In compressed sensing, the design of the measurement matrix is a key work. In order to achieve a more precise reconstruction result, the columns of the measurement matrix should have better orthogonality or linear incoherence. A random matrix, like a Gaussian random matrix (GRM), is commonly adopted as the measurement matrix currently. However, the columns of the random matrix are only statistically-orthogonal. By substituting an orthogonal basis into the random matrix to construct a semi-random measurement matrix and by optimizing the mutual coherence between dictionary columns to approach a theoretical lower bound, the linear incoherence of the measurement matrix can be greatly improved. With this optimization measurement matrix, the signal can be reconstructed from its measures more precisely.

The key escrow problem and high computational cost are the two major problems that hinder the wider adoption of hierarchical identity-based signature (HIBS) scheme. HIBS schemes with either escrow-free (EF) or online/offline (OO) model have been proved secure in our previous work. However, there is no much EF or OO scheme that has been evaluated experimentally. In this letter, several EF/OO HIBS schemes are considered. We study the algorithmic complexity of the schemes both theoretically and experimentally. Scheme performance and practicability of EF and OO models are discussed.

This paper focuses on developing a square root (SQRT) algorithm in finite fields GF(p2d) (d 0). Examining the Smart algorithm, a well-known SQRT algorithm, we can see that there is some computation overlap between the Smart algorithm and the quadratic residue (QR) test, which must be implemented before a SQRT computation. It makes the Smart algorithm inefficient. In this paper, we propose a new QR test and a new SQRT algorithm in GF(p2d), in which not only there is no computation overlap, but also most of computations required for the proposed SQRT algorithm in GF(p2d) can be implemented in the corresponding subfields GF(p2d-i) for 1 i d, which yields many reductions in the computational time and complexity. The computer simulation also shows that the proposed SQRT algorithm is much faster than the Smart algorithm.

A tri-band Multiple-input-multiple-output (MIMO) antenna system for LTE 700, LTE2500 and GSM 1800/1900 mobile handset application is presented. The whole system consists of four identical 3-D IFAs (inverted F antenna) folded on FR4 cuboids. Without any special designed decoupling structures, the measured isolation among antenna elements is higher than 20dB in the low and upper bands, even in the middle band, the isolation is higher than 13.7dB. Reflection coefficient, correlation coefficient, gain and radiation pattern are also presented. Acceptable agreement between the antenna models with and without plastic housing, battery and LCD screen demonstrate that the proposed antenna is a competitive candidate for mobile handsets.

Multipath routing has been extended to Border Gateway Protocol (BGP), the current de facto inter-domain routing protocol, to address the reliability and performance issues of the current Internet. However, inter-domain multipath routing introduces a significant challenge for scalability due to the large scale of the inter-domain routing system. At the same time it also introduces new challenges in terms of security and security related overhead. In this paper, we propose a regional multipath approach, Regional Multipath Inter-domain Routing (RMI), where multiple paths are only allowed to be propagated within a well-defined range. With multipath routing in a region, we enable inter-domain routing with rich path diversity and improved security, and no longer have to sacrifice scalability. We show how to propagate multiple paths based on the region by theoretical analysis and by extensive simulations. Our simulations show that the number of messages generated using this approach and the convergence delay are much less than those of BGP and BGP with full multipath advertisement.

Network servers and applications commonly use static IP addresses and communication ports, making themselves easy targets for network reconnaissances and attacks. Moving target defense (MTD) is an innovatory and promising proactive defense technique. In this paper, we develop a novel MTD mechanism, called Random Port and Address Hopping (RPAH). The goal of RPAH is to hide network servers and applications and resist network reconnaissances and attacks by constantly changing their IP addresses and ports. In order to enhance the unpredictability, RPAH integrates source identity, service identity and temporal parameter in the hopping to provide three hopping frequencies, i.e., source hopping, service hopping and temporal hopping. RPAH provides high unpredictability and the maximum hopping diversities by introducing port and address demultiplexing mechanism, and provides a convenient attack detection mechanism with which the messages from attackers using invalid or inactive addresses/ports will be conveniently detected and denied. Our experiments and evaluation on campus network and PlanetLab show that RPAH is effective in resisting various network reconnaissance and attack models such as network scanning and worm propagation, while introducing an acceptable operation overhead.

This paper simulates the dynamic behavior of the operating mechanism of ACB, and analyzes factors influencing the mechanism's operating time. First, it builds a dynamic model for the mechanism with virtual prototype technology. Experiment validation is carried out to prove the correctness of the model. Based on this model, it puts emphasis on analyzing the influence of electro-dynamic repulsion force on the operating time of the mechanism. Simulation and experimental results show that after adding electric repulsion force to the model, the operating time is shortened about 1.1 ms. Besides the repulsion force, other influencing factors including the stiffness of opening spring, locations of every key axis, mass and centroidal coordinates of every mechanical part are analyzed as well. Finally, it makes an optimum design for the mechanism. After optimization, the velocity of operating mechanism is improved about 6.7%.

In this paper, we consider the optimization of measurement matrix in Compressed Sensing (CS) framework. Based on the boundary constraint, we propose a novel algorithm to make the “mutual coherence” approach a lower bound. This algorithm is implemented by using an iterative strategy. In each iteration, a neighborhood interval of the maximal off-diagonal entry in the Gram matrix is scaled down with the same shrinkage factor, and then a lower mutual coherence between the measurement matrix and sparsifying matrix is obtained. After many iterations, the magnitudes of most of off-diagonal entries approach the lower bound. The proposed optimization algorithm demonstrates better performance compared with other typical optimization methods, such as t-averaged mutual coherence. In addition, the effectiveness of CS can be used for the compression of complex synthetic aperture radar (SAR) image is verified, and experimental results using simulated data and real field data corroborate this claim.

