Spectrum sensing is an important function for dynamic spectrum access (DSA) type cognitive radio systems to detect opportunities for sharing the spectrum with a primary system. The key requirements for spectrum sensing are stability in controlling the probability of false alarm as well as detection performance of the primary signals. However, false alarms can be triggered by noise uncertainty at the secondary devices or unknown interference signals from other secondary systems in realistic radio environments. This paper proposes a robust spectrum sensing method against such uncertainties; it is a kind of cyclostationary feature detection (CFD) approaches. Our proposed method, referred to as maximum cyclic autocorrelation selection (MCAS), compares the peak and non-peak values of the cyclic autocorrelation function (CAF) to detect primary signals, where the non-peak value is the CAF value calculated at cyclic frequencies between the peaks. In MCAS, the desired probability of false alarm can be obtained by setting the number of the non-peak values. In addition, the multiple peak values are combined in MCAS to obtain noise reduction effect and coherent combining gain. Through computer simulations, we show that MCAS can control the probability of false alarm under the condition of noise uncertainty and interference. Furthermore, our method achieves better performance with much less computational complexity in comparison to conventional CFD methods.

This paper reviews applications of fuzzy logic to telecommunications and proposes a novel fuzzy combining scheme for cooperative spectrum sensing in cognitive radio systems. A summary of previous applications of fuzzy logic to telecommunications is given outlining also potential applications of fuzzy logic in future cognitive radio systems. In complex and dynamic operational environments, future cognitive radio systems will need sophisticated decision making and environment awareness techniques that are capable of handling multidimensional, conflicting and usually non-predictable decision making problems where optimal solutions can not be necessarily found. The results indicate that fuzzy logic can be used in cooperative spectrum sensing to provide additional flexibility to existing combining methods.

We propose a method of assigning polarity to causal information extracted from Japanese financial articles concerning business performance of companies. Our method assigns polarity (positive or negative) to causal information in accordance with business performance, e.g. "zidousya no uriage ga koutyou: (Sales of cars are good)" (The polarity positive is assigned in this example). We may use causal expressions assigned polarity by our method, e.g., to analyze content of articles concerning business performance circumstantially. First, our method classifies articles concerning business performance into positive articles and negative articles. Using them, our method assigns polarity (positive or negative) to causal information extracted from the set of articles concerning business performance. Although our method needs training dataset for classifying articles concerning business performance into positive and negative ones, our method does not need a training dataset for assigning polarity to causal information. Hence, even if causal information not appearing in the training dataset for classifying articles concerning business performance into positive and negative ones exist, our method is able to assign it polarity by using statistical information of this classified sets of articles. We evaluated our method and confirmed that it attained 74.4% precision and 50.4% recall of assigning polarity positive, and 76.8% precision and 61.5% recall of assigning polarity negative, respectively.

Alumina supported cobalt-ferrum catalysts were prepared using wet impregnation method by applying 3 different conditions, namely hotplate (A), sonication (B) and soaking (C). The alumina supported cobalt-ferrum catalysts were applied in the synthesis of multi-walled carbon nanotubes (MWNTs) using catalytic chemical vapour deposition (CCVD) technique. The morphology and particle size of the cobalt-ferrum catalysts and the MWNTs yield were examined by field emission-scanning electron microscopy (FE-SEM) while the surface elemental composition of the samples was obtained by energy dispersive X-ray analysis (EDX). The morphology of catalysts A, B and C were found to be different, the particle sizes were ranged from 20-40 nm. The diameters of the MWNTs yield from samples A, B and C were found to be related to the catalyst particle size, thus the smaller the catalyst particle, the thinner the MWNTs obtained. The MWNTs with smaller diameter were obtained with higher purity and quality becuase the nanotube surface are free from amorphous carbon. Therefore, different catalyst preparation methods resulted in different sizes of the catalyst particle in order to synthesize MWNTs with desired diameter.

To realize dynamic spectrum access (DSA), spectrum sensing is performed to detect the presence or absence of primary users (PUs). This paper proposes a sensing architecture. This architecture enables use cases such as DSA with PU detection using a single spectrum sensor and DSA with distributed sensing, such as cooperative sensing, collaborative sensing, and selective sensing. In this paper we focus on distributed sensing. These sensing schemes employ distributed spectrum sensors (DSSs) where each sensor uses energy detection (ED) in Rayleigh fading environment. To theoretically analyze the performance of the three sensing schemes, a closed-form expression for the probability of detection by ED with selective combining (SC) in Rayleigh fading environment is derived. Applying this expression to the PU detection problem, we obtain analytical models of the three sensing schemes. Analysis shows that at 5-dB signal-to-noise ratio (SNR) and with a false alarm rate of 0.004, the probability of detection is increased from 0.02 to 0.3 and 0.4, respectively, by cooperative sensing and collaborative sensing schemes using using three DSSs. Results also show that the selected sensing scheme matches the performance of the collaborative sensing scheme. Moreover, it provides a low false alarm rate.

