In this paper, we analyze the performance of a dual-hop multiuser amplify-and-forward (AF) relay network with the effect of the feedback delay, where the source and each of the K destinations are equipped with Nt and Nr antennas respectively, and the relay is equipped with a single antenna. In the relay network, multi-antenna and multiuser diversities are guaranteed via beamforming and opportunistic scheduling, respectively. To examine the impact of delayed feedback, the new exact analytical expressions for the outage probability (OP) and symbol error rate (SER) are derived in closed-form over Rayleigh fading channel, which are useful for a large number of modulation schemes. In addition, we present the asymptotic expressions for OP and SER in the high signal-to-noise ratio (SNR) regime, from which we gain an insight into the system performance with deriving the diversity order and array gain. Moreover, based on the asymptotic expressions, we determine power allocation among the network nodes such that the OP is minimized. The analytical expressions are validated by Monte-Carlo simulations.

We compared two audio output devices for augmented audio reality applications. In these applications, we plan to use speech annotations on top of the actual ambient environment. Thus, it becomes essential that these audio output devices are able to deliver intelligible speech annotation along with transparent delivery of the environmental auditory scene. Two candidate devices were compared. The first output was the bone-conduction headphone, which can deliver speech signals by vibrating the skull, while normal hearing is left intact for surrounding noise since these headphones leave the ear canals open. The other is the binaural microphone/earphone combo, which is in a form factor similar to a regular earphone, but integrates a small microphone at the ear canal entry. The input from these microphones can be fed back to the earphones along with the annotation speech. We also compared these devices to normal hearing (i.e., without headphones or earphones) for reference. We compared the speech intelligibility when competing babble noise is simultaneously given from the surrounding environment. It was found that the binaural combo can generally deliver speech signals at comparable or higher intelligibility than the bone-conduction headphones. However, with the binaural combo, we found that the ear canal transfer characteristics were altered significantly by shutting the ear canals closed with the earphones. Accordingly, if we employed a compensation filter to account for this transfer function deviation, the resultant speech intelligibility was found to be significantly higher. However, both of these devices were found to be acceptable as audio output devices for augmented audio reality applications since both are able to deliver speech signals at high intelligibility even when a significant amount of competing noise is present. In fact, both of these speech output methods were able to deliver speech signals at higher intelligibility than natural speech, especially when the SNR was low.

Multicell cooperation is a promising technique to mitigate the inter-cell interference and improve the sum rate in cellular systems. Limited feedback design is of great importance to base station cooperation as it provides the quantized channel state information (CSI) of both the desired and interfering channels to the transmitters. Most studies on multicell limited feedback deal with scenarios of a single receive antenna at the mobile user. This paper, however, applies limited feedback to cooperative multicell multiple-input multiple-output (MIMO) systems where both base stations and users are equipped with multiple antennas. An optimized feedback strategy with random vector quantization (RVQ) codebook is proposed for interference aware coordinated beamforming that approximately maximizes the lower bound of the sum rate. By minimizing the upper-bound on the mean sum-rate loss induced by the quantization errors, we present a feedback-bit allocation algorithm to divide the available feedback bits between the desired and interfering channels for arbitrary number of transmit and receive antennas under different interfering signal strengths. Simulation results demonstrate that the proposed scheme utilizes the feedback resource effectively and achieves sum-rate performance reasonably close to the full CSI case.

Because dielectrics between active layers have low thermal conductivities, there is a demand to reduce the temperature increase in three-dimensional integrated circuits (3D ICs). This paper demonstrates that, in the design of 3D ICs, different layer assignments often lead to different temperature increases. Based on this observation, we are motivated to perform temperature-aware layer assignment. Our work includes two parts. Firstly, an integer linear programming (ILP) approach that guarantees a minimum temperature increase is proposed. Secondly, a polynomial-time heuristic algorithm that reduces the temperature increase is proposed. Compared with the previous work, which does not take the temperature increase into account, the experimental results show that both our ILP approach and our heuristic algorithm produce a significant reduction in the temperature increase with a very small area overhead.

