In this paper, a distributed cooperative multicell beamforming algorithm is proposed, and a detail analysis and solving method for instantaneous and statistical channel state information (CSI) are presented. Firstly, an improved distributed iterative beamforming algorithm is proposed for the multiple-input single-output interference channel (MISO IC) scenario which chooses virtual signal-to-interference-and-noise (SINR) as decision criterion to initialize and then iteratively solves the constrained optimization problem of maximizing the virtual SINR for a given level of generated interference to other users. Then, the algorithm is generalized to the multicell date sharing scenario with a heuristics power allocation scheme based on a viewpoint of the layered channel. Finally, the performance is illustrated through numerical simulations.

In automated transport applications, the design of a task allocation policy becomes a complex problem when there are several agents in the system and conflicts between them may arise, affecting the system's performance. In this situation, to achieve a globally optimal result would require the complete knowledge of the system's model, which is infeasible for real systems with huge state spaces and unknown state-transition probabilities. Reinforcement Learning (RL) methods have done well approximating optimal results in the processing of tasks, without requiring previous knowledge of the system's model. However, to our knowledge, there are not many RL methods focused on the task allocation problem in transportation systems, and even fewer directly used to allocate tasks, considering the risk of conflicts between agents. In this paper, we propose an option-based RL algorithm with conditioned updating to make agents learn a task allocation policy to complete tasks while preventing conflicts between them. We use a multicar elevator (MCE) system as test application. Simulation results show that with our algorithm, elevator cars in the same shaft effectively learn to respond to service calls without interfering with each other, under different passenger arrival rates, and system configurations.

To realize a single or several molecule device, the following are necessary: (1) an electrical wiring method that is not destructive to the molecular aggregates and does not affect the electronic state of the molecules, (2) noncontact and controllable molecular manipulation technology, (3) oriented growth techniques especially to prepare a nanodevice employing an anisotropic molecular system. In this paper, recently developed electric-field assisted growth and its application to molecular device fabrication are presented.

Bayesian methods are often applied for estimating the event rate from a series of event occurrences. However, the Bayesian posterior distribution requires the computation of the marginal likelihood which generally involves an analytically intractable integration. As an event rate is defined in a very high dimensional space, it is computationally demanding to obtain the Bayesian posterior distribution for the rate. We estimate the rate underlying a sequence of event counts by deriving an approximate Bayesian inference algorithm for the time-varying binomial process. This enables us to calculate the posterior distribution analytically. We also provide a method for estimating the prior hyperparameter, which determines the smoothness of the estimated event rate. Moreover, we provide an efficient method to compute the upper and lower bounds of the marginal likelihood, which evaluate the approximation accuracy. Numerical experiments demonstrate the effectiveness of the proposed method in terms of the estimation accuracy.

In Long-Term Evolution-Advanced (LTE-A), which is currently in the process of standardization in the 3rd generation partnership project (3GPP), carrier aggregation (CA) was introduced as a main feature for bandwidth extension while maintaining backward compatibility with LTE Release 8 (Rel. 8). In the CA mode of operation, since two or more component carriers (CCs), each of which is compatible with LTE Rel. 8, are aggregated, mobility management is needed for CCs such as inter/intra-frequency handover, CC addition, and CC removal to provide sufficient coverage and better overall signal quality. Therefore, the signaling overhead for Radio Resource Control (RRC) reconfiguration for the mobility management of CCs in LTE-A is expected to be larger than that in LTE Rel. 8. In addition, CA allows aggregation of cells with different types of coverage. Therefore, the signaling overhead may be dependent on the coverage of each CC assumed in a CA deployment scenario. Furthermore, especially in a picocell-overlaid scenario, the amount of signaling overhead may be different according to whether the aggregation of CCs between a macrocell and a picocell, i.e., transmission and reception from multiple sites, is allowed or not. Therefore, this paper investigates the CC control overhead with several CC management policies in some CA deployment scenarios, including a scenario with overlaid picocells. Simulation results show that the control overhead is almost the same irrespective of the different management policies, when almost the same coverage is provided for the CCs. In addition, it is shown that the increase in the control overhead is not significant even in a CA deployment scenario with overlaid picocells. We also show that the amount of signaling overhead in a picocell-overlaid scenario with the CA between a macrocell and a picocell is almost twice as that without the CA between a macrocell and a picocell.

