Due to the computational complexity of the optimum maximum likelihood detector (OMD) growing exponentially with the number of users, suboptimum techniques have received significant attention. We have proposed the particle swarm optimization (PSO) for the multiuser detection (MUD) in asynchronous multicarrier code division multiple access (MC-CDMA) system. The performance of PSO based MUD is near optimum, while its computational complexity is far less than OMD. Performance of PSO-MUD has also been shown to be better than that of genetic algorithm based MUD (GA-MUD) at practical SNR.

Unforgeability of digital signatures is closely related to the security of hash functions since hashing messages, such as hash-and-sign paradigm, is necessary in order to sign (arbitrarily) long messages. Recent successful collision finding attacks against practical hash functions would indicate that constructing practical collision resistant hash functions is difficult to achieve. Thus, it is worth considering to relax the requirement of collision resistance for hash functions that is used to hash messages in signature schemes. Currently, the most efficient strongly unforgeable signature scheme in the standard model which is based on the CDH assumption (in bilinear groups) is the Boneh-Shen-Waters (BSW) signature proposed in 2006. In their scheme, however, a collision resistant hash function is necessary to prove its security. In this paper, we construct a signature scheme which has the same properties as the BSW scheme but does not rely on collision resistant hash functions. Instead, we use a target collision resistant hash function, which is a strictly weaker primitive than a collision resistant hash function. Our scheme is, in terms of the signature size and the computational cost, as efficient as the BSW scheme.

The MIMO system can meet the growing demand for higher capacity in wireless communication fields. So far, the authors have reported that, based on channel measurements, uncoded performance of narrowband MIMO spatial multiplexing in indoor line-of-sight (LOS) environments generally outperforms that in non-LOS (NLOS) ones under the same transmit power condition. In space-frequency coded MIMO-OFDM spatial multiplexing, however, we cannot expect high space-frequency diversity gain in LOS environments because of high fading correlations and low frequency selectivity of channels so that the performance may degrade unlike uncoded cases. In this letter, we present the practical performance of coded MIMO-OFDM spatial multiplexing based on indoor channel measurements. The results show that an LOS environment tends to provide lower space-frequency diversity effect whereas the MIMO-OFDM spatial multiplexing performance is still better in the environment compared with an NLOS environment.

In this letter we propose a simple adaptive algorithm which solves the unit-norm constrained optimization problem. Instead of conventional parameter norm based normalization, the proposed algorithm incorporates single parameter normalization which is computationally much simpler. The simulation results illustrate that the proposed algorithm performs as good as conventional ones while being computationally simpler.

We propose a new type of direction-of-arrival estimation method for robot audition that is free from strict head related transfer function estimation. The proposed method is based on statistical pattern recognition that employs a ratio of power spectrum amplitudes occurring for a microphone pair as a feature vector. It does not require any phase information explicitly, which is frequently used in conventional techniques, because the phase information is unreliable for the case in which strong reflections and diffractions occur around the microphones. The feature vectors we adopted can treat these influences naturally. The effectiveness of the proposed method was shown from direction-of-arrival estimation tests for 19 kinds of directions: 92.4% of errors were reduced compared with the conventional phase-based method.

Code acquisition performance in the Direct-Sequence Code-Division Multiple-Access (DS/CDMA) communication system is strongly related to the quality of the communication systems. The performance is assessed by (i) code acquisition time; (ii) precision; and (iii) complexity for implementation. This paper applies the method of maximum likelihood (ML) to estimation of propagation delay in DS/CDMA communications, and proposes a low-complexity method for code acquisition. First, a DS/CDMA system model and properties of outputs with a passive matched-filter receiver are reviewed, and a statistical problem in code acquisition is mentioned. Second, an error-controllable code acquisition method based on the maximum likelihood is discussed. Third, a low-complexity ML code acquisition method is proposed. It is shown that the code acquisition time with the low-complexity method is about 1.5 times longer than that with the original ML method, e.g. 13 data periods under 4.96 dB.

