In this paper, a frequency domain adaptive antenna array (FDAAA) algorithm is proposed for broadband single-carrier uplink transmissions in a cellular system. By employing AAA weight control in the frequency domain, the FDAAA receiver is able to suppress the multi-user interference (MUI) and the co-channel interference (CCI). In addition, the channel frequency selectivity can be exploited to suppress the inter-symbol interference (ISI) and to obtain frequency diversity (or the multi-path diversity). Another advantage of the FDAAA algorithm is that its performance is not affected by the spread of angles of arrival (AOA) of the received multi-path signal. In this study the structure of FDAAA receiver is discussed and the frequency domain signal-to-interference-plus-noise-ratio (SINR) after weight control is investigated. The performance of the FDAAA algorithm is confirmed by simulation results. It is shown that, the optimal FDAAA weight to obtain the best BER performance is that which fully cancels the interference when single-cell system is considered; On the other hand, when multi-cell cellular system is considered, the optimal FDAAA weight depends on both the cellular structure and the target signal to noise ratio (SNR) of transmit power control (TPC).

This paper introduces a hard handover strategy with a novel adaptive hysteresis adjustment that is needed to reduce handover drop rate in 3GPP long term evolution (LTE). First of all, we adopt a Hybrid handover scheme considering both the received signal strength (RSS) and the load information of the adjacent evolved Node Bs (eNBs) as a factor for deciding the target eNB. The Hybrid scheme causes the load status between the adjacent eNBs to be largely similar. Then, we propose a modified load-based adaptive hysteresis scheme to find a suitable handover hysteresis value utilizing the feature of the small load difference between the target and serving eNBs obtained from the result of the Hybrid scheme. As a result, through the proposed modified load-based adaptive hysteresis scheme, the best target cell is very well selected according to the dynamically changing communication environments. The simulation results show that the proposed scheme provides good performance in terms of handover drop rate.

Cognitive radio in network core devices, such as basestations, is being considered as a spectrum management solution for future society's communication demands. Aside from new resource allocation algorithms, efficient inter- and intra-protocol processing should be considered. In this paper, we propose an opportunistic cross layer architecture called COmmon Layer Architecture (COLA) for information exchange between arbitrary layers in New Generation Networks with network-oriented cognitive radio. COLA provides a means for faster information exchange between OSI layers by introducing abstraction at each layer and designing primitives for communication between each abstraction layer. Emulation and simulation results showed improvements, compared to conventional networks, in disrupted service (42% reduction), average delay (47% reduced) and packet drop ratio (22% reduced) in the scenario analyzed.

This study demonstrates the ability of a portable X-band Doppler weather radar (XDR) to measure Doppler velocity (Vd). Existing portable X-band weather radars are housed in a container and hence have to be carried by a truck. Therefore they have limitations in their installation places. For installations at small areas where the existing X-band weather radars cannot be installed (e.g., rooftop area of small building), XDR is designed to be carried by a cart. Components of the outdoor unit (a parabolic antenna with a diameter of 1.2 m, magnetron transmitter, and radio frequency (RF) and intermediate frequency (IF) analog components) are housed in a compact body with a weight less than 300 kg. The radar operation, IF digital processing, and data storage are carried out by a desktop computer having a commercial IF digital receiver. In order to attain the required portability and reduced purchase and running costs, XDR uses a magnetron transmitter. Because XDR is the first that utilizes an IF digital receiver for the signal processing specific to magnetron transmitters (i.e., the phase correction of received signals due to the randomness of the transmitted pulse phase), Vd measured by XDR (hereafter VdXDR) was assessed. Using the dataset collected from 25 to 26 October 2009 at the Shigaraki MU Observatory (3451'N, 13606'E), the equivalent radar reflectivity factor (Ze) and VdXDR were assessed using Ze and Vd measured by a Micro Rain Radar and a L-band Doppler radar named LQ-7. The results using correlation coefficients and regression lines demonstrate that XDR measured Ze and Vd accurately. The results also show that IF digital receivers are useful for providing magnetron weather radars with the function of Vd measurement, and further suggest that a combination of IF digital receiver and magnetron transmitter contributes to future development of Doppler weather radars, because high cost performance is strongly required for a precipitation monitoring radar network.

A new compact form of the sliding window recursive least squares (SWRLS) algorithm, the I-SWRLS algorithm, is derived using an indefinite matrix. The resultant algorithm has a form similar to that of the traditional recursive least squares (RLS) algorithm, and is more computationally efficient than the conventional SWRLS algorithm including two Riccati equations. Furthermore, a computationally reduced version of the I-SWRLS algorithm is developed utilizing a shift property of the correlation matrix of input data. The resulting fast algorithm reduces the computational complexity from O(N2) to O(N) per iteration when the filter length (tap number) is N, but retains the same tracking performance as the original algorithm. This fast algorithm is much easier to implement than the existing SWC FTF algorithms.

