The scheduling of real-time tasks with fault-tolerant requirements has been an important problem in multiprocessor systems. The primary-backup (PB) approach is often used as a fault-tolerant technique to guarantee the deadlines of tasks despite the presence of faults. In this paper we propose a dynamic PB-based task scheduling approach, wherein an allocation parameter is used to search the available time slots for a newly arriving task, and the previously scheduled tasks can be re-scheduled when there is no available time slot for the newly arriving task. In order to improve the schedulability we also propose an overloading strategy for PB-overloading and Backup-backup (BB) overloading. Our proposed task scheduling algorithm is compared with some existing scheduling algorithms in the literature through simulation studies. The results have shown that the task rejection ratio of our real-time task scheduling algorithm is almost 50% lower than the compared algorithms.

We present a low-complexity maximum likelihood (ML) detector for a coded double space-time transmit diversity-orthogonal frequency division multiplexing (DSTTD-OFDM) system. The proposed ML detector exploits properties of two permuted equivalent channel matrices and multiple decision-feedback (DF) detections. This can reduce computational efforts from O(|A|4) to O(2|A|2) with maintaining ML performance, where |A| is the modulation order. Numerical results shows that the proposed ML detector obtains ML performance and requires remarkably lower computational loads compared with the conventional ML detector.

This letter presents new delayed perturbation bounds (DPBs) for stabilizing receding horizon H∞ control (RHHC). The linear matrix inequality (LMI) approach to determination of DPBs for the RHHC is proposed. We show through a numerical example that the RHHC can guarantee an H∞ norm bound for a larger class of systems with delayed perturbations than conventional infinite horizon H∞ control (IHHC).

This paper presents our developed decoder which adopts the idea of statically optimizing part of the knowledge sources while handling the others dynamically. The lexicon, phonetic contexts and acoustic model are statically integrated to form a memory-efficient state network, while the language model (LM) is dynamically incorporated on the fly by means of extended tokens. The novelties of our approach for constructing the state network are (1) introducing two layers of dummy nodes to cluster the cross-word (CW) context dependent fan-in and fan-out triphones, (2) introducing a so-called "WI layer" to store the word identities and putting the nodes of this layer in the non-shared mid-part of the network, (3) optimizing the network at state level by a sufficient forward and backward node-merge process. The state network is organized as a multi-layer structure for distinct token propagation at each layer. By exploiting the characteristics of the state network, several techniques including LM look-ahead, LM cache and beam pruning are specially designed for search efficiency. Especially in beam pruning, a layer-dependent pruning method is proposed to further reduce the search space. The layer-dependent pruning takes account of the neck-like characteristics of WI layer and the reduced variety of word endings, which enables tighter beam without introducing much search errors. In addition, other techniques including LM compression, lattice-based bookkeeping and lattice garbage collection are also employed to reduce the memory requirements. Experiments are carried out on a Mandarin spontaneous speech recognition task where the decoder involves a trigram LM and CW triphone models. A comparison with HDecode of HTK toolkits shows that, within 1% performance deviation, our decoder can run 5 times faster with half of the memory footprint.

This paper proposes a self-test method of coarse grain dynamically reconfigurable processors (DRPs) without hardware overhead. In the method, processor elements (PEs) compose a test frame, which consists of test pattern generators (TPGs), processor elements under test (PEUTs) and response analyzers (RAs), while testing themselves one another by changing test frames appropriately. We design several test frames with different structures, and discuss the relationship of the structures to the numbers of contexts and test frames for testing all the functions of PEs. A case study shows that there exists an optimal test frame which minimizes the test application time under a constraint.

Much research has shown that a carefully designed auto rate medium access control can utilize the underlying physical multi-rate capability to exploit the time-variation of the channel. In this paper, we develop a simple analytical model to elucidate the rule that maximizes the throughput of RTS/CTS based multi-rate wireless local area networks. Based on the discovered rule, we propose two distributed fair auto rate medium access control schemes called FARM and FARM+ from the viewpoint of throughput fairness and time-share fairness, respectively. With the proposed schemes, after receiving a RTS frame, the receiver selectively returns the CTS frame to inform the transmitter the maximum feasible rate probed by the signal-to-noise ratio of the received RTS frame. The key feature of the proposed schemes is that they are capable of maintaining throughput/time-share fairness in asymmetric situation where the distribution of SNR varies with stations. Extensive simulation results show that the proposed schemes outperform the existing throughput/time-share fair auto rate schemes in time-varying channel conditions.