In this paper, we propose a reduced-complexity radial basis function (RBF)-assisted decision-feedback equalizer (DFE)-based turbo equalization (TEQ) scheme using a novel extended fuzzy c-means (FCM) algorithm, which not only is comparable in performance to the Jacobian RBF DFE-based TEQ but also is low-complexity. Previous TEQ research has shown that the Jacobian RBF DFE TEQ considerably reduces the computational complexity with similar performance, when compared to the logarithmic maximum a posteriori (Log-MAP) TEQ. In this study, the proposed reduced-complexity RBF DFE TEQ further greatly reduces the computational complexity and is capable of attaining a similar performance in contrast to the Jacobian RBF DFE TEQ in the context of both binary phase-shift keying (BPSK) modulation and 4 quadrature amplitude modulation (QAM). With this proposal, the materialization of the RBF-assisted TEQ scheme becomes more feasible.

Multiply-stacked structures of Si quantum dots (Si-QDs) in gate oxide are attracting much attention because of their potential importance to improve retention characteristics in a high density charge storage. In this work, we have fabricated 6-fold stacked Si-QDs with 2 nm-thick SiO2 interlayers, whose areal dot density and average dot size were 5.71011 cm-2 in each dot layer and 5 nm in height, and studied progress on electron distribution in 6-fold stacked Si-QDs with 2 nm-thick SiO2 interlayers from the measurements of temporal changes in the surface potential after electron charging and discharging locally at room temperature using an AFM/Kelvin probe technique in clean room air. First, by scanning an area of 22 µm2 with the AFM tip biased at +3 V with respect to the substrate in a tapping mode, the area was negatively charged due to electron injection from the substrate to the dot through the bottom tunnel oxide and subsequently, the central part of 100100 nm2 in the pre-charged area was scanned with the tip biased at -3 V to emit the electrons from the Si-QDs to the substrate. As a result, the negative charging level was markedly reduced in the central part in comparison to its peripheral region. And then, the surface potential of the negatively-charged peripheral region was decay monotonously with time as a result of progressive electron tunneling to the substrate. In contrast to this, the temporal change in the surface potential of the central part shows that the electron charging proceeds with time until the surface potential becomes almost the same as that in the peripheral region. This result can be interpreted in terms of lateral spreading of electrons stored in the Si-QDs layer due to the potential difference between the central part and its peripheral region more negatively charged.

In order to overcome the drawback of TVQI and to utilize the property of dimensionality increasing techniques, a novel model for Kernel TV-based Quotient Image employing Gabor analysis is proposed and applied to face recognition with only one sample per subject. To deal with illumination outliers, an enhanced TV-based quotient image (ETVQI) model is first adopted. Then for preprocessed images by ETVQI, a bank of Gabor filters is built to extract features at specified scales and orientations. Lastly, KPCA is introduced to extract final high-order and nonlinear features of extracted Gabor features. According to experiments on the CAS-PEAL face database, our model could outperform Gabor-based KPCA, TVQI and Gabor-based TVQI when they face most outliers (illumination, expression, masking etc.).

Previously proposed batch signature schemes do not allow a signer to generate a signature immediately for sequentially asked signing queries. In this letter, we propose flexible batch signatures which do not need any waiting period and have very light computational overhead. Therefore our schemes are well suited for low power devices.