In this paper, a differential input/output linear MOS transconductor using an adaptively biasing technique is proposed. The proposed transconductor based on a differential pair is linearized by employing an adaptively biasing circuit. The linear characteristic of the individual differential output currents are obtained by introducing the adaptively biased currents to terminate the differential output terminals. Using the proposed technique, the common-mode rejection ration (CMRR) becomes high. Simulation results show that the proposed technique is effective for improvement of the linearity and other performances.

Simple half-duplex repetition-based relaying protocols can achieve spatial diversity at the expense of additional relaying signals in the time domain. In this paper, a linear unitary precoder based on a singular vector for cooperative systems with the amplify-and-forward (AF) relaying protocol is proposed in order to improve spectral efficiency. An exact expression of the precoder design is first derived for the case of equal power allocation. Then, water-filling power allocation is used in conjunction with the precoder to further increase the system capacity, where the precoder matrix is generated with an iterative process. From the implementation point of view, the channel state information (CSI) has to be estimated and quantized in systems, the detail of which is described in the sequel. The adaptive modulation and coding (AMC) technique with the proposed precoder is also discussed to achieve high throughput performance. Finally, numerical and simulation results are presented to demonstrate the effectiveness of the proposed technique in improving capacity and throughput.

In this paper, we propose a memory-efficient structure for a pulse Doppler radar in order to reduce the hardware's complexity. The conventional pulse Doppler radar is computed by fast frequency transform (FFT) of all range cells in order to extract the velocity of targets. We observed that this method requires a huge amount of memory to perform the FFT processes for all of the range cells. Therefore, instead of detecting the velocity of all range cells, the proposed architecture extracts the velocity of the targets by using the cells related to the moving targets. According to our simulations and experiments, the detection performance of this proposed architecture is 93.5%, and the proposed structure can reduce the hardware's complexity by up to 66.2% compared with the conventional structure.

In this letter, a new terrain type classifier is proposed for polarimetric Synthetic Aperture Radar (Pol-SAR) images. This classifier uses the binary tree structure. The homogenous and inhomogeneous areas are first classified by the support vector machine (SVM) classifier based on the texture features extracted from the span image. Then the homogenous and inhomogeneous areas are, respectively, classified by the traditional Wishart classifier and the SVM classifier based on the texture features. Using a NASA/JPL AIRSAR image, the authors achieve the classification accuracy of up to 98%, demonstrating the effectiveness of the proposed method.

Based on the reiterative maximum signal minus interference level (MSMIL) criterion and adaptive beamforming, a novel interference suppression algorithm is proposed for shared-spectrum multistatic radar that must contend with clutter. In this algorithm, two-dimensional adaptive beamformers are designed for azimuths and range cells. Numerical results show advantages of the proposed method.

This paper proposes an adaptive antenna using a combination of on-off and CMA algorithms. With the proposed technique, the on-off algorithm is first employed to search for a desired signal direction in which maximum received power is achieved. Then, interference is suppressed by performing CMA. Simulations are conducted according to the potential application of the proposed adaptive antenna. The simulation results show the SINR improvement implying that the proposed adaptive antenna can be applied to microwave RFID systems in order to resolve reader collision. Furthermore, the proposed adaptive antenna is implemented and then experimented. The experimental results verify that the proposed adaptive antenna can reduce interference resulting in the collision problem.

Dicode partial response signaling system over inductively-coupled channel has been developed to achieve higher data rate than self-resonant frequencies of inductors. The developed system operates at five times higher data rates than conventional systems with the same inductor. A current-mode equalization in the transmitter designed in a 90-nm CMOS successfully reshapes waveforms to obtain dicode signals at the receiver. For a 5-Gb/s signaling through the coupled inductors with a 120-µm diameter and a 120-µm distance, 20-mV eye opening was observed. The power consumption value of the transmitter was 58 mW at the 5-Gb/s operation.

We propose new adaptive tree search algorithms for multiple-input multiple-output (MIMO) systems based on path metric comparison. With the fixed number of survivor paths, the correct path metric may be temporarily larger than the maximum path metric of the survivor paths under an ill-conditioned channel. There have been also adaptive path metric algorithms that control the number of survivor paths according to SNR. However, these algorithms cannot instantaneously adapt to the channel condition. The proposed algorithms accomplish dynamic adaptation based on the ratio of two minimum path metrics as the minimum is significantly smaller than the second minimum under good channel conditions and vice versa. The proposed algorithms are much less complex than the conventional noise variance-based adaptive tree search algorithms while keeping lower or similar error performance. We first employ the proposed adaptive tree search idea to K-best detection and then extend it QRD-M MIMO detection.