In this letter, we first investigate some new properties of a known power residue frequency-hopping sequence (FHS) set which is established as an optimal one-coincidence frequency-hopping sequence (OC-FHS) set with near-optimal set size. Next, combining the mathematical structure of power residue theory with interleaving technique, we present a new class of optimal OC-FHS set, using the Chinese Remainder Theorem (CRT). As a result, one optimal OC-FHS set with prime length is extended to another optimal OC-FHS set with composite length in which the construction preserves the maximum Hamming correlation (MHC) and the set size as well as the optimality of the Lempel-Greenberger bound.

In this paper, a new scheme is presented for ground moving target indication for multichannel high-resolution wide-swath (HRWS) SAR systems with modified reconstruction filters. The conventional steering vector is generalized for moving targets through taking into account the additional Doppler centroid shift caused by the across-track velocity. Two modified steering vectors with symmetric velocity information are utilized to produce two images for the same scene. Due to the unmatched steering vectors, the stationary backgrounds are defocused but they still hold the same intensities in both images but moving targets are blurred to different extents. The ambiguous components of the moving targets can also be suppressed due to the beamforming in the reconstruction procedure. Therefore, ground moving target indication can be carried out via intensity comparison between the two images. The effectiveness of the proposed method is verified by both simulated and real airborne SAR data.

As a concept stemmed from social field, we argued that, in P2P networks, peers' recommendation behaviors and functional behaviors should be explicitly separated, thus we propose the HopRec scheme which uses hop-based recommendation ability to improve the accuracy of reputation ranking in P2P networks. Our contributions lie in the following aspects: firstly, we adopt the simple but effective idea to infer peer's recommendation ability (RA): the farer away that peer is from the initial malicious seeds, the higher RA that peer should have; Then, the computation of reputation rankings appropriately reflects peer's different RA. The simulation results show that, in comparison with Eigentrust-like algorithms, HopRec can be robust to sybils and front peers attacks, and achieve significant performance improvement. Moreover, we compare HopRec with two related schemes, Poisonedwater and CredibleRank, and found that: in hospitable P2P environment, HopRec can obtain better performance than Poisonedwater, and can achieve the comparable performance as CredibleRank, with less computation overhead then CredibleRank. Finally, we also show that, if the initial good and malicious seeds could be selected based on peers' degrees, then HopRec and CredibleRank can achieve perfect performance.

Recently, Kang et al. discussed some security flaws of Wu et al.'s and Wei et al.'s authentication schemes that guarantee user anonymity in wireless communications and showed how to overcome the problems regarding anonymity and the forged login messages. However, we will show that Kang et al.'s improved scheme still did not provide user anonymity as they claimed.

This paper provides a prototype neural prosthesis system dedicated to restoring continence and micturition function for patients with lower urinary tract diseases, such as detrusor hyperreflexia and detrusor-sphincter dyssynergia. This system consists of an ultra low-noise electroneurogram (ENG) signal recording module, a bi-phasic electrical stimulator module and a control unit for closed-loop bladder monitoring and controlling. In order to record extremely weak ENG signal from extradural sacral nerve roots, the system provides a programmable gain from 80 dB to 117 dB. By combining of advantages of commercial-off-the-shelf (COTS) electronics and custom designed IC, the recording front-end acquires a fairly low input-referred noise (IRN) of 0.69 μVrms under 300 Hz to 3 kHz and high area-efficiency. An on-chip multi-steps single slope analog-to-digital converter (ADC) is used to digitize the ENG signals at sampling rate of 10 kSPS and achieves an effective number of bits (ENOB) of 12.5. A bi-phasic current stimulus generator with wide voltage supply range (±0.9 V to ±12.5 V) and variable output current amplitude (0-500 μA) is introduced to overcome patient-depended impedance between electrode and tissue electrolyte. The total power consumption of the entire system is 5.61 mW. Recording and stimulation function of this system is switched by control unit with time division multiplexing strategy. The functionality of this proposed prototype system has been successfully verified through in-vivo experiments from dogs extradural sacral nerve roots.

The rapid advancement of cloud-edge-end collaboration offers a feasible solution to realize low-delay and low-energy-consumption data processing for internet of things (IoT)-based smart distribution grid. The major concern of cloud-edge-end collaboration lies on resource management. However, the joint optimization of heterogeneous resources involves multiple timescales, and the optimization decisions of different timescales are intertwined. In addition, burst electromagnetic interference will affect the channel environment of the distribution grid, leading to inaccuracies in optimization decisions, which can result in negative influences such as slow convergence and strong fluctuations. Hence, we propose a cloud-edge-end collaborative multi-timescale multi-service resource management algorithm. Large-timescale device scheduling is optimized by sliding window pricing matching, which enables accurate matching estimation and effective conflict elimination. Small-timescale compression level selection and power control are jointly optimized by disturbance-robust upper confidence bound (UCB), which perceives the presence of electromagnetic interference and adjusts exploration tendency for convergence improvement. Simulation outcomes illustrate the excellent performance of the proposed algorithm.

In this letter, an improved statistical simulation model with a new parameter computation method is proposed for Rayleigh fading channels. Compared with the existing simulators, the proposed model yields much higher simulation efficiency, while it can still obtain adequate approximations of the desired statistical properties.