In recent wireless communication systems, security is ensured mainly in the upper-layer techniques such as a password or a cryptography processing. However, security needs not be restricted to the upper-layer and the addition of physical-layer security also would yield a much more robust system. Therefore, in this paper, we exploit chaos communication and propose a chaos multiple-input multiple-output (MIMO) transmission scheme which achieves physical-layer security and additional channel-coding gain. A chaotic modulation symbol is multiplied to the data to be transmitted at each MIMO antenna to exploit the MIMO antenna diversity, and at the receiver, the joint MIMO detection and chaos decoding is done by maximum likelihood decoding (MLD). The conventional chaos modulation suffers from bit error rate (BER) performance degradation, while the coding gain is obtained in the proposed scheme by the chaos modulation in MIMO. We evaluate the performances of the proposed scheme by an analysis and computer simulations.

A new class of almost quadriphase sequences with four zero elements of period 4N, where N ≡ 1(mod 4) being a prime, is constructed. The maximum nontrivial autocorrelations of the constructed almost quadriphase sequences are shown to be 4.

In a wireless multi-hop network between a source node (S) and a destination node (D), multipath routing in which S redundantly sends the same packets to D through multiple routes at the same time is effective for enhancing the reliability of the wireless data transmission by means of route diversity. However, when applying the multipath routing to a factory where huge robots are moving around, if closer multiple routes are selected, the probability that they are blocked by the robots at the same time becomes higher, so the reliability in terms of packet loss rate cannot be enhanced. In this paper, we propose a multipath routing method which can select physically distant multiple routes without any knowledge on the locations of nodes. We introduce a single metric composed of “the distance between routes” and “the route quality” by means of scalarization in multi-objective maximization problem and apply a genetic algorithm (GA) for searching for adequate routes which maximize the metric. Computer simulation results show that the proposed method can adaptively control the topologies of selected routes between S and D, and effectively reduce the packet loss rates.

This letter proposes a novel connected dominanting set based decentralized cooperative spectrum sensing algorithm for cognitive radio networks. It is analytically shown that the proposed algorithm distributively converges to the average consensus as that of traditional distributed consensus algorithm, while reducing both the convergence time and message complexity significantly.

The 802.11n networks with MIMO technique provide a spatial degree of freedom for dealing with co-channel interference. In this letter, our proposed spatial interference coordination scheme is achieved by distributed precoding for the downlink and distributed multi-user detection for the uplink. Simulation results validate the proposed scheme in terms of the downlink and uplink maximum achievable rates at each AP.

This letter is concerned with cellular controlled short-range communication (CCSRC) systems, which can provide a significant performance gain over the traditional cellular systems as shown in the literature. However, to obtain such a gain, CCSRC systems need perfect channel state information (CSI) of all users and the complexity of setting up the optimal cooperative clusters is factorial with respect to the number of potentially cooperative users, which is very unrealistic in practical systems. To solve this problem, we propose a novel cooperative strategy, where CCSRC systems only need the distances between all user pairs and the complexity of setting up the cooperative clusters is relatively low. Simulation results show that the performance of the proposed strategy is close to optimal.

Hybrid wired/wireless on-chip network is a promising communication architecture for multi-/many-core SoC. For application-specific SoC design, it is important to design a dedicated on-chip network architecture according to the application-specific nature. In this paper, we propose a heuristic wireless link allocation algorithm for creating hybrid on-chip network architecture. The algorithm can eliminate the performance bottleneck by replacing multi-hop wired paths by high-bandwidth single-hop long-range wireless links. The simulation results show that the hybrid on-chip network designed by our algorithm improves the performance in terms of both communication delay and energy consumption significantly.

This paper presents analysis and design of a new ultra-low voltage analog front end (AFE) dedicated to strain sensor applications. The AFE, designed in 0.18 µm CMOS process, features a chopper-stabilized instrumentation amplifier (IA), a balanced active MOSFET-C 2nd order low pass filter (LPF), a clock generator and a voltage booster which operate at supply voltage (Vdd) of 0.6 V. The designed IA achieves 30 dB of closed-loop gain, 101 dB of common-mode rejection ratio (CMRR) at 50 Hz, 80 dB of power-supply rejection ratio (PSRR) at 50 Hz, thermal noise floor of 53.4 nV/, current consumption of 14 µA, and noise efficiency factor (NEF) of 9.7. The high CMRR and rail-to-rail output swing capability is attributed to a new low voltage realization of the active-bootstrapped technique using a pseudo-differential gain-boosting operational transconductance amplifier (OTA) and proposed current-driven bulk (CDB) biasing technique. An output capacitor-less low-dropout regulator (LDO), with a new fast start-up LPF technique, is used to regulate this 0.6 V supply from a 0.8–1.0 V energy harvesting power source. It achieves power supply rejection (PSR) of 42 dB at frequency of 1 MHz. A cascode compensated pseudo differential amplifier is used as the filter's building block for low power design. The filter's single-ended-to-balanced converter is implemented using a new low voltage amplifier with two-stage common-mode cancellation. The overall AFE was simulated to have 65.6 dB of signal-to-noise ratio (SNR), total harmonic distortion (THD) of less than 0.9% for a 100 Hz sinusoidal maximum input signal, bandwidth of 2 kHz, and power consumption of 51.2 µW. Spectre RF simulations were performed to validate the design using BSIM3V3 transistor models provided by GLOBALFOUNDRIES 0.18 µm CMOS process.