In this paper, we present an efficient fingerprint classification algorithm which is an essential component in many critical security application systems e.g. systems in the e-government and e-finance domains. Fingerprint identification is one of the most important security requirements in homeland security systems such as personnel screening and anti-money laundering. The problem of fingerprint identification involves searching (matching) the fingerprint of a person against each of the fingerprints of all registered persons. To enhance performance and reliability, a common approach is to reduce the search space by firstly classifying the fingerprints and then performing the search in the respective class. Jain et al. proposed a fingerprint classification algorithm based on a two-stage classifier, which uses a K-nearest neighbor classifier in its first stage. The fingerprint classification algorithm is based on the fingercode representation which is an encoding of fingerprints that has been demonstrated to be an effective fingerprint biometric scheme because of its ability to capture both local and global details in a fingerprint image. We enhance this approach by improving the efficiency of the K-nearest neighbor classifier for fingercode-based fingerprint classification. Our research firstly investigates the various fast search algorithms in vector quantization (VQ) and the potential application in fingerprint classification, and then proposes two efficient algorithms based on the pyramid-based search algorithms in VQ. Experimental results on DB1 of FVC 2004 demonstrate that our algorithms can outperform the full search algorithm and the original pyramid-based search algorithms in terms of computational efficiency without sacrificing accuracy.

Recently, cyber attacks have become a serious hindrance to the stability of Internet. These attacks exploit interconnectivity of networks, propagate in an instant, and have become more sophisticated and evolutionary. Traditional Internet security systems such as firewalls, IDS and IPS are limited in terms of detecting recent cyber attacks in advance as these systems respond to Internet attacks only after the attacks inflict serious damage. In this paper, we propose a hybrid intrusion forecasting system framework for an early warning system. The proposed system utilizes three types of forecasting methods: time-series analysis, probabilistic modeling, and data mining method. By combining these methods, it is possible to take advantage of the forecasting technique of each while overcoming their drawbacks. Experimental results show that the hybrid intrusion forecasting method outperforms each of three forecasting methods.

This letter presents a simple joint estimation method for residual frequency offset (RFO) and sampling frequency offset (STO) in OFDM-based digital video broadcasting (DVB) systems. The proposed method selects a continual pilot (CP) subset from an unsymmetrically and non-uniformly distributed CP set to obtain an unbiased estimator. Simulation results show that the proposed method using a properly selected CP subset is unbiased and performs robustly.

This paper presents a new QoS model for end-to-end service provisioning in multi-hop wireless networks. In legacy IEEE 802.11e based multi-hop wireless networks, the fixed assignment of service classes according to flow's priority at every node causes priority inversion problem when performing end-to-end service differentiation. Thus, this paper proposes a new QoS provisioning model called Dynamic Hop Service Differentiation (DHSD) to alleviate the problem and support effective service differentiation between end-to-end nodes. Many previous works for QoS model through the 802.11e based service differentiation focus on packet scheduling on several service queues with different service rate and service priority. Our model, however, concentrates on a dynamic class selection scheme, called Per Hop Class Assignment (PHCA), in the node's MAC layer, which selects a proper service class for each packet, in accordance with queue states and service requirement, in every node along the end-to-end route of the packet. The proposed QoS solution is evaluated using the OPNET simulator. The simulation results show that the proposed model outperforms both best-effort and 802.11e based strict priority service models in mobile ad hoc environments.

This paper reports the new gate and recess structure design of millimeter-wave, high power pHEMTs, which highly improves humidity resistance and reliability. By using tantalum nitride as the refractory gate metal and a silicon nitride layer prepared by a catalytic chemical vapor deposition technique for passivation of this transistor, strong moisture resistance was obtained without degradation of the device characteristics. Moreover, we have designed a stepped recess structure to increase the on-state breakdown voltage without degradation of the power density of the millimeter-wave pHEMT, according to the analysis based on the new nonlinear drain resistance model. Consequently, the developed pHEMT has shown strong humidity resistance with no degradation of the DC characteristics even after 1000 hours storage at 400 K and 85% humidity, and the high on-state breakdown voltage of over 30 V while keeping the high power density of 0.65 W/mm in the Ka band. In addition, the proposed nonlinear drain resistance model effectively explains this power performance.