A simple analytical model to predict the DC MOSFET behavior under electromagnetic interference (EMI) is presented. The model is able to describe the MOSFET performance in the linear and saturation regions under EMI disturbance applied to the gate. The model consists of a unique simple equivalent circuit based on a voltage dependent current source and a reduced number of parameters which can accurately predict the drift on the drain current due to the EMI source. The analytical approach has been validated by means of electric simulation and measurements and can be easily introduced in circuit simulators. The proposed modeling technique combined with the nth-power law model of the MOSFET without EMI, significantly improves its accuracy in comparison with the n-th power law directly applied to a MOSFET under EMI impact.

In multi-cell wireless systems with insufficient frequency reuse, the downlink transmission suffers from other cell interference (OCI). The cooperative transmission among multiple base stations is an effective way to mitigate OCI and increase the system sum rate. An adaptive scheme for serving one user in each cell was proposed in [1]. In this paper, we generalize the scheme in [1] by serving more than one user in each cell with adaptive OCI cancelation. Based on our derived statistics of a user for different transmission strategies, we propose a low complexity transmission scheme that achieves near-maximal ergodic sum rate. Through numerical examples, we show that the system sum rate can be improved by selecting the appropriate transmission strategy combination adaptively. As a result, our proposed system can explore spatial multiplexing gain without additional power and thus improves the system sum rate significantly.

In this letter, we present a novel timing offset estimation method for chirp-based communication systems which is robust against frequency offset. For robust timing offset estimation, we propose a partial cross-correlation and differential multiplication method using up and down chirp symbols. The performances of the proposed estimator in indoor multipath channel model provided by IEEE 802.15.4a standard are presented in terms of mean-square error (MSE) obtained by computer simulation. The simulation results show that the proposed estimator has a significantly smaller MSE than the conventional estimators.

This paper investigates a new method for fusion of scores generated by multiple classification sub-systems that help to further reduce the classification error rate in Spoken Language Recognition (SLR). In recent studies, a variety of effective classification algorithms have been developed for SLR. Hence, it has been a common practice in the National Institute of Standards and Technology (NIST) Language Recognition Evaluations (LREs) to fuse the results from several classification sub-systems to boost the performance of the SLR systems. In this work, we introduce a discriminative performance measure to optimize the performance of the fusion of 7 language classifiers developed as IIR's submission to the 2009 NIST LRE. We present an Error Corrective Fusion (ECF) method in which we iteratively learn the fusion weights to minimize error rate of the fusion system. Experiments conducted on the 2009 NIST LRE corpus demonstrate a significant improvement compared to individual sub-systems. Comparison study is also conducted to show the effectiveness of the ECF method.

In this paper, the performance of a low duty factor (DF) hybrid direct sequence (DS) multiband (MB)-pulsed ultra wideband (UWB) system is evaluated over realistic propagation channels to highlight its capability of interference mitigation. The interference mitigation techniques incorporated in the DS-MB-UWB system is a novel design that includes the utilization of the frequency-agile multiple sub-band configuration and the coexistence-friendly low DF signaling. The system design consists of a Rake type receiver over multipath and multi-user channel in the presence of a coexisting narrowband interferer. The propagation channels are modeled based on actual measurement data. Firstly, by suppressing the power in the particular sub-band coexisting with the narrowband signal, performance degradation due to narrowband interference can be improved. It is observed that by fully suppressing the sub-band affected by the narrowband signal, a typical 1-digit performance improvement (e.g. BER improves from 10-3 to 10-4) can be achieved. Secondly, by employing lower DF signaling, self interference (SI) and multi-user interference (MUI) can be mitigated. It is found that a typical 3 dB improvement is achieved by reducing the DF from 0.5 to 0.04. Together, the sub-band power suppression and low DF signaling are shown to be effective mitigation techniques against environment with the presence of SI, MUI and narrowband interference.