We present the adaptation of the acoustic models of hidden Markov models (HMMs) to the target speaker and noise environment using bilinear models. Acoustic models trained from various speakers and noise conditions are decomposed to build the bases that capture the interaction between the two factors. The model for the target speaker and noise is represented as a product of bases and two weight vectors. In experiments using the AURORA4 corpus, the bilinear model outperforms the linear model.

Sensor noise prevents the exact measurement of output, which makes it difficult to guarantee the ultimate bound of the actual output and states, which is smaller than the sensor noise amplitude. Even worse, the time-varying delay in the input does not guarantee the boundedness of the actual output and states under sensor noise. In this letter, our considered system is a chain of integrators in which time-varying delay exists in the input and there is an additive form of sensor noise in the output measurement. To guarantee the arbitrarily small ultimate bound of the actual output and states, we newly propose an adaptive output feedback controller whose gain is tuned on-line. The merits of our control method over the existing results are clearly shown in the example.

To implement a wideband bandpass filter with improved skirt-selectivity and out-band characteristics, a new parallel-coupled three-line unit with two short-circuited stubs symmetrically-loaded at the center line is proposed. Unlike most traditional ones, the passband of the proposed parallel-coupled three-line structure is based on the cross-coupling between non-adjacent lines rather than the direct-coupling between adjacent ones, whereas a pair of attenuation poles is found in the stopbands. After revealing its work mechanism, an efficient filter-design-scheme is correspondingly proposed for the presented structure. Firstly, based on a chebyshev-filter synthesis theory, a wideband passband filter consisting of a parallel-coupled two-line and two short-circuited stubs loaded at the input- and output- ports is designed. Furthermore, by putting a properly-designed 3/4-wavelength stepped-impedance resonator (SIR) in between the parallel-coupled two lines, two attenuation poles are then realized at the frequencies very close to the cutoff ones. Accordingly, the roll-off characteristics of the filter are significantly-improved to greater than 100,dB/GHz. Furthermore, two-section open-ended stubs are used to replace the short-circuited ones to realize a pair of extra attenuation poles in stopbands. To validate the proposed techniques, a wideband filter with a bandwidth of 3--5,GHz (Fractional bandwidth (FBW) $= (5,GHz-3,GHz)/4,GHz =50%)$ was designed, simulated, fabricated and measured. The measured responses of the filter agree well with the simulation and theoretical ones, which validates the effectiveness of the newly-proposed three-line unit and the corresponding design scheme.

We propose a power-saving mechanism (PSM) specific to request-and-response-based applications, which simply changes the order of the operating procedure of the legacy PSM by considering the attributes of the request-and-response delay. We numerically analyze the PSM with respect to the energy consumption and buffering delay and characterize this performance by employing a simple energy-delay trade-off (EDT) curve that is determined by the operating parameters. The resulting EDT curve clearly shows that the proposed PSM outperforms the legacy PSM.

Smart city services are implemented using various data collected from houses and infrastructure within a city. As the volume and variety of the smart city data becomes huge, individual services have suffered from expensive computation effort and large processing time. In order to reduce the effort and time, this paper proposes a concept of Materialized View as a Service (MVaaS). Using the MVaaS, every application can easily and dynamically construct its own materialized view, in which the raw data is converted and stored in a convenient format with appropriate granularity. Thus, once the view is constructed, the application can quickly access necessary data. In this paper, we design a framework of MVaaS specifically for large-scale house log, managed in a smart-city data platform. In the framework, each application first specifies how the raw data should be filtered, grouped and aggregated. For a given data specification, MVaaS dynamically constructs a MapReduce batch program that converts the raw data into a desired view. The batch is then executed on Hadoop, and the resultant view is stored in HBase. We present case studies using house log in a real home network system. We also conduct an experimental evaluation to compare the response time between cases with and without MVaaS.