This paper presents an asynchronous design technique, an enabler for the emerging technology of flexible microelectronics that feature low-temperature processed polysilicon (LTPS) thin-film transistors (TFT) and surface-free technology by laser annealing/ablation (SUFTLA®). The first design instance chosen is an 8-bit microprocessor. LTPS TFTs are good for realizing displays having integrated VLSI circuit at lower costs. However, LTPS TFTs have drawbacks, including substantial deviations in characteristics and the self-heating phenomenon. To solve these problems, the authors adopted the asynchronous circuit design technique and developed an asynchronous design language called Verilog+, which is based on a subset of Verilog HDL® and includes minimal primitives used for describing the communications between modules, and the dedicated tools including a translator called xlator and a synthesizer called ctrlsyn. The flexible 8-bit microprocessor stably operates at 500 kHz, drawing 180 µA from a 5 V power source. The microprocessor's electromagnetic emissions are 21 dB less than those of the synchronous counterpart.

Phased array antennas are attractive in terms of low cost and power consumption. This paper proposes a controlling scheme based on a bisection method for phased array antennas employing phase shifters with slow switching speed, which is typical for Micro Electro Mechanical Systems (MEMS) switches. Computer simulation results, assuming the IEEE 802.11a Wireless Local Area Network (WLAN) standard, show that the proposed scheme has good gain enhancement capability in multipath fading channels.

Further development of a network based on the Inverse Function Delayed (ID) model which can recall temporal sequences of patterns, is proposed. Additional advantage is taken of the negative resistance region of the ID model and its hysteretic properties by widening the negative resistance region and letting the output of the ID neuron be almost instant. Calling this neuron limit ID neuron, a model with limit ID neurons connected pairwise with conventional neurons enlarges the storage capacity and increases it even further by using a weightmatrix that is calculated to guarantee the storage after transforming the sequence of patterns into a linear separation problem. The network's tolerance, or the model's ability to recall a sequence, starting in a pattern with initial distortion is also investigated and by choosing a suitable value for the output delay of the conventional neuron, the distortion is gradually reduced and finally vanishes.

Motion-compensated frame interpolation (MCFI) is widely used to smoothly display low frame rate video sequences by synthesizing and inserting new frames between existing frames. The temporal shift interpolation technique (TSIT) is popular for frame interpolation of video sequences that are encoded by a block-based video coding standard such as MPEG-4 or H.264/AVC. TSIT assumes the existence of a motion vector (MV) and may not result in high-quality interpolation for intra-mode blocks that do not have MVs. This paper proposes a new frame interpolation algorithm mainly designed for intra-mode blocks. In order to improve the accuracy of pixel interpolation, the new algorithm proposes sub-pixel interpolation and the reuse of MVs for their refinement. In addition, the new algorithm employs two different interpolation modes for inter-mode blocks and intra-mode blocks, respectively. The use of the two modes reduces ghost artifacts but potentially increases blocking effects between the blocks interpolated by different modes. To reduce blocking effects, the proposed algorithm searches the boundary of an object and interpolates all blocks in the object in the same mode. Simulation results show that the proposed algorithm improves PSNR by an average of 0.71 dB compared with the TSIT with MV refinement and also significantly improves the subjective quality of pictures by reducing ghost artifacts.

Various advantages of cooperative peer-to-peer networks are strongly counterbalanced by the open nature of a distributed, serverless network. In such networks, it is relatively easy for an attacker to launch various attacks such as misrouting, corrupting, or dropping messages as a result of a successful identifier forgery. The impact of an identifier forgery is particularly severe because the whole network can be compromised by attacks such as Sybil or Eclipse. In this paper, we present an identifier authentication mechanism called random visitor, which uses one or more randomly selected peers as delegates of identity proof. Our scheme uses identity-based cryptography and identity ownership proof mechanisms collectively to create multiple, cryptographically protected indirect bindings between two peers, instantly when needed, through the delegates. Because of these bindings, an attacker cannot achieve an identifier forgery related attack against interacting peers without breaking the bindings. Therefore, our mechanism limits the possibility of identifier forgery attacks efficiently by disabling an attacker's ability to break the binding. The design rationale and framework details are presented. A security analysis shows that our scheme is strong enough against identifier related attacks and that the strength increases if there are many peers (more than several thousand) in the network.