We fabricated solution-processed organic complementary inverters based on α,ω-bis(2-hexyldecyl)sexithiophene (BHD6T) for p-channel and C60-fused N-methylpyrrolidine-meta-dodecyl phenyl (C60MC12) for n-channel. The BHD6T and C60MC12 thin-film transistors showed high field-effect mobilities of 0.035 and 0.057 cm2/Vs, respectively. The complementary inverter with a supply voltage of 50 V exhibited inverting voltages of 26.8 V for forward and 27.0 V for backward sweeps and a high gain of 76.

In this paper, we consider the signal processing algorithm on each subcarrier for the downlink of Multi-User Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MU-MIMO OFDM) system. A novel transmit scheme is proposed for the cancellation of Inter-User Interference (IUI) at the Base Station (BS). The improved performance of each user is obtained by optimizing the transmit scheme on each subcarrier, where the Particle Swarm Optimization (PSO) algorithm is employed to solve the constrained nonlinear optimization problem. Compared with the conventional Zero Forcing Dirty Paper Coding (ZF-DPC) having only single receive antenna at each Mobile Station (MS), the proposed scheme also applies the principle of DPC to cancel the IUI, but the MS users can be equipped with multiple receive antennas producing their increased receive SNR's. With the Channel State Information (CSI) being known at the BS and the MS, the eigenvalues for all the user channels are calculated first and then the user with the maximum eigenvalue is selected as the 1-st user. The remaining users are ordered and sequentially processed, where the transmit weights are generated from the previously selected users by the Particle Swarm Optimization (PSO) algorithm which ensures the transmit gain for each user as large as possible. The computational complexity analysis, BER performance and achievable sum-rate analysis of system verify the effectiveness of the proposed scheme.

This paper presents an interconnect resilient (IR) methodology with maximal interconnect fault tolerance, yield, and reliability for both single and multiple interconnect faults under stuck-at and open fault models. By exploiting multiple routes inherent in an interconnect structure, this method can tolerate faulty connections by efficiently finding alternative paths. The proposed approach is compatible with previous interconnect detection and diagnosis methods under oscillation ring schemes, and together they can be applied to implement a robust interconnect structure that may still provide correct communication even under multiple link faults in Network-on-Chips (NoCs). With such knowledge, designers can significantly improve interconnect reliability by augmenting vulnerable interconnect structures in NoCs. As a result, the experimental results show that alternative paths in NoCs can be found for almost all paths. Hence, the proposed method provides a good way to achieve fault tolerance and reliability/yield improvement.

Iterative synthesis methods for making aware of wire congestion are proposed for a multi-context dynamically reconfigurable processor (DRP) with a large number of processing elements (PEs) and programmable-wire connections. Although complex data-paths can be synthesized using the programmable-wire, its delay is long especially when wire connections are congested. We propose two iterative synthesis techniques between a high-level synthesizer (HLS) and the place & route tool to shorten the prolonged wire delay. First, we feed back wire delays for each context to a scheduler in the HLS. The experimental results showed that a critical-path delay was shorten by 21% on average for applications with timing closure problems. Second, we skip the routing and estimate wire delays based on the congestion. The synthesis time was shorten to 1/3 causing delay improvement rate degradation at two points on average.

Visibly pushdown automata (VPA), introduced by Alur and Madhusuan in 2004, is a subclass of pushdown automata whose stack behavior is completely determined by the input symbol according to a fixed partition of the input alphabet. Since it was introduced, VPA have been shown to be useful in various contexts, e.g., as specification formalism for verification and as an automaton model for processing XML streams. However, implementation of formal verification based on VPA framework is a challenge. In this paper, we propose on-the-fly algorithms to test universality and inclusion problems of this automata class. In particular, we first present a slight improvement on the upper bound for determinization of VPA. Next, in order to check universality of a nondeterministic VPA, we simultaneously determinize this VPA and apply the P-automata technique to compute a set of reachable configurations of the target determinized VPA. When a rejecting configuration is found, the checking process stops and reports that the original VPA is not universal. Otherwise, if all configurations are accepting, the original VPA is universal. Furthermore, to strengthen the algorithm, we define a partial ordering over transitions of P-automaton, and only minimal transitions are used to incrementally generate the P-automaton. The purpose of this process is to keep the determinization step implicitly for generating reachable configurations as minimum as possible. This improvement helps to reduce not only the size of the P-automaton but also the complexity of the determinization phase. We implement the proposed algorithms in a prototype tool, named VPAchecker. Finally, we conduct experiments on randomly generated VPA. The experimental results show that the proposed method outperforms the standard one by several orders of magnitude.

