Traditional TCP has a good congestion control strategy that adapts its sending rate in accordance with network congestion. In addition, a fast recovery algorithm can help TCP achieve better throughput by responding to temporary network congestion well. However, if multiple packet losses occur, the time to enter congestion avoidance phase would be delayed due to the long recovery time. Moreover, during the recovery phase, TCP freezes congestion window size until all lost packets are recovered, and this can make recovery time much longer resulting in performance degradation. To mitigate such recovery overhead, we propose Momentary recovery algorithm that recovers packet loss without an extra recovery phase. As other TCP and variants, our algorithm also halves the congestion window size when packet drop is detected, but it performs congestion avoidance phase immediately as if loss recovery is completed. For lost packets, TCP sender transmits them along with normal packets as long as congestion window permits rather than performs fast retransmission. In this manner, we can eliminate recovery overhead efficiently and reach steady state momentarily after network congestion. Finally, we provide a simulation based study on TCP recovery behaviors and confirm that our Momentary recovery algorithm always shows better performance compared with NewReno, SACK, and FACK.

When cognitive radio (CR) systems dynamically use the frequency band, a control signal is necessary to indicate which carrier frequencies are currently available in the network. In order to keep efficient spectrum utilization, this control signal also should be transmitted based on the channel conditions. If transmitters dynamically select carrier frequencies, receivers have to receive control signals without knowledge of their carrier frequencies. To enable such transmission and reception, this paper proposes a novel scheme called DCPT (Differential Code Parallel Transmission). With DCPT, receivers can receive low-rate information with no knowledge of the carrier frequencies. The transmitter transmits two signals whose carrier frequencies are spaced by a predefined value. The absolute values of the carrier frequencies can be varied. When the receiver acquires the DCPT signal, it multiplies the signal by a frequency-shifted version of the signal; this yields a DC component that represents the data signal which is then demodulated. The performance was evaluated by means of numerical analysis and computer simulation. We confirmed that DCPT operates successfully even under severe interference if its parameters are appropriately configured.

Carbon nanofibers (CNFs) were fabricated on graphite plates using "Ar+ ion sputtering method" in large amount at room temperature. The morphology of CNFs was controlled by a simultaneous carbon supply during ion sputtering. CNF-tipped cones were formed on graphite plate surfaces without carbon supply whereas those with a simultaneous carbon supply featured mainly needle-like protrusions of large size. The field electron emission (FE) properties, measured using parallel plate configurations in 10-4 Pa range, showed the threshold fields of 4.4 and 5.2 V/µm with a current density of 1 µA/cm2 for CNF-tipped cones and needle-like protrusion, respectively. Reliability test results indicated that CNF-tipped cones were more stable than needle-like protrusion. The morphological change after reliability test showed a so-called "self-regenerative" process and structure damage for CNF-tipped cones and needle-like protrusions, respectively.

A 2 to 5 GHz-band self frequency dividing quadrature mixer utilizing current re-use configuration with small size and broad band operation is proposed for a direct conversion receiver and a low-IF receiver of cognitive radio. The proposed mixer operates at twice the LO frequency by directly using a static type flip-flop frequency divider as the LO switching circuit for quadrature signal generation. The current re-use configuration is realized because the dc current of the frequency divider and the RF common-emitter amplifier share the same current flow path. Simulations and experiments verify that the proposed mixer offers broad band operation, miniaturization, and low power consumption. The mixer IC fabricated by 0.35 µm SiGe-BiCMOS technology achieved the conversion gain of 20.6 dB, noise figure of 11.9 dB and EVM for π/4-shift QPSK signal of 4.4% at 2.1 GHz with power consumption of 15 mW and size of 0.22 0.31 mm2. For the confirmation of broad band operation, the characteristics of conversion gain and noise figure were measured at 5.2 GHz. The proposed mixer could operate at 5.2 GHz with enough conversion gain, but the noise figure was inferior to that of 2.1 GHz. Therefore the further investigation and improvement about the noise figure will be needed for higher frequency.

In this paper, we use frequency-domain equalization (FDE) to create coherent optical single-carrier (CO-SC) transmission systems that are very tolerant of chromatic dispersion (CD) and polarization mode dispersion (PMD). The efficient transmission of a 25-Gb/s NRZ-QPSK signal by using the proposed FDE is demonstrated under severe CD and PMD conditions. We also discuss the principle of FDE and some techniques suitable for implementing CO-SC-FDE. The results show that a CO-SC-FDE system is very tolerant of CD and PMD and can achieve high transmission rates over single mode fiber without optical dispersion compensation.