A 0.4-5.8 GHz SiGe-MMIC quadrature modulator (Q-MOD) employing a self current controlled mixer for cognitive radio is described. The self current controlled mixer consists of a Gilbert cell mixer and a self current control circuit which is composed of both a current feedback circuit and an output buffer amplifier. The self current control circuit automatically controls the mixer current according to the output power level, and improves the linearity over wide radio frequency (RF) range. Simulation results show that the proposed Q-MOD realizes 1 dB compression point (P1 dB) improvement of more than 3.0 dB compared to the conventional Q-MOD at the frequencies of 0.4, 0.8, 1.95, 5.2 and 5.8 GHz. The fabricated Q-MOD achieves P1 dB improvement of more than 2.8 dB under the same condition. It also improves the output power with error vector magnitude (EVM) of 3.0% (Pout@EVM=3.0%), and achieves the Pout improvement of more than 2.7 dB under the modulation conditions of UHF wireless system (OFDM/16QAM, 0.4 GHz), W-CDMA (HPSK/QPSK, 0.8 GHz/1.95 GHz) and wireless-LAN (OFDM/64QAM, 5.2 GHz/5.8 GHz).

Channel estimation is a key baseband processing task in wireless systems. Filtering or smoothing algorithms can improve the accuracy of channel estimates and the Discrete Cosine Transform (DCT) can be used for this purpose. By using the DCT, performance will be improved compared to the straight-forward approach of per subcarrier estimation (PSE). However, the complexity of the DCT is not negligible. This paper proposes a low-complexity channel estimation scheme using the DCT. Simulation results show that the performance is improved by more than 1dB compared with PSE in MIMO-OFDM system.

Estimating a location of mobile phones or sound source is of considerable interest in wireless communications and signal processing. In this letter, we propose squared range weighted least squares (SRWLS) using the range estimate attained from the Taylor series-based maximum likelihood. The weight can be determined more accurately when using the proposed method, compared with the existing methods using the variance of noise. The simulation results show that the proposed method is superior to the existing methods in RMSE as the measurement noise amount of sensors increases.

This paper addresses the problem of optimizing metalization patterns of back-end connections for the power-MOSFET based driver since the back-end connections tend to dominate the on-resistance Ron of the driver. We propose a heuristic algorithm to seek for better geometric shapes for the patterns targeting at minimizing Ron and at balancing the current distribution. In order to speed up the analysis, the equivalent resistance network of the driver is modified by inserting ideal switches to avoid repeatedly inverting the admittance matrix. With the behavioral model of the ideal switch, we can significantly accelerate the optimization. Simulation on three drivers from industrial TEG data demonstrates that our algorithm can reduce Ron effectively by shaping metals appropriately within a given routing area.

High temperature adversely impacts on circuit's reliability, performance, and leakage power. During behavioral synthesis, both resource usage allocation and resource binding influence thermal profile. Current thermal-aware behavioral syntheses do not utilize location information of resources from floorplan and in addition only focus on binding, ignoring allocation. This paper proposes thermal-aware behavioral synthesis with resource usage allocation. Based on a hybrid metric of physical location information and temperature, we rebind operations and reallocate the number of resources under area constraint. Our approach effectively controls peak temperature and creates even power densities among resources of different types and within resources of the same type. Experimental results show an average of 8.6 drop in peak temperature and 5.3% saving of total power consumption with little latency overhead.

The purpose of the paper is to show that boundary implication results hold for complex-valued uncertain linear time-delay systems. The results are derived by the Lambert W function and yield tractable robust stability criteria for simultaneously triangularizable linear time-delay systems. The setting is similar to a recently reported extreme-point result, but the assumed uncertainty sets can be much more free in shape.

We study the online file allocation problem on ring networks. In this paper, we present a 7-competitive randomized algorithm against an adaptive online adversary on uniform cactus graphs. The algorithm is deterministic if the file size is 1. Moreover, we obtain lower bounds of 4.25 and 3.833 for a deterministic algorithm and a randomized algorithm against an adaptive online adversary, respectively, on ring networks.

We propose a video ontology system to overcome semantic gap in video retrieval. The proposed video ontology is aimed at bridging of the gap between the semantic nature of user queries and raw video contents. Also, results of semantic retrieval shows not only the concept of topic keyword but also a sub-concept of the topic keyword using semantic query extension. Through this process, recall is likely to provide high accuracy results in our method. The experiments compared with keyframe-based indexing have demonstrated that this proposed scene-based indexing presents better results in several kinds of videos.