Fidelity Range Extension (FRExt) (i.e. High Profile) was added to the H.264/AVC recommendation in the second version. One of the features included in FRExt is the Adaptive Block-size Transform (ABT). In order to conform to the FRExt, a Fractional Motion Estimation (FME) architecture is proposed to support the 88/44 adaptive Hadamard Transform (88/44 AHT). The 88/44 AHT circuit contributes to higher throughput and encoding performance. In order to increase the utilization of SATD (Sum of Absolute Transformed Difference) Generator (SG) in unit time, the proposed architecture employs two 8-pel interpolators (IP) to time-share one SG. These two IPs can work in turn to provide the available data continuously to the SG, which increases the data throughput and significantly reduces the cycles that are needed to process one Macroblock. Furthermore, this architecture also exploits the linear feature of Hadamard Transform to generate the quarter-pel SATD. This method could help to shorten the long datapath in the second-step of two-iteration FME algorithm. Finally, experimental results show that this architecture could be used in the applications requiring different performances by adjusting the supported modes and operation frequency. It can support the real-time encoding of the seven-mode 4 K2 K@24 fps or six-mode 4 K2 K@30 fps video sequences.

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.

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.

For large-scale sensor networks, multiple sinks are often deployed in order to reduce source-to-sink distance and thus cost of data delivery. However, having multiple sinks may work against cost reduction, because routes from sources can diverge towards different sinks which reduces the benefit of in-network data aggregation. In this letter we propose a self-clustering data aggregation protocol (SCAP) that can benefit from having multiple sinks as well as joint routes. In SCAP, nodes which detect the event communicate with each other to aggregate data between themselves, before sending the data to the sinks. The self-clustering extends network lifetime by reducing energy consumption of nodes near the sinks, because the number of paths in which the packets are delivered is reduced. A performance comparison with existing protocols L-PEDAP and LEO shows that SCAP can conserve energy and extend network lifetime significantly, in a multi-sink environment.

We describe a multi-step approach for automatic segmentation of the femoral head and the acetabulum in the hip joint from three dimensional (3D) CT images. Our segmentation method consists of the following steps: 1) construction of the valley-emphasized image by subtracting valleys from the original images; 2) initial segmentation of the bone regions by using conventional techniques including the initial threshold and binary morphological operations from the valley-emphasized image; 3) further segmentation of the bone regions by using the iterative adaptive classification with the initial segmentation result; 4) detection of the rough bone boundaries based on the segmented bone regions; 5) 3D reconstruction of the bone surface using the rough bone boundaries obtained in step 4) by a network of triangles; 6) correction of all vertices of the 3D bone surface based on the normal direction of vertices; 7) adjustment of the bone surface based on the corrected vertices. We evaluated our approach on 35 CT patient data sets. Our experimental results show that our segmentation algorithm is more accurate and robust against noise than other conventional approaches for automatic segmentation of the femoral head and the acetabulum. Average root-mean-square (RMS) distance from manual reference segmentations created by experienced users was approximately 0.68 mm (in-plane resolution of the CT data).

This paper describes a method for estimating Direction Of Arrival (DOA) of multiple sound sources in full azimuth with three microphones. Estimating DOA with paired microphone arrays creates imaginary sound sources because of time delay of arrival (TDOA) being identical between real and imaginary sources. Imaginary sound sources can create chronic problems in multiple Sound Source Localization (SSL), because they can be localized as real sound sources. Our proposed approach is based on the observation that each microphone array creates imaginary sound sources, but the DOA of imaginary sources may be different depending on the orientation of the paired microphone array. With the fact that a real source would always be localized in the same direction regardless of the array orientation, we can suppress the imaginary sound sources by minimum filtering based on Steered Response Power – Phase Transform (SRP-PHAT) method. A set of experiments conducted in a real noisy environment showed that the proposed method was accurate in localizing multiple sound sources.

Feature selection (FS) plays an important role in pattern recognition and machine learning. FS is applied to dimensionality reduction and its purpose is to select a subset of the original features of a data set which is rich in the most useful information. Most existing FS methods based on rough set theory focus on dependency function, which is based on lower approximation as for evaluating the goodness of a feature subset. However, by determining only information from a positive region but neglecting a boundary region, most relevant information could be invisible. This paper, the maximal lower approximation (Max-Certainty) – minimal boundary region (Min-Uncertainty) criterion, focuses on feature selection methods based on rough set and mutual information which use different values among the lower approximation information and the information contained in the boundary region. The use of this idea can result in higher predictive accuracy than those obtained using the measure based on the positive region (certainty region) alone. This demonstrates that much valuable information can be extracted by using this idea. Experimental results are illustrated for discrete, continuous, and microarray data and compared with other FS methods in terms of subset size and classification accuracy.

In this letter, a novel resource allocation method is proposed for Discrete Fourier Transform Spread Orthogonal Frequency Division Multiple Access (DFT-s-OFDMA) systems in Long Term Evolution (LTE). The proposed method is developed based on a minimal metric loss criterion and performs better than the commonly used Recursive Maximum Expansion (RME) method.

We propose a novel substrate-bias control scheme for an FD-SOI SRAM that suppresses inter-die variability. The proposed circuits detect inter-die threshold-voltage variation automatically, and then maximize read/write margins of memory cells to supply the substrate bias. We confirmed that a 486-kb 6T SRAM operates at 0.42 V, in which an FS corner can be compared as much as 0.14 V or more.

Traditional authentication protocols are based on cryptographic techniques to achieve identity verification. Distance bounding protocols are an enhanced type of authentication protocol built upon both signal traversal time measurement and cryptographic techniques to accomplish distance verification as well as identity verification. A distance bounding protocol is usually designed to defend against the relay attack and the distance fraud attack. As there are applications to which the distance fraud attack is not a serious threat, we propose a streamlined distance bounding protocol that focuses on the relay attack. The proposed protocol is more efficient than previous protocols and has a low false acceptance rate under the relay attack.

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.

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.