This paper describes the design and measurements of two-gain-mode MMIC power amplifier modules (PAMs) for Band 1 and Band 5 WCDMA data communications. The PAMs are based on the two-stage single-chain amplifier topology with an L-shaped FET step attenuator (ATT) placed at the interstage, featuring not only high-efficiency operation but also both a small phase discontinuity and a small input return loss variation between the two gain modes: a high-gain mode (0-dB thru state for the ATT) and a low-gain mode (14-dB attenuation state for the ATT). The PAMs are assembled on a 3 mm × 3 mm FR-4 laminate together with several surface mount devices, and a high-directivity, 20-dB bilayer-type directional coupler is integrated on the laminate for accurate forward-power monitoring even under a 2.5:1-VSWR load mismatching condition. To validate the design and analysis for the PAMs using the L-shaped ATT, two PAM products — a Band 1 PAM and a Band 5 PAM — were fabricated using our in-house GaAs-BiFET process. The main RF measurements under the condition of a WCDMA (R99) modulated signal and a 3.4-V supply voltage are as follows. The Band 1 PAM can deliver a power-added efficiency (PAE) as high as 46% at an output power (Pout) of 28.25 dBm while maintaining a ±5-MHz-offset adjacent channel power ratio (ACLR1) of approximately -40 dBc or less and a small phase discontinuity of less than 5°. The Band 5 PAM can also deliver a high PAE of 46% at the same Pout and ACLR1 levels with small phase discontinuity of less than 4°. This small discontinuity is due to the phase-shift compensation capacitance embedded in the ATT. The measured input return loss is well maintained at better than 10 dB at the two modes. In addition, careful coupler design achieves a small detection error of less than 0.5 dB even under a 2.5:1-VSWR load mismatching condition.

We present the concept of key-rotatable and security-updatable homomorphic encryption (KR-SU-HE) scheme, which is defined as a class of public-key homomorphic encryption in which the keys and the security of any ciphertext can be rotated and updated while still keeping the underlying plaintext intact and unrevealed. After formalising the syntax and security notions for KR-SU-HE schemes, we build a concrete scheme based on the Learning With Errors assumption. We then perform several careful implementations and optimizations to show that our proposed scheme is efficiently practical.

This paper addresses recommendation diversification. Existing diversification methods have difficulty in dealing with the tradeoff between accuracy and diversity. We point out the root of the problem in diversification methods and propose a novel method that can avoid the problem. Our method aims to find an optimal solution of the objective function that is carefully designed to consider user preference and the diversity among recommended items simultaneously. In addition, we propose an item clustering and a greedy approximation to achieve efficiency in recommendation.

A robust pedestrian detection approach in thermal infrared imageries for an all-day surveillance is proposed. Firstly, the candidate regions which are likely to contain pedestrians are extracted based on a saliency detection method. Then a deep convolutional network with a multi-task loss is constructed to recognize the pedestrians. The experimental results show the superiority of the proposed approach in pedestrian detection.

Based on the known binary and quaternary zero correlation zone (ZCZ) sequence sets, a class of 16-QAM sequence sets with ZCZ is presented, where the term “QAM sequence” means the sequence over the quadrature amplitude modulation (QAM) constellation. The sequence sets obtained by this method achieve an expansion in the number of 16-QAM sequence sets with ZCZ. The proposed sequence sets can be applied to quasi-synchronous code division multiple access (QS-CDMA) systems to eliminate the multiple access interference (MAI) and multipath interference (MPI) and improve the transmission data rate (TDR).

Deterministic ID-based signatures are digital signatures where secret keys are probabilistically generated by a key generation center while the signatures are generated deterministically. Although the deterministic ID-based signatures are useful for both systematic and cryptographic applications, to the best of our knowledge, there is no scheme with a tight reduction proof. Loosely speaking, since the security is downgraded through dependence on the number of queries by an adversary, a tighter reduction for the security of a scheme is desirable, and this reduction must be as close to the difficulty of its underlying hard problem as possible. In this work, we discuss mathematical features for a tight reduction of deterministic ID-based signatures, and show that the scheme by Selvi et al. (IWSEC 2011) is tightly secure by our new proof framework under a selective security model where a target identity is designated in advance. Our proof technique is versatile, and hence a reduction cost becomes tighter than the original proof even under an adaptive security model. We furthermore improve the scheme by Herranz (The Comp. Jour., 2006) to prove tight security in the same manner as described above. We furthermore construct an aggregate signature scheme with partial aggregation, which is a key application of deterministic ID-based signatures, from the improved scheme.

