revenue. The experimental simulations will compare our method's performance with other existing methods and show the robustness of our method.

In an embedded system where a single application or a class of applications is repeatedly executed on a processor, its cache configuration can be customized such that an optimal one is achieved. We can have an optimal cache configuration which minimizes overall memory access time by varying the three cache parameters: the number of sets, a line size, and an associativity. In this paper, we first propose two cache simulation algorithms: CRCB1 and CRCB2, based on Cache Inclusion Property. They realize exact cache simulation but decrease the number of cache hit/miss judgments dramatically. We further propose three more cache design space exploration algorithms: CRMF1, CRMF2, and CRMF3, based on our experimental observations. They can find an almost optimal cache configuration from the viewpoint of access time. By using our approach, the number of cache hit/miss judgments required for optimizing cache configurations is reduced to 1/10-1/50 compared to conventional approaches. As a result, our proposed approach totally runs an average of 3.2 times faster and a maximum of 5.3 times faster compared to the fastest approach proposed so far. Our proposed cache simulation approach achieves the world fastest cache design space exploration when optimizing total memory access time.

In this paper, we analyze the extended real-time Polling Service (ertPS) algorithm in IEEE 802.16e systems, which is designed to support Voice-over-Internet-Protocol (VoIP) services with data packets of various sizes and silence suppression. The analysis uses a two-dimensional Markov Chain, where the grant size and the voice packet state are considered, and an approximation formula for the total throughput in the ertPS algorithm is derived. Next, to improve the performance of the ertPS algorithm, we propose an enhanced uplink resource allocation algorithm, called the e 2rtPS algorithm, for VoIP services in IEEE 802.16e systems. The e 2rtPS algorithm considers the queue status information and tries to alleviate the queue congestion as soon as possible by using remaining network resources. Numerical results are provided to show the accuracy of the approximation analysis for the ertPS algorithm and to verify the effectiveness of the e 2rtPS algorithm.

This Letter proposes an optimal gain filter for the perceptual acoustic echo suppressor. We designed an optimally-modified log-spectral amplitude estimation algorithm for the gain filter in order to achieve robust suppression of echo and noise. A new parameter including information about interferences (echo and noise) of single-talk duration is statistically analyzed, and then the speech absence probability and the a posteriori SNR are judiciously estimated to determine the optimal solution. The experiments show that the proposed gain filter attains a significantly improved reduction of echo and noise with less speech distortion.