This paper discusses the behavior of the second-order modes (Hankel singular values) of linear continuous-time systems under variable transformations with positive-real functions. That is, given a transfer function H(s) and its second-order modes, we analyze the second-order modes of transformed systems H(F(s)), where 1/F(s) is an arbitrary positive-real function. We first discuss the case of lossless positive-real transformations, and show that the second-order modes are invariant under any lossless positive-real transformation. We next consider the case of general positive-real transformations, and reveal that the values of the second-order modes are decreased under any general positive-real transformation. We achieve the derivation of these results by describing the controllability/observability Gramians of transformed systems, with the help of the lossless positive-real lemma, the positive-real lemma, and state-space formulation of transformed systems.

Automated capture and retrieval of experiences at home is interesting due to the wide variety and personal significance of such experiences. We present a system for retrieval and summarization of continuously captured multimedia data from Ubiquitous Home, a two-room house consisting of a large number of cameras and microphones. Data from pressure based sensors on the floor are analyzed to segment footsteps of different persons. Video and audio handover are implemented to retrieve continuous video streams corresponding to moving persons. An adaptive algorithm based on the rate of footsteps summarizes these video streams. A novel method for audio segmentation using multiple microphones is used for video retrieval based on sounds with high accuracy. An experiment, in which a family lived in this house for twelve days, was conducted. The system was evaluated by the residents who used the system for retrieving their own experiences; we report and discuss the results.

For unitary space-time code (USTC), the impact of spatial correlation on error performance is investigated. A tighter and simpler upper bound is derived for generalized likelihood ratio test decoder. We establish that the spatial correlation does not change the diversity gain, whereas it degrades the error performance of USTC. Motivated by the precoding of space-time block code, we designed a precoder for USTC to handle the case of the joint transmit-receive correlation. Numerical results show that the degradation in performance due to spatial correlation can be considerably compensated by the proposed algorithm.

This letter deals with computationally efficient maximum-likelihood (ML) detection for the quasi-orthogonal space-time block code (QOSTBC) with four transmit antennas. The proposed ML detector uses a permutation based real-valued equivalent channel matrix representation. As a result, the complexity of ML detection problem is moderated from O(2|A|2) to O(4|A|), where |A| is modulation order. Numerical results show that the proposed ML detector provides ML performance and achieves greatly high computational savings.

With the rapid advances in wireless network communication, multimedia presentation has become more applicable. However, due to the limited wireless network resource and the mobility of Mobile Host (MH), QoS for wireless streaming is much more difficult to maintain. How to decrease Call Dropping Probability (CDP) in multimedia traffic while still keeping acceptable Call Block Probability (CBP) without sacrificing QoS has become an significant issue in providing wireless streaming services. In this paper, we propose a novel Dynamic Resources Adjustment (DRA) algorithm, which can dynamically borrow idle reserved resources in the serving cell or the target cell for handoffing MHs to compensate the shortage of bandwidth in media streaming. The experimental simulation results show that compared with traditional No Reservation (NR), and Resource Reservation in the six neighboring cells (RR-nb), and Resource Reservation in the target cell(RR-t), our proposed DRA algorithm can fully utilize unused reserved resources to effectively decrease the CDP while still keeping acceptable CBP with high bandwidth utilization.

In this letter, a switched transmission technique is presented that can provide the orthogonal frequency division multiplexing (OFDM) systems with additional diversity gain. The space-time block coding (STBC) and space-frequency block coding (SFBC) are considered for the transmission of the OFDM signals. A proper coding scheme is selected based on the estimated normalized delay spread and normalized Doppler spread. The selection criterion is derived empirically. It is shown through computer simulations that the proposed switching technique can improve the bit error rate (BER) performance of an OFDM system when the corresponding wireless channel has some time variation of time selectivity as well as frequency selectivity.