Blur distortion is a common artifact in image communication and affects the perceived sharpness of a digital image. In this paper, we capitalize on the mathematical knowledge of Gaussian convolution and propose a strategy to minimally reblur test images. From the reblur algorithm, synthetic reblur images are created. We propose a new blind blur metric which makes use of the reblur images to produce blur scores. Compared to other no-reference blur assessments, the proposed method has the advantages of fast computation and training-free operation. Experiment results also show that the proposed method can produce blur scores which are highly correlated with human perception of blurriness.

This paper proposes a simple and practical scheme to decide the direction of a phased array antenna beam in wireless access systems using Radio-over-Fiber (RoF) technique. The feasibility of the proposed scheme is confirmed by the optical and wireless transmission experiments using 2GHz RoF signals. In addition, two-dimensional steering operation in the millimeter-wave band is demonstrated for targeting future high-speed wireless communication systems. The required system parameters for practical use are also provided by investigating the induced transmission penalties. The proposed detection scheme is applicable to two-dimensional antenna beam steering in the millimeter-wave band by properly designing the fiber length and wavelength variable range.

We demonstrate an all-optical non-return-to-zero differential phase shift keying (NRZ-DPSK) to return-to-zero differential phase shift keying (RZ-DPSK) format conversion with wavelength-shift-free and pulsewidth tunable operations by using a semiconductor optical amplifier (SOA)-based switch. An NRZ-DPSK signal is injected into the SOA-based switch with an RZ clock, and is converted to RZ-DPSK signal owing to the nonlinear effects inside the SOA. In this scheme, the wavelength of the converted RZ-DPSK signal is maintained as the original wavelength of the input NRZ-DPSK signal during the format conversion. Moreover, the pulsewidth of the converted signal is tunable in a wider operating range from 30 to 60 ps. The format conversion with pulsewidth tunability is based on cross-phase modulation (XPM) and cross-gain modulation (XGM) effects in the SOA. The clear eye diagrams, optical spectra and the bit-error-rate (BER) characteristics show high conversion performance with the wide pulsewidth tuning range. For all cases of the converted RZ-DPSK signal with different pulsewidths, the receiver sensitivities at a BER of 10$^{-9}$ for the converted RZ-DPSK signal were 0.7 to 1.5 dB higher than the receiver sensitivity of the input NRZ-DPSK signal.

General purpose computing on GPU (GPGPU) has become a popular computing model for high-performance, data-intensive applications. Accordingly, there is a strong need to develop highly efficient data structures to ease the development of GPGPU applications. In this work, we proposed an efficient concurrent queue data structure for GPU computing. The GPU based provably correct, lock-free FIFO queue allows a massive number of concurrent producers and consumers. Warp-centric en-queue and de-queue procedures are introduced to better match the underlying Single-Instruction, Multiple-Thread execution model of modern GPUs. It outperforms the best previous GPU queues by up to 40 fold. The correctness of the proposed queue operations is formally validated by linearizability criteria.

Bit error rate characteristic of negative feedback optical amplifier was investigated by manipulating the negative feedback signal intensity fed into the semiconductor optical amplifier together with the input signal. Consequently, bit error rate was reduced as negative feedback signal intensity increases. Suppression towards the unevenness at the power level `1' and overshoot during rising phase on the output signal eye-diagram was recorded. With negative feedback, through gain decrease of 2.4 dB, power penalty improved remarkably by 15 dB.

Acoustic feedback is a major complaint of hearing aid users. Adaptive filters are a common method for suppressing acoustic feedback in digital hearing aids. In this letter, we propose a new variable step-size algorithm for normalized least mean square and an affine projection algorithm to combine with a variable step-size affine projection algorithm and global speech absence probability in an adaptive filter. The computer simulation used to test the proposed algorithm results in a lower misalignment error than the comparison algorithm at a similar convergence rate. Therefore, the proposed algorithm suggests an effective solution for the feedback suppression system of digital hearing aids.