Since multiview video coding (MVC) based on H.264/AVC uses a prediction scheme exploiting inter-view correlation among multiview video, MVC encoder compresses multiple views more efficiently than simulcast H.264/AVC encoder. However, in case that the number of views to be encoded increases in MVC, the total encoding time will be greatly increased. To reduce computational complexity in MVC, a fast mode decision using both Macroblock-based region segmentation information and global disparity vector among views is proposed to reduce the encoding time. The proposed method achieves on the average 1.5 2.9 reduction of the total encoding time with the PSNR (Peak Signal-to-Noise Ratio) degradation of about 0.05 dB.

This paper presents an error diagnosis technique for incremental synthesis, called EXLLS (Extended X-algorithm for LUT-based circuit model based on Location sets to rectify Subcircuits), which rectifies five or more functional errors in the whole circuit based on location sets to rectify subcircuits. Conventional error diagnosis technique, called EXLIT, tries to rectify five or more functional errors based on incremental rectification for subcircuits. However, the solution depends on the selection and the order of modifications on subcircuits, which increases the number of locations to be changed. To overcome this problem, we propose EXLLS based on location sets to rectify subcircuits, which obtains two or more solutions by separating i) extraction of location sets to be rectified, and ii) rectification for the whole circuit based on the location sets. Thereby EXLLS can rectify five or more errors with fewer locations to change. Experimental results have shown that EXLLS reduces increase in the number of locations to be rectified with conventional technique by 90.1%.

In this paper, we propose a Modified nested sparse grid based Adaptive Stochastic Collocation Method (MASCM) for block-based Statistical Static Timing Analysis (SSTA). The proposed MASCM employs an improved adaptive strategy derived from the existing Adaptive Stochastic Collocation Method (ASCM) to approximate the key operator MAX during timing analysis. In contrast to ASCM which uses non-nested sparse grid and tensor product quadratures to approximate the MAX operator for weakly and strongly nonlinear conditions respectively, MASCM proposes a modified nested sparse grid quadrature to approximate the MAX operator for both weakly and strongly nonlinear conditions. In the modified nested sparse grid quadrature, we firstly construct the second order quadrature points based on extended Gauss-Hermite quadrature and nested sparse grid technique, and then discard those quadrature points that do not contribute significantly to the computation accuracy to enhance the efficiency of the MAX approximation. Compared with the non-nested sparse grid quadrature, the proposed modified nested sparse grid quadrature not only employs much fewer collocation points, but also offers much higher accuracy. Compared with the tensor product quadrature, the modified nested sparse grid quadrature greatly reduced the computational cost, while still maintains sufficient accuracy for the MAX operator approximation. As a result, the proposed MASCM provides comparable accuracy while remarkably reduces the computational cost compared with ASCM. The numerical results show that with comparable accuracy MASCM has 50% reduction in run time compared with ASCM.

The public safety spectrum is generally under-utilized due to the unique traffic characteristics of bursty and mission critical. This letter considers the application of dynamic spectrum access (DSA) to the combined spectrum of public safety (PS) and commercial (CMR) users in a common shared network that can provide both PS and CMR services. Our scenario includes the 700 MHz Public/Private Partnership which was recently issued by the Federal Communications Commission. We first propose an efficient DSA mechanism to coordinate the combined spectrum, and then establish a call admission control that reflects the proposed DSA in a wideband code division multiple access based network. The essentials of our proposed DSA are opportunistic access to the public safety spectrum and priority access to the commercial spectrum. Simulation results show that these schemes are well harmonized in various network environments.

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.

In this paper, a sidelobe suppression technique for orthogonal frequency division multiplexing (OFDM)-based cognitive radios (CR) is proposed. In the OFDM-based CR systems, after the CR terminal executes spectrum sensing, it transmits a CR packet by activating the subcarriers in the frequency bands where no signals are detected (hereinafter, these subcarriers are called "active subcarrier") and by disabling (nulling) the subcarriers in the frequency bands where the signals are detected. In this situation, a problem arises in that the signals that leak from the active subcarriers to the null subcarriers may interfere with the primary systems. Therefore, this signal leakage has to be minimized. In many OFDM-based wireless communication systems, one packet or frame consists of multiple OFDM symbols and the discontinuity between the consecutive OFDM symbols causes the signal leakage to the null subcarriers. In the proposed method, signal leakage to the null subcarriers is suppressed by regenerating null subcarriers in the frequency-domain signal of the whole packet as follows. One CR packet consisting of multiple OFDM symbols having null subcarriers and guard interval (GI) is buffered and oversampled, and then the oversampled signal is Fourier transformed at once and consequently the frequency-domain signal of the packet is obtained. The null subcarriers in the frequency-domain signal are zeroed again, and then the signal is inverse Fourier transformed and transmitted. The proposed method significantly suppresses the signal leakage. The spectral power density, the peak-to-average power ratio (PAPR) and the packet error rate (PER) performances of the proposed method are evaluated by computer simulations and the effectiveness of the proposed method is shown.