Development of an artificial reverberator for low-memory requirements is an issue of importance in applications such as mobile multimedia devices. One possibility is to use an All-Pass Filter (APF), which is embedded in the feedback loop of the comb filter network. In this paper, we propose a reverberator employing time-varying APFs to increase the reverberation performance. By changing the gain of the APF, we can increase the number of frequency peaks perceptually. Thus, the resulting reverberation sounds much more natural, even with less memory, than the conventional approach. In this paper, we perform theoretical and perceptual analyses of artificial reverberators employing time-varying APF. Through the analyses, we derive the degree of phase variation of the APF that is perceptually acceptable. Based on the analyses, we propose a method of designing artificial reverberators associated with the time-varying APFs. Through subjective tests, it is shown that the proposed method is capable of providing perceptually comparable sound quality to the conventional methods even though it uses less memory.

In this letter, we consider the uplink packet scheduling for non-real-time data users in a DS-CDMA system. As an effort to jointly optimize throughput and fairness, we formulate a time-span minimization problem incorporating the time-multiplexing of different simultaneous transmission schemes. Based on simple rules, we propose efficient scheduling algorithms and compare them with the optimal solution obtained by linear programming.

For the purpose of reducing the quantization noise and power consumption of UWB-OFDM transceiver, a new time domain-based interpolator and decimator structure is proposed to realize five-bit D/A and A/D converters in the five-bit 128-tone sigma-delta modulation (SDM) UWB-OFDM transceiver. The five-bit 128-tone SDM UWB-OFDM transceiver using time domain-based interpolator and decimator in place of time spreader and de-spreader can obtain time-domain spread spectrum processing gain and reduce quantization noise simultaneously. The structure of the five-bit 128-tone SDM A/D converter, which employs 32 parallel analog SDM circuits without up-sampling, is designed. Simulation results demonstrate that BER of the proposed five-bit 128-tone SDM D/A and A/D converters based on time domain-based interpolator and decimator scheme can satisfy the performance requirements of the five-bit 128-tone SDM UWB-OFDM transceiver for the QPSK, 16-QAM and 64-QAM modulations.

We propose a simple asynchronous UWB (Ultra Wide Band) position location algorithm with low complexity, power consumption and processing delay. In the proposed algorithm, only a single RTTX (Round-Trip Transmission) of UWB pulses is utilized based on the ToA (Time of Arrival) principle. Hence, the proposed algorithm decreases power consumption and processing delay as compared to the basic ToA based on triple RTTXs. Moreover, unlike the TDoA (Time Difference of Arrival) algorithm, the proposed algorithm can perform the position location with low complexity since it does not require strict synchronization between multiple beacons. Simulation results using IEEE 802.15.4a UWB channel models reveal that the proposed algorithm achieves closely comparable position location performance of the basic ToA and TDoA algorithms.

In this letter, we analyze symbol error probability (SEP) and diversity gain of orthogonal space-time block codes (OSTBCs) in spatially correlated Rician fading channel. We derive the moment generating function (MGF) of an effective signal-to-noise ratio (SNR) at the receiver and use it to derive the SEP for M-PSK modulation. We use this result to show that the diversity gain is achieved by the product of the rank of the transmit and receive correlation matrix, and the loss in array gain is quantified as a function of the spatial correlation and the line of sight (LOS) component.

In this paper, an evolutionary approach is proposed to obtain a discrete-time state-space interval model for uncertain continuous-time systems having interval uncertainties. Based on a worst-case analysis, the problem to derive the discrete interval model is first formulated as multiple mono-objective optimization problems for matrix-value functions associated with the discrete system matrices, and subsequently optimized via a proposed genetic algorithm (GA) to obtain the lower and upper bounds of the entries in the system matrices. To show the effectiveness of the proposed approach, roots clustering of the characteristic equation of the obtained discrete interval model is illustrated for comparison with those obtained via existing methods.

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.

A low complexity minimum mean squared error (MMSE) equalizer for orthogonal frequency division multiplexing (OFDM) systems over time-varying channels is presented. It uses a small matrix of dominant partial channel information and recursive calculation of matrix inverse to significantly reduce the complexity. Theoretical analysis and simulations results are provided to validate its significant performance or complexity advantages over the previously published MMSE equalizers.