Tunstall code is known as an optimal variable-to-fixed length (VF) lossless source code under the criterion of average coding rate, which is defined as the codeword length divided by the average phrase length. In this paper we define the average coding rate of a VF code as the expectation of the pointwise coding rate defined by the codeword length divided by the phrase length. We call this type of average coding rate the average pointwise coding rate. In this paper, a new VF code is proposed. An incremental parsing tree construction algorithm like the one that builds Tunstall parsing tree is presented. It is proved that this code is optimal under the criterion of the average pointwise coding rate, and that the average pointwise coding rate of this code converges asymptotically to the entropy of the stationary memoryless source emitting the data to be encoded. Moreover, it is proved that the proposed code attains better worst-case coding rate than Tunstall code.

Wireless video sensor networks address problems, such as low power consumption of sensor nodes, low computing capacity of nodes, and unstable channel bandwidth. To transmit video of distributed video coding in wireless video sensor networks, we propose an efficient scalable distributed video coding scheme. In this scheme, the scalable Wyner-Ziv frame is based on transmission of different wavelet information, while the Key frame is based on transmission of different residual information. A successive refinement of side information for the Wyner-Ziv and Key frames are proposed in this scheme. Test results show that both the Wyner-Ziv and Key frames have four layers in quality and bit-rate scalable, but no increase in complexity of the encoder.

This paper proposes a novel secure biometric authentication scheme. The scheme deals with fingerprint minutiae as the biometric feature and the matching is checked by a widely used technique. To discuss security, we formalize the model of secure biometric authentication scheme by abstracting the related and proposed schemes. The schemes which satisfy all the proposed security requirements are guaranteed to prevent leakage of biometric information and impersonation. In particular, the definition captures well-known and practical attacks including replay attacks and hill-climbing attacks. We prove that the proposed scheme achieves all the requirements if the additive homomorphic encryption scheme used in the scheme satisfies some additional properties. As far as we know, the proposed scheme is the first one that satisfies all the requirements. Also, we show that modified Elgamal cryptosystem satisfies all the properties under the decisional Diffie-Hellman assumption.

We study an authentication method using secret figures of Pattern Lock, called pass patterns. In recent years, it is important to prevent the leakage of personal and company information on mobile devices. Android devices adopt a login authentication called Pattern Lock, which achieves both high resistance to Brute Force Attack and usability by virtue of pass pattern. However, Pattern Lock has a problem that pass patterns directly input to the terminal can be easily remembered by shoulder-surfing attack. In this paper, we propose a shoulder-surfing resistant authentication using pass pattern of Pattern Lock, which adopts a challenge & response authentication and also uses users' short-term memory. We implement the proposed method as an Android application and measure success rate, authentication time and the resistance against shoulder surfing. We also evaluate security and usability in comparison with related work.

In this paper, we theoretically analyse the influence of intersymbol interference (ISI) and continuous wave interference (CWI) on the bit error rate (BER) performance of the spread spectrum (SS) system using a real-valued Huffman sequence under the additive white Gaussian noise (AWGN) environment. The aperiodic correlation function of the Huffman sequence has zero sidelobes except the shift-end values at the left and right ends of shift. The system can give the unified communication and ranging system because the output of a matched filter (MF) is the ideal impulse by generating transmitted signal of the bit duration T=NTc, N=2n, n=1,2,… from the sequence of length M=2kN+1, k=0,1,…, where Tc is the chip duration and N is the spreading factor. As a result, the BER performance of the system is improved with decrease in the absolute value of the shift-end value, and is not influenced by ISI if the shift-end value is almost zero-value. In addition, the BER performance of the system of the bit duration T=NTc with CWI is improved with increase in the sequence length M=2kN+1, and the system can decrease the influence of CWI.