In this paper, a novel decentralised dynamic sub-carrier assignment (DSA) algorithm for orthogonal frequency division multiple access (OFDMA)-based adhoc and cellular networks operating in time division duplexing (TDD) mode is proposed to solve the hidden and exposed node problem in media access control (MAC). This method reduces the co-channel interference (CCI), and thus increases the overall throughput of the network. Reduced CCI and increased throughput can be achieved, if time and frequency selectivity of the multi-path fading channel and the channel reciprocity offered by the TDD are fully exploited. The time and frequency selectivity of the channel are usually the main problem in mobile communication. However, in the context of channel assignment for OFDMA-based networks in TDD mode, the time and frequency selectivity of the channel are the key to reduce the interference. In the proposed channel assignment mechanism, several clusters of sub-carriers are assigned for data transmission between a transmitter and a receiver only if the corresponding channels of those sub-carriers linking this transmitter to potential victim receivers are deeply faded. In addition, the proposed algorithm works in a fully decentralised fashion and, therefore, it is able to effectively support ad hoc and multihop communication as well as network self-organisation. Numerical results show that the throughput obtained by the proposed approach for a given quality of service is higher than those of the conventional methods in any precondition of adhoc geographic scenario.

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.

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.

Interface state density was estimated from diode factor n of SiC MIS Schottky diode. The interface state density was the order of 1012 cm-2eV-1, and was same order to the value for the sample carefully prepared by oxidation and post oxidation annealing. The interface state density determined from n was consistent to the value calculated from the capacitance voltage curve of SiO2/nitride/SiC MIS diode by Terman method. High temperature nitridation was effective to reduce the interface state density.

The synthesis of single- and double-wall carbon nanotubes by gas flow-modified, catalyst-supported chemical vapor deposition (CCVD) is reported. We have investigated the gas flow condition dependence on the synthesis of carbon nanotubes (CNTs) by placing blocks in the CCVD reactor. Carbon nanotubes having large diameters are preferentially grown under turbulent flow conditions. This indicates that the diameter distribution of CNTs can be controlled by modification of the gas flow condition in the CCVD.

In this paper, we present a novel analysis approach for large on-chip power grid circuit analysis. The new approach, called ETBR for extended truncated balanced realization, is based on model order reduction techniques to reduce the circuit matrices before the simulation. Different from the (improved) extended Krylov subspace methods EKS/IEKS, ETBR performs fast truncated balanced realization on response Gramian to reduce the original system. ETBR also avoids the adverse explicit moment representation of the input signals. Instead, it uses spectrum representation in frequency domain for input signals by fast Fourier transformation. The proposed method is very amenable for threading-based parallel computing, as the response Gramian is computed in a Monte-Carlo-like sampling style and each sampling can be computed in parallel. This contrasts with all the Krylov subspace based methods like the EKS method, where moments have to be computed in a sequential order. ETBR is also more flexible for different types of input sources and can better capture the high frequency contents than EKS, and this leads to more accurate results especially for fast changing input signals. Experimental results on a number of large networks (up to one million nodes) show that, given the same order of the reduced model, ETBR is indeed more accurate than the EKS method especially for input sources rich in high-frequency components. If parallel computing is explored, ETBR can be an order of magnitude faster than the EKS/IEKS method.

In recent VLSI systems, signal propagation delays are requested to achieve the specifications with very high accuracy. In order to meet the specifications, the routing of a net often needs to be detoured in order to increase the routing delay. A routing method should utilize a routing area with obstacles as much as possible in order to realize the specifications of nets simultaneously. In this paper, a fast longer path algorithm that generates a path of a net in routing grid so that the length is increased as much as possible is proposed. In the proposed algorithm, an upper bound for the length in which the structure of a routing area is taken into account is used. Experiments show that our algorithm utilizes a routing area with obstacles efficiently.

In this paper, we propose a routing method for 2-layer ball grid array packages that generates a routing pattern satisfying a design rule. In our proposed method, the routing structure on each layer is restricted while keeping most of feasible patterns to efficiently obtain a feasible routing pattern. A routing pattern that satisfies the design rule is formulated as a mixed integer linear programming. In experiments with seven data, we obtain a routing pattern such that satisfies the design rule within a practical time by using a mixed integer linear programming solver.

The extraction of verb synonyms is a key technology to build a verb dictionary as a language resource. This paper presents a co-clustering-based verb synonym extraction approach that increases the number of extracted meanings of polysemous verbs from a large text corpus. For verb synonym extraction with a clustering approach dealing with polysemous verbs can be one problem issue because each polysemous verb should be categorized into different clusters depending on each meaning; thus there is a high possibility of failing to extract some of the meanings of polysemous verbs. Our proposed approach can extract the different meanings of polysemous verbs by recursively eliminating the extracted clusters from the initial data set. The experimental results of verb synonym extraction show that the proposed approach increases the correct verb clusters by about 50% with a 0.9% increase in precision and a 1.5% increase in recall over the previous approach.