As MOS transistors are scaled down, the impact of randomly placed discrete charge (impurity atoms, traps and surface states) on device characteristics rapidly increases. Significant variability caused by random dopant fluctuation (RDF) is a direct result of this, which urges the adoption of new device architectures (ultra-thin body SOI FETs and FinFETs) which do not use impurity for body doping. Variability caused by traps and surface states, such as random telegraph noise (RTN), though less significant than RDF today, will soon be a major problem. The increased complexity of such residual-charge-induced variability due to non-Gaussian and time-dependent behavior will necessitate new approaches for variation-aware design.

This paper presents a new common-mode stabilization method for a CMOS differential cascode Class-E power amplifier with LC-tank based driver stage. The stabilization method is based on the identification of the poles and zeros of the closed-loop transfer function at a critical node. By adding a series resistor at the common-gate node of the cascode transistor, the right-half-plane poles are moved to the left half plane, improving the common-mode stability. The simulation results show that the new method is an effective way to stabilize the PA.

In this paper, we discuss a fundamental theory of incremental verification for workflows. Incremental verification is a method to help multiple designers share and collaborate on huge workflows while maintaining their consistency. To this end, we introduce passbacks in workflows and their consistency property in the control flow perspective. passbacks indicate redoing of works. Workflows with passbacks are useful to naturally represent human works. To define the consistency property above, we define normality of workflows with passbacks and total correctness of normal workflows based on transition system-based semantics of normal workflows. We further extend workflows to sorted workflows and define their vertical division and composition. We also extend total correctness to normal sorted workflows, for the sake of incremental verification of a large-scale workflow with passbacks via vertical division and composition.

AspectM, an aspect-oriented modeling (AOM) language, provides not only basic modeling constructs but also an extension mechanism called metamodel access protocol (MMAP) that allows a modeler to modify the metamodel. MMAP consists of metamodel extension points, extension operations, and primitive predicates for navigating the metamodel. Although the notion of MMAP is useful, it needs tool support. This paper proposes a method for implementing a MMAP-based AspectM support tool. It consists of model editor, model weaver, and model verifier. We introduce the notion of edit-time structural reflection and extensible model weaving. Using these mechanisms, a modeler can easily construct domain-specific languages (DSLs). We show a case study using the AspectM support tool and discuss the effectiveness of the extension mechanism provided by MMAP. As a case study, we show a UML-based DSL for describing the external contexts of embedded systems.

The identification of functional and non-functional concerns is an important activity during requirements analysis. However, there may be conflicts between the identified concerns, and they must be discovered and resolved through trade-off analysis. Aspect-Oriented Requirements Engineering (AORE) has trade-off analysis as one of its goals, but most AORE approaches do not actually offer support for trade-off analysis; they focus on describing concerns and generating their composition. This paper proposes an approach for trade-off analysis based on AORE using use cases and the Requirements Conflict Matrix (RCM) to represent compositions. RCM shows the positive or negative effect of non-functional concerns over use cases and other non-functional concerns. Our approach is implemented within a tool called E-UCEd (Extended Use Case Editor). We also show the results of evaluating our tool.

Defining quality requirements completely and correctly is more difficult than defining functional requirements because stakeholders do not state most of quality requirements explicitly. We thus propose a method to measure a requirements specification for identifying the amount of quality requirements in the specification. We also propose another method to recommend quality requirements to be defined in such a specification. We expect stakeholders can identify missing and unnecessary quality requirements when measured quality requirements are different from recommended ones. We use a semi-formal language called X-JRDL to represent requirements specifications because it is suitable for analyzing quality requirements. We applied our methods to a requirements specification, and found our methods contribute to defining quality requirements more completely and correctly.

In this paper, the problem of control reconfiguration in the presence of actuator failure preserving the nominal controller is addressed. In the actuator failure condition, the processing algorithm of the control signal should be adapted in order to re-achieve the desired performance of the control loop. To do so, the so-called reconfiguration block, is inserted into the control loop to reallocate nominal control signals among the remaining healthy actuators. This block can be either a constant mapping or a dynamical system. In both cases, it should be designed so that the states or output of the system are fully recovered. All these situations are completely analysed in this paper using a novel structural approach leading to some theorems which are supported in each section by appropriate simulations.