This paper presents a verification and analysis tool set for embedded systems. Recently, the development scale of embedded systems has been increasing since they are used for mobile systems, automobile platforms, and various consumer systems with rich functionality. This has increased the amount of time and cost needed to develop them. Consequently, it is very important to develop tools to reduce development time and cost. This paper describes a tool set consisting of three tools to enhance the efficiency of embedded system design. The first tool is an integrated tool platform. The second is a remote debugging system. The third is a clock-accurate verification system based on a field-programmable gate array (FPGA) for custom embedded systems. This tool set promises to significantly reduce the time and cost needed to develop embedded systems.

In the underlay decode-and-forward (DaF) cooperative cognitive radio (CR) network, an optimal relay can be selected by the conventional max-min selection on the condition of not violating the interference temperature (IT) constraint. However, the max-min selection may cause some extra amount of interference to the primary system (PS) such that the so-called transfer ratio (TR) may be lower. Note that TR is newly defined as the ratio of the secondary system's (SS's) capacity gain to the PS's capacity loss due to the activities of SS. In order to improve the TR value, we are motivated by the pricing function in game theory to propose a novel low-interference relay selection by taking the impacts of the interference from SS to PS into consideration. Using the low-interference selection, however, it will not always allow the optimal relay to be picked. To clarify this phenomenon, the still optimal probability is defined as the probability of selecting the optimal relay by the proposed scheme. In addition, the impacts of the low-interference selection on the SS's capacity and outage probability are also analyzed. The simulation results prove that compared with the max-min selection, the proposed scheme can achieve higher TR values as well as the total capacity which also indicates that a higher spectrum efficiency can be achieved. It is believed that the results of this paper can provide an alternative viewpoint of evaluating the spectrum efficiency and inspire more interesting and important research topics in the future.

This paper presents a method of generating sets of orthogonal and zero-correlation zone (ZCZ) periodic real-valued sequences of period 2n, n ≥ 1. The sequences admit a fast correlation algorithm and the sets of sequences achieve the upper bound on family size. A periodic orthogonal sequence has the periodic autocorrelation function with zero sidelobes, and a set with orthogonal sequences whose mutual periodic crosscorrelation function at zero shift is zero. Similarly, a ZCZ set is the set of the sequences with zero-correlation zone. In this paper, we derive the real-valued periodic orthogonal sequences of period 2n from a real-valued Huffman sequence of length 2ν+1, ν being a positive integer and ν ≥ n, whose aperiodic autocorrelation function has zero sidelobes except possibly at the left and right shift-ends. The orthogonal and ZCZ sets of real-valued periodic orthogonal sequences are useful in various systems, such as synchronous code division multiple access (CDMA) systems, quasi-synchronous CDMA systems and digital watermarkings.

The accurate and fast estimation of link price is the key component of network-based congestion control schemes. A fast estimation method A2DPM is presented. Multiple hashes on IP identifier of packet header are adopted to accelerate the side information transmission, so accurate estimation of maximum price on the flow forwarding path can be realized after the receipt of just a few probe packets, and the sender is capable of reacting to congestion more quickly, making it suitable to meet the demands of dynamic networks.

The aim of this study is to improve the accuracy of flicker parameters estimation in old film sequences in which moving objects are present. Conventional methods tend to fail in flicker parameters estimation due to the effects of moving objects. Our proposed method firstly utilizes an adaptive Gaussian mixture model (GMM)-based method to detect the moving objects in the film sequences, and combines the detected results with the histogram-matched frames to generate reference frames for flicker parameters estimation. Then, on the basis of a linear flicker model, the proposed method uses an M-estimator with the reference frames to estimate the flicker parameters. Experimental results show that the proposed method can effectively improve the accuracy of flicker parameters estimation when the moving objects are present in the film sequences.