To ensure secure mobile communication, the communicating entities must know their mutual identities. The entities which need to be identified in a mobile communication system are mobile devices and the network. Third Generation Partnership Project (3GPP) has specified Evolved Packet System Authentication and Key Agreement (EPS AKA) procedure for the mutual authentication of user and the Long Term Evolution (LTE) network. EPS AKA certainly overcomes most of the vulnerabilities in the Global System for Mobile Communications (GSM) and Universal Mobile Telecommunication System (UMTS) access procedures. However, the LTE access procedure still has security weaknesses against some of the sophisticated security threats, such as, Denial-of-Service (DoS) attacks, Man-in-the-Middle (MitM) attacks, rogue base station attacks and fails to ensure privacy protection for some of the important parameters. This paper proposes an improved security framework for the LTE access procedure by ensuring the confidentiality protection of International Mobile Subscriber Identity (IMSI) and random-challenge RAND. Also, our proposed system is designed to reduce the impact of DoS attacks which try to overwhelm the network with useless computations. We use a one-time shared key with a short lifetime between the UE and MME to protect IMSI and RAND privacy. Finally, we explore the parameters design for the proposed system which leads to satisfy the requirements imposed on computational load and latency as well as security strength.

Transfer boosting, a branch of instance-based transfer learning, is a commonly adopted transfer learning method. However, currently popular transfer boosting methods focus on binary classification problems even though there are many multi-classification tasks in practice. In this paper, we developed a new algorithm called MultiTransferBoost on the basis of TransferBoost for multi-classification. MultiTransferBoost firstly separated the multi-classification problem into several orthogonal binary classification problems. During each iteration, MultiTransferBoost boosted weighted instances from different source domains while each instance's weight was assigned and updated by evaluating the difficulty of the instance being correctly classified and the “transferability” of the instance's corresponding source domain to the target. The updating process repeated until it reached the predefined training error or iteration number. The weight update factors, which were analyzed and adjusted to minimize the Hamming loss of the output coding, strengthened the connections among the sub binary problems during each iteration. Experimental results demonstrated that MultiTransferBoost had better classification performance and less computational burden than existing instance-based algorithms using the One-Against-One (OAO) strategy.

Long-distance wireless local area networks (WLANs) are the key enablers of wide-area and low-cost access networks in rural areas. In a WLAN, the long propagation delay between an access point (AP) and stations (STAs) significantly degrades the throughput and creates a throughput imbalance because the delay causes unexpected frame collisions. This paper summarizes the problems caused in the medium access control (MAC) mechanism of the WLAN by a long propagation delay. We propose a MAC protocol for solving the delay-induced throughput degradation and the throughput imbalance between the uplink and the downlink in WLANs to address these problems. In the protocol, the AP extends NAV duration of CTS frame to protect an ACK frame and transmits its data frame to avoid delay induced frame collisions by piggybacking on the ACK frame transmission. We also provide a throughput model for the proposed protocol based on the Bianchi model. A numerical analysis using the proposed throughput model and simulation evaluation demonstrate that the proposed protocol increases the system throughput by 150% compared with that obtained using the conventional method, and the uplink throughput can be increased to the same level as the downlink throughput.

In this paper, for an odd prime p, two positive integers n, m with n=2m, and pm≡1 (mod 4), we derive an upper bound on the magnitude of the cross-correlation function between two decimated sequences of a p-ary m-sequence. The two decimation factors are 2 and 2(pm+1), and the upper bound is derived as $rac{3}{2}p^m + rac{1}{2}$. In fact, those two sequences correspond to the p-ary sequences used for the construction of Kasami sequences decimated by 2. This result is also used to obtain an upper bound on the cross-correlation magnitude between a p-ary m-sequence and its decimated sequence with the decimation factor $d=rac{(p^m +1)^2}{2}$.

Montgomery modular multiplication is one of the most efficient algorithms for modular multiplication of large integers. On resource-constraint embedded processors, memory-access operations play an important role as arithmetic operations in the modular multiplication. To improve the efficiency of Montgomery modular multiplication on embedded processors, this paper concentrates on reducing the memory-access operations through adding a few working registers. We first revisit previous popular Montgomery modular multiplication algorithms, and then present improved algorithms for Montgomery modular multiplication and squaring for arbitrary prime fields. The algorithms adopt the general ideas of hybrid multiplication algorithm proposed by Gura and lazy doubling algorithm proposed by Lee. By careful optimization and redesign, we propose novel implementations for Montgomery multiplication and squaring called coarsely integrated product and operand hybrid scanning algorithm (CIPOHS) and coarsely integrated lazy doubling algorithm (CILD). Then, we implement the algorithms on general MIPS64 processor and OCTEON CN6645 processor equipped with specific multiply-add instructions. Experiments show that CIPOHS and CILD offer the best performance both on the general MIPS64 and OCTEON CN6645 processors. But the proposed algorithms have obvious advantages for the processors with specific multiply-add instructions such as OCTEON CN6645. When the modulus is 2048 bits, the CIPOHS and CILD outperform the CIOS algorithm by a factor of 47% and 58%, respectively.

The biometrical identification system, introduced by Willems et al., is a system to identify individuals based on their measurable physical characteristics. Willems et al. characterized the identification capacity of a discrete memoryless biometrical identification system from information theoretic perspectives. Recently, Mori et al. have extended this scenario to list-decoding whose list size is an exponential function of the data length. However, as the data length increases, how the maximum identification error probability (IEP) behaves for a given rate has not yet been characterized for list-decoding. In this letter, we investigate the reliability function of the system under fixed-size list-decoding, which is the optimal exponential behavior of the maximum IEP. We then use Arimoto's argument to analyze a lower bound on the maximum IEP with list-decoding when the rate exceeds the capacity, which leads to the strong converse theorem. All results are derived under the condition that an unknown individual need not be uniformly distributed and the identification process is done without the knowledge of the prior distribution.

For IP-based mobile networks, efficient mobility management is vital to provision seamless online service. IP address starvation and scalability issue constrain the wide deployment of existing mobility schemes, such as Mobile IP, Proxy Mobile IP, and their derivations. Most of the studies focus on the scenario of mobility among public networks. However, most of current networks, such as home networks, sensor networks, and enterprise networks, are deployed with private networks hard to apply mobility solutions. With the rapid development, Software Defined Networking (SDN) offers the opportunity of innovation to support mobility in private network schemes. In this paper, a novel mobility management scheme is presented to support mobile node moving from public network to private network in a seamless handover procedure. The centralized control manner and flexible flow management in SDN are utilized to provide network-based mobility support with better QoS guarantee. Benefiting from SDN/OpenFlow technology, complex handover process is simplified with fewer message exchanges. Furthermore, handover efficiency can be improved in terms of delay and overhead reduction, scalability, and security. Analytical analysis and implementation results showed a better performance than mobile IP in terms of latency and throughput variation.

In a real-time system, tasks are required to be completed before their deadlines. Under normal workload conditions, a scheduler with a proper scheduling policy can make all the tasks meet their deadlines. However, in practical environment, system workload may vary widely. Once system workload becomes too heavy, so that there does not exist a feasible schedule can make all the tasks meet