An n-dimensional folded hypercube, denoted by FQn, is an enhanced n-dimensional hypercube with one extra link between nodes that have the furthest Hamming distance. Let FFv (respectively, FFe) denote the set of faulty nodes (respectively, faulty links) in FQn. Under the assumption that every fault-free node in FQn is incident to at least two fault-free links, Hsieh et al. (Inform. Process. Lett. 110 (2009) pp.41-53) showed that if |FFv|+|FFe| ≤ 2n-4 for n ≥ 3, then FQn-FFv-FFe contains a fault-free cycle of length at least 2n-2|FFv|. In this paper, we show that, under the same conditional fault model, FQn with n ≥ 5 can tolerate more faulty elements and provides the same lower bound of the length of a longest fault-free cycle, i.e., FQn-FFv-FFe contains a fault-free cycle of length at least 2n-2|FFv| if |FFv|+|FFe| ≤ 2n-3 for n ≥ 5.

Multi-task learning is an important area of machine learning that tries to learn multiple tasks simultaneously to improve the accuracy of each individual task. We propose a new tree-based ensemble multi-task learning method for classification and regression (MT-ExtraTrees), based on Extremely Randomized Trees. MT-ExtraTrees is able to share data between tasks minimizing negative transfer while keeping the ability to learn non-linear solutions and to scale well to large datasets.

This paper proposes a novel approach for integrating spectral feature extraction and acoustic modeling in hidden Markov model (HMM) based speech synthesis. The statistical modeling process of speech waveforms is typically divided into two component modules: the frame-by-frame feature extraction module and the acoustic modeling module. In the feature extraction module, the statistical mel-cepstral analysis technique has been used and the objective function is the likelihood of mel-cepstral coefficients for given speech waveforms. In the acoustic modeling module, the objective function is the likelihood of model parameters for given mel-cepstral coefficients. It is important to improve the performance of each component module for achieving higher quality synthesized speech. However, the final objective of speech synthesis systems is to generate natural speech waveforms from given texts, and the improvement of each component module does not always lead to the improvement of the quality of synthesized speech. Therefore, ideally all objective functions should be optimized based on an integrated criterion which well represents subjective speech quality of human perception. In this paper, we propose an approach to model speech waveforms directly and optimize the final objective function. Experimental results show that the proposed method outperformed the conventional methods in objective and subjective measures.

This study analyzes the performance of a downlink beamformer with partitioned vector quantization under optimized feedback budget allocation. A multiuser multiple-input single-output downlink precoding system with perfect channel state information at mobile stations is considered. The number of feedback bits allocated to the channel quality indicator (CQI) and the channel direction indicator (CDI) corresponding to each partition are optimized by exploiting the quantization mean square error. In addition, the effects of equal and unequal partitioning on codebook memory and system capacity are studied and elucidated through simulations. The results show that with optimized CQI-CDI allocation, the feedback budget distributions of equal or unequal partitions are proportional to the size ratios of the partitioned subvectors. Furthermore, it is observed that for large-sized partitions, the ratio of optimal CDI to CQI is much higher than that for small-sized partitions.

Establishing trust measurements among peer-to-peer (P2P) networks is fast becoming a de-facto standard, and a fair amount of work has been done in the area of trust aggregation and calculation algorithms. However, the area of developing secure underlying protocols to distribute and access the trust ratings in the overlay network has been relatively unexplored. We propose an elliptic curve-based trust management protocol for P2P systems, which is designed to provide authentication and signature functions to protect the processes of trust value query and rating report. Additionally, instead of using single identities, the protocol generates two verifiable pseudonyms, one is used for transaction, the other is applied when the peer acts as a trust holding peer. A security analysis shows that the proposed protocol is extremely secure in the face of a variety of possible attacks.