In this letter, a new approach to segment depth-of-field (DoF) images is proposed. The methodology is based on a two-stage model of visual neuron. The first stage is a retinal filtering by means of luminance normalizing non-linearity. The second stage is a V1-like filtering using filters estimated by independent component analysis (ICA). Segmented image is generated by the response activity of the neuron measured in terms of kurtosis. Results demonstrate that the model can discriminate image parts in different levels of depth-of-field. Comparison with other methodologies and limitations of the proposed methodology are also presented.

As process technology is scaled down, a typical system on a chip (SoC) becomes denser. In scaled process technology, process variation becomes greater and increasingly affects the SoC circuits. Moreover, the process variation strongly affects network-on-chips (NoCs) that have a synchronous network across the chip. Therefore, its network frequency is degraded. We propose a process-variation-adaptive NoC with a variation-adaptive variable-cycle router (VAVCR). The proposed VAVCR can configure its cycle latency adaptively on a processor core basis, corresponding to the process variation. It can increase the network frequency, which is limited by the process variation in a conventional router. Furthermore, we propose a variable-cycle pipeline adaptive routing (VCPAR) method with VAVCR; the proposed VCPAR can reduce packet latency and has tolerance to network congestion. The total execution time reduction of the proposed VAVCR with VCPAR is 15.7%, on average, for five task graphs.

In this paper, a theoretical analysis of current-controlled (CC-) MOS current mode logic (MCML) is reported. Furthermore, the circuit performance of the CC-MCML with the auto-detection of threshold voltage (Vth) fluctuation is evaluated. The proposed CC-MCML with the auto-detection of Vth fluctuation automatically suppresses the degradation of circuit performance induced by the Vth fluctuations of the transistors automatically, by detecting these fluctuations. When a Vth fluctuation of ± 0.1 V occurs on the circuit, the cutoff frequency of the circuit is increased from 0 Hz to 3.5 GHz by using the proposed CC-MCML with the auto-detection of Vth fluctuation.

In this paper, we propose a test generation method for diagnosing transition faults. The proposed method assumes launch on capture test, and it generates test vectors for given fault pairs using a stuck-at ATPG tool so that they can be distinguished. If a given fault pair is indistinguishable, it is identified, and thus the proposed method achieves a complete diagnostic test generation. The conditions for distinguishing a fault pair are carefully considered, and they are transformed into the conditions of the detection of a stuck-at fault, and some additional logic gates are inserted in a CUT during the test generation process. Experimental results show that the proposed method can generate test vectors for distinguishing the fault pairs that are not distinguished by commercial tools, and also identify indistinguishable fault pairs.

In this letter, we apply dynamic software updating to long-lived applications on the DDS middleware while minimizing service interruption and satisfying Quality of Service (QoS) requirements. We dynamically updated applications which run on a commercial DDS implementation to demonstrate the applicability of our approach to dynamic updating. The results show that our update system does not impose an undue performance overhead–all patches could be injected in less than 350 ms and the maximum CPU usage is less than 17%. In addition, the overhead on application throughput due to dynamic updates ranged from 0 to at most 8% and the deadline QoS of the application was satisfied while updating.

In a large queuing system, the effect of the ratio of the filled data on the queue and waiting time from the head of a queue to the service gate are important factors for process efficiency because they are too large to ignore. However, many research works assumed that the factors can be considered to be negligible according to the queuing theory. Thus, the existing queuing models are not applicable to the design of large-scale systems. Such a system could be used as a product classification center for a home delivery service. In this paper, we propose a tree-queue model for large-scale systems that is more adaptive to efficient processes compared to existing models. We analyze and design a mean waiting time equation related to the ratio of the filled data in the queue. Based on simulations, the proposed model demonstrated improvement in process-efficiency, and it is more suitable to realistic system modeling than other compared models for large-scale systems.

Non-negative matrix factorization (NMF) is widely used for monaural musical sound source separation because of its efficiency and good performance. However, an additional clustering process is required because the musical sound mixture is separated into more signals than the number of musical tracks during NMF separation. In the conventional method, manual clustering or training-based clustering is performed with an additional learning process. Recently, a clustering algorithm based on the mel-frequency cepstrum coefficient (MFCC) was proposed for unsupervised clustering. However, MFCC clustering supplies limited information for clustering. In this paper, we propose various timbre features for unsupervised clustering and a clustering algorithm with these features. Simulation experiments are carried out using various musical sound mixtures. The results indicate that the proposed method improves clustering performance, as compared to conventional MFCC-based clustering.