In this paper, an indoor repeater antenna with high isolation for WCDMA application is proposed. The designed repeater has very small separation of 20 mm between the donor and server antennas. The antenna has two resonance frequencies to cover the WCDMA band from 1.92 GHz to 2.17 GHz. The fabricated antenna has VSWR below 1.5, gain over 8 dBi, and isolation between server and donor antennas less than -80 dB in the WCDMA band.

In this paper, we propose a novel method for gathering sensing information by using an orthogonal narrowband signal for cooperative sensing in cognitive radio. It is desirable to improve the spectrum sensing performance by countering the locality effect of a wireless channel; cooperative sensing by using multiple inputs of sensing information from the surrounding sensing nodes has attracted attention. Cooperative sensing requires that sensing information be gathered at the master node for determining the existence of a primary signal. If the used information gathering method leads to redundancies, the total capacity of the secondary networks is not improved. In this paper, we propose a novel method for gathering sensing information that maps the sensing information to the orthogonal narrowband signal to achieve simultaneous sensing information gathering at the master node. In this method, the sensing information is mapped to an orthogonal subcarrier signal of an orthogonal frequency division multiplexing (OFDM) structure to reduce the frequency resource required for sensing information gathering. The orthogonal signals are transmitted simultaneously from multiple sensing nodes. This paper evaluates the performance of the proposed information gathering method and confirms its effectiveness.

In this paper, a novel intra-die spatial correlation extraction method referred to as MLEMTC (Maximum Likelihood Estimation for Multiple Test Chips) is presented. In the MLEMTC method, a joint likelihood function is formulated by multiplying the set of individual likelihood functions for all test chips. This joint likelihood function is then maximized to extract a unique group of parameter values of a single spatial correlation function, which can be used for statistical circuit analysis and design. Moreover, to deal with the purely random component and measurement error contained in measurement data, the spatial correlation function combined with the correlation of white noise is used in the extraction, which significantly improves the accuracy of the extraction results. Furthermore, an LU decomposition based technique is developed to calculate the log-determinant of the positive definite matrix within the likelihood function, which solves the numerical stability problem encountered in the direct calculation. Experimental results have shown that the proposed method is efficient and practical.

This paper presents a Reduced-reference based video-quality estimation method suitable for individual end-user quality monitoring of IPTV services. With the proposed method, the activity values for individual given-size pixel blocks of an original video are transmitted to end-user terminals. At the end-user terminals, the video quality of a received video is estimated on the basis of the activity-difference between the original video and the received video. Psychovisual weightings and video-quality score adjustments for fatal degradations are applied to improve estimation accuracy. In addition, low-bit-rate transmission is achieved by using temporal sub-sampling and by transmitting only the lower six bits of each activity value. The proposed method achieves accurate video quality estimation using only low-bit-rate original video information (15 kbps for SDTV). The correlation coefficient between actual subjective video quality and estimated quality is 0.901 with 15 kbps side information. The proposed method does not need computationally demanding spatial and gain-and-offset registrations. Therefore, it is suitable for real-time video-quality monitoring in IPTV services.

In this paper, we demonstrate a 10.66 Gb/s bidirectional TDM over long-reach WDM hybrid PON supported by distributed Raman amplification, and the power budget margin is measured to be 15 dB for downstream transmission and 12 dB for upstream transmission, with dual Raman pump power of 300 mW.

3D graphics application is widely used in consumer electronics which is an inevitable tendency in the future. In general, the higher abstraction level is used to model a complex system like 3D graphics SoC. However, the concerned issue is that how to use efficient methods to traverse design space hierarchically, reduce simulation time, and refine the performance fast. This paper demonstrates a system-level design space exploration model for a tile-based 3D graphics SoC refinement. This model uses UML tools which can assist designers to traverse the whole system and reduces simulation time dramatically by adopting SystemC. As a result, the system performance is improved 198% at geometry function and 69% at rendering function, respectively.

Partial forwarding is a design method to place forwarding paths on a part of processor pipeline. Hardware cost of processor can be reduced without performance loss by partial forwarding. However, compiler with the instruction scheduler which considers partial forwarding structure of the target processor is required since conventional scheduling algorithm cannot make the most of partial forwarding structure. In this paper, we propose a heuristic instruction scheduling method for processors with partial forwarding structure. The proposed algorithm uses available distance to schedule instructions which are suitable for the target partial forwarding processor. Experimental results show that the proposed method generates near-optimal solutions in practical time and some of the optimized codes for partial forwarding processor run in the shortest time among the target processors. It also shows that the proposed method is superior to hazard detection unit.