Previous research illustrates that LRU replacement policy is not efficient when applications exhibit a distant re-reference interval. Recently RRIP policy is proposed to improve the performance for such kind of workloads. However, the lack of access recency information in RRIP confuses the replacement policy to make the accurate prediction. To enhance the robustness of RRIP for recency-friendly workloads, we propose an Dynamic Adaptive Insertion and Re-reference Prediction (DAI-RRP) policy which evicts data based on both re-reference prediction value and the access recency information. DAI-RRP makes adaptive adjustment on insertion position and prediction value for different access patterns, which makes the policy robust across different workloads and different phases. Simulation results show that DAI-RRP outperforms LRU and RRIP. For a single-core processor with a 1 MB 16-way set last-level cache (LLC), DAI-RRP reduces CPI over LRU and Dynamic RRIP by an average of 8.1% and 2.7% respectively. Evaluations on quad-core CMP with a 4 MB shared LLC show that DAI-RRP outperforms LRU and Dynamic RRIP (DRRIP) on the weighted speedup metric by an average of 8.1% and 15.7% respectively. Furthermore, compared to LRU, DAI-RRP consumes the similar hardware for 16-way cache, or even less hardware for high-associativity cache. In summary, the proposed policy is practical and can be easily integrated into existing hardware approximations of LRU.

This paper presents an adaptive magnification transformation based particle swarm optimizer (AMT-PSO) that provides an adaptive search strategy for each particle along the search process. Magnification transformation is a simple but very powerful mechanism, which is inspired by using a convex lens to see things much clearer. The essence of this transformation is to set a magnifier around an area we are interested in, so that we could inspect the area of interest more carefully and precisely. An evolutionary factor, which utilizes the information of population distribution in particle swarm, is used as an index to adaptively tune the magnification scale factor for each particle in each dimension. Furthermore, a perturbation-based elitist learning strategy is utilized to help the swarm's best particle to escape the local optimum and explore the potential better space. The AMT-PSO is evaluated on 15 unimodal and multimodal benchmark functions. The effects of the adaptive magnification transformation mechanism and the elitist learning strategy in AMT-PSO are studied. Results show that the adaptive magnification transformation mechanism provides the main contribution to the proposed AMT-PSO in terms of convergence speed and solution accuracy on four categories of benchmark test functions.

A class of balanced semi-bent functions with an even number of variables is proposed. It is shown that they include one subclass of semi-bent functions with maximum algebraic degrees. Furthermore, an example of semi-bent functions in a small field is given by using the zeros of some Kloosterman sums. Based on the result given by S.Kim et al., an example of infinite families of semi-bent functions is also obtained.

UWB (ultra wide-band) pulse radar is a promising candidate for surveillance systems. The fast SEABED (Shape Estimation Algorithm based on BST and Extraction of Directly scattered waves) imaging algorithm is deployed in the application of UWB pulse radar in fields that require real-time operations. However, since the SEABED algorithm uses signals received at multiple locations, this method either needs to scan antennas or to install many antennas. Such systems are inevitably costly and unrealistic for applications such as surveillance. To overcome this problem, a revised SEABED algorithm that estimates unknown target shape based on target motion using only a pair of fixed antennas was developed. However, the method cannot be used when the target moves arbitrarily because it assumes the target motion is parallel to the baseline of the pair of antennas. In this paper, we propose a new UWB radar imaging algorithm that is applicable even for targets with arbitrary motion. The proposed method introduces another antenna which is added to the pair of antennas used in the revised SEABED, and estimates unknown target motion based on the target surface using the three antennas. Next, the proposed method applies the SEABED imaging algorithm to the estimated motion and obtains the target image. Some numerical simulations establishes that the proposed method can accurately estimate the target shape even under severe conditions.

The letter deals with direction-of-arrival (DOA) estimation under nonuniform white noise and moderately small signal-to-noise ratios. The proposed approach first uses signal subspace projection for received data vectors, which form an efficient iterative quadratic maximum-likelihood (IQML) approach to achieve fast convergence and high resolution capabilities. In conjunction with a signal subspace selection technique, a more exact signal subspace can be obtained for reducing the nonuniform noise effect. The performance improvement achieved by applying the proposal to the classic IQML method is confirmed by computer simulations.

Metadata registry (MDR) is based on the international standard ISO/IEC 11179. The committee of ISO/IEC JTC 1/SC 32, which had standardized the MDR, has started to improvise the MDR, and the improvised version is named extended MDR (XMDR). However, the XMDR does not fully support the ontology concept, and no method is available for mapping ontology registrations onto registries. To overcome the limitations of the outdated XMDR, this paper proposes an extended XMDR (XMDR+) framework. The XMDR+ framework provides a method for mapping of ontology registrations between the metadata registry and ontologies. To improve the functions of the XMDR, we have proposed herein a framework that is capable of defining a model that manages the relations not only among ontological concepts but also among instances, and guarantees the management and storage of their relationships for supporting valid relations of the ontologies.

This letter deals with eigenspace-based (ESB) beamforming based on the decision-directed (DD) correction with robust capability. It has been shown that the output of the ESB beamformer includes the desired signal and noise under small pointing errors. In conjugation with DD and soft decision decoding scheme, the proposed approach can be used to form a robust DD-ESB beamformer without any specific training sequence. Computer simulations are provided to illustrate the effectiveness of the proposed beamformer.