In this paper, we consider an amplify-and-forward cooperative wireless network in which network nodes use multiple input multiple output (MIMO) spatial division multiplexing (SDM) to communicate with one another. We examine the problem of distributed cooperative relay selection and signal combining at the destination. First, we propose three distributed relay selection algorithms based on the maximum channel gains, the maximum harmonic mean of the channel gains, and the minimum mean squared error (MSE) of the signal estimation. Second, we propose a minimum mean square error (MMSE) signal combining scheme which jointly serves as the optimal signal combiner and interference canceler. It is shown that the MSE selection together with the MMSE combining achieves the maximal diversity gain. We also show that in MIMO-SDM cooperative networks increasing the number of candidate nodes does not help to improve the BER performance as opposed to the cooperative networks where each node is equipped with only single antenna. A practical approach to implementation of the combiner based on the current wireless access network protocols will also be presented.

In this paper, we propose a joint diversity algorithm for error-rate minimization in multi-user spatial multiplexing (SM) systems with block diagonalization (BD)-precoding. The proposed algorithm adapts or selects the user set, transmit antenna subset, and the number of streams by an exhaustive search over the available resources. The proposed algorithm makes use of the multi-user diversity (MUD) and the spatial diversity gains as well as the array gain through selecting the best set. Exhaustive search, however, imposes a heavy burden in terms of computational complexity which exponentially increases with the size of the total number of users, streams, and transmit antennas. For complexity reduction, we propose two suboptimal algorithms which reduce the search space by first selecting the best user or by both selecting the best user and fixing the number of streams. Simulation results show that the proposed algorithms improve error probability over the conventional algorithm due to their diversity improvement and the signal-to-noise ratio (SNR) gains over the conventional algorithm. We also show that the suboptimal algorithms significantly reduce the computational complexity over exhaustive search with low-SNR loss.

This paper proposes a heterogeneous wireless network with handover in the application layer. The proposed network requires no upgrade of wireless infrastructure and mobile terminals to convert the present homogeneous networks to the proposed heterogeneous network. Only installing application programs on the content server side and the mobile terminal side is required. The performance of the proposed network has been evaluated in a field trial using a mobile broadband wireless access (MBWA) air interface with wide coverage and a wireless local area network (WLAN) air interface with high throughput. The field trial results show that the maximum value of the handover outage time is only 170 ms. The proposed heterogeneous wireless network is promising since both high throughput and wide coverage area are attained by a combination of the proposed handover scheme with the present homogeneous wireless networks.

We propose a network coordinated opportunistic beamforming (NC-OBF) protocol for downlink K-cell networks with M-antenna base stations (BSs). In the NC-OBF scheme, based on pseudo-randomly generated BF vectors, a user scheduling strategy is introduced, where each BS opportunistically selects a set of mobile stations (MSs) whose desired signals generate the minimum interference to the other MSs. Its performance is then analyzed in terms of degrees-of-freedom (DoFs). As our achievability result, it is shown that KM DoFs are achievable if the number N of MSs in a cell scales at least as SNRKM-1, where SNR denotes the received signal-to-noise ratio. Furthermore, by deriving the corresponding upper bound on the DoFs, it is shown that the NC-OBF scheme is DoF-optimal. Note that the proposed scheme does not require the global channel state information and dimension expansion, thereby resulting in easier implementation.

We propose a new cognitive radio network architecture using the IP multimedia subsystem (IMS) functionality. We implement the cognitive radio network entities standardized in IEEE 1900.4 on the IMS that exchanges RAN and terminal context information between the networks and the terminals to make optimum and immediate reconfiguration decisions. In our proposed architecture, RAN context information is obtained from cellular networks which are directly connected to the IMS. The presence management functions of the IMS are applied to exchange those information in a “push” manner, which enables immediate notification of changes in wireless environment. We evaluate the performance of the proposed context information exchange method, by comparing with the cases that adequate and immediate RAN context information is not available. The evaluation results show that the proposed framework gives 10–30% superior performance than the conventional cognitive radio networks.