This paper presents a new GPU-based rasterization algorithm for Boolean operations that handles arbitary closed polygons. We construct an efficient data structure for interoperation of CPU and GPU and propose a fast GPU-based contour extraction method to ensure the performance of our algorithm. We then design a novel traversing strategy to achieve an error-free calculation of intersection point for correct Boolean operations. We finally give a detail evaluation and the results show that our algorithm has a higher performance than exsiting algorithms on processing polygons with large amount of vertices.

Regular expression matching is essential in network and big-data applications; however, it still has a serious performance bottleneck. The state-of-the-art schemes use a multi-pattern exact string-matching algorithm as a filtering module placed before a heavy regular expression engine. We design a new approximate string-matching filter using multiple q-grams; this filter not only achieves better space compactness, but it also has higher throughput than the existing filters.

The radio wave shadowing by a two-dimensional human body is examined numerically as the scattering problem by using the Method of Moments (MoM) in order to verify the equivalent human body diameter. Three human body models are examined: (1) a circular cylinder, (2) an elliptical cylinder, and (3) an elliptical cylinder with two circular cylinders are examined. The scattered fields yields by the circular cylinder are compared with measured data. Since the angle of the model to an incident wave affects scattered fields in models other than a circular cylinder, the models of an elliptical cylinder and an elliptical cylinder with two circular cylinders are converted into a circular cylinder of equivalent diameter. The frequency characteristics for the models are calculated by using the equivalent diameter.

This paper deals with the scattering of a cylindrical wave by a perfectly conductive periodic surface. This problem is equivalent to finding the Green's function G(x,z|xs,zs), where (x,z) and (xs,zs) are the observation and radiation source positions above the periodic surface, respectively. It is widely known that the Green's function satisfies the reciprocity: G(x,z|xs,zs)=G(xs,zs|x,z), where G(xs,zs|x,z) is named the reversal Green's function in this paper. So far, there is no numerical method to synthesize the Green's function with the reciprocal property in the grating theory. By combining the shadow theory, the reciprocity theorem for scattering factors and the average filter introduced previously, this paper gives a new numerical method to synthesize the Green's function with reciprocal property. The reciprocity means that any properties of the Green's function can be obtained from the reversal Green's function. Taking this fact, this paper obtains several new formulae on the radiation and scattering from the reversal Green's function, such as a spectral representation of the Green's function, an asymptotic expression of the Green's function in the far region, the angular distribution of radiation power, the total power of radiation and the relative error of power balance. These formulae are simple and easy to use. Numerical examples are given for a very rough periodic surface. Several properties of the radiation and scattering are calculated for a transverse magnetic (TM) case and illustrated in figures.

ZHFE, proposed by Porras et al. at PQCrypto'14, is one of the very few existing multivariate encryption schemes and a very promising candidate for post-quantum cryptosystems. The only one drawback is its slow key generation. At PQCrypto'16, Baena et al. proposed an algorithm to construct the private ZHFE keys, which is much faster than the original algorithm, but still inefficient for practical parameters. Recently, Zhang and Tan proposed another private key generation algorithm, which is very fast but not necessarily able to generate all the private ZHFE keys. In this paper we propose a new efficient algorithm for the private key generation and estimate the number of possible keys generated by all existing private key generation algorithms for the ZHFE scheme. Our algorithm generates as many private ZHFE keys as the original and Baena et al.'s ones and reduces the complexity from O(n2ω+1) by Baena et al. to O(nω+3), where n is the number of variables and ω is a linear algebra constant. Moreover, we also analyze when the decryption of the ZHFE scheme does not work.

The stream cipher Sprout with a short internal state was proposed in FSE 2015. Although the construction guaranteed resistance to generic Time Memory Data Tradeoff attacks, there were some weaknesses in the design and the cipher was completely broken. In this paper we propose a family of stream ciphers LILLE in which the size of the internal state is half the size of the secret key. Our main goal is to develop robust lightweight stream cipher. To achieve it, our cipher based on the two-key Even Mansour construction and thus its security against key/state recovery attacks reduces to a well analyzed problem. We also prove that like Sprout, the construction is resistant to generic Time Memory Data Tradeoff attacks. Unlike Sprout, the construction of the cipher guarantees that there are no weak key-IV pairs which produce a keystream sequence with short period or which make the algebraic structure of the cipher weaker and easy to cryptanalyze. The reference implementations of all members of the LILLE family with standard cell libraries based on the STM 90nm and 65nm processes were also found to be smaller than Grain v1 while security of LILLE family depend on reliable problem in the symmetric cryptography.

In this paper, we propose a low-complexity widely-linear minimum mean square error (WL-MMSE) signal detection based on the Chebyshev polynomials accelerated symmetric successive over relaxation (SSORcheb) algorithm for uplink (UL) over-loaded large-scale multiple-input multiple-output (MIMO) systems. The technique of utilizing Chebyshev acceleration not only speeds up the convergence rate significantly, and maximizes the data throughput, but also reduces the cost. By utilizing the random matrix theory, we present good estimates for the Chebyshev acceleration parameters of the proposed signal detection in real large-scale MIMO systems. Simulation results demonstrate that the new WL-SSORcheb-MMSE detection not only outperforms the recently proposed linear iterative detection, and the optimal polynomial expansion (PE) WL-MMSE detection, but also achieves a performance close to the exact WL-MMSE detection. Additionally, the proposed detection offers superior sum rate and bit error rate (BER) performance compared to the precision MMSE detection with substantially fewer arithmetic operations in a short coherence time. Therefore, the proposed detection can satisfy the high-density and high-mobility requirements of some of the emerging wireless networks, such as, the high-mobility Internet of Things (IoT) networks.

With an annual growth of billions of sensor-based devices, it is an urgent need to do stream mining for the massive data streams produced by these devices. Cloud computing is a competitive choice for this, with powerful computational capabilities. However, it sacrifices real-time feature and energy efficiency. Application-specific integrated circuit (ASIC) is with high performance and efficiency, which is not cost-effective for diverse applications. The general-purpose microcontroller is of low performance. Therefore, it is a challenge to do stream mining on these low-cost devices with scalability and efficiency. In this paper, we introduce an FPGA-based scalable and parameterized architecture for stream mining.Particularly, Dynamic Time Warping (DTW) based k-Nearest Neighbor (kNN) is adopted in the architecture. Two processing element (PE) rings for DTW and kNN are designed to achieve parameterization and scalability with high performance. We implement the proposed architecture on an FPGA and perform a comprehensive performance evaluation. The experimental results indicate thatcompared to the multi-core CPU-based implementation, our approach demonstrates over one order of magnitude on speedup and three orders of magnitude on energy-efficiency.

In this paper, we propose a received signal interpolation method for enhancing the performance of multiple signal classification (MUSIC) algorithm. In general, the performance of the conventional MUSIC algorithm is very sensitive to signal-to-noise ratio (SNR) of the received signal. When array elements receive the signals with nonuniform SNR values, the resolution performance is degraded compared to elements receiving the signals with uniform SNR values. Hence, we propose a signal calibration technique for improving the resolution of the algorithm. First, based on original signals, rough direction of arrival (DOA) estimation is conducted. In this stage, using frequency-domain received signals, SNR values of each antenna element in the array are estimated. Then, a deteriorated element that has a relatively lower SNR value than those of the other elements is selected by our proposed scheme. Next, the received signal of the selected element is spatially interpolated based on the signals received from the neighboring elements and the DOA information extracted from the rough estimation. Finally, fine DOA estimation is performed again with the calibrated signal. Simulation results show that the angular resolution of the proposed method is better than that of the conventional MUSIC algorithm. Also, we apply the proposed scheme to actual data measured in the testing ground, and it gives us more enhanced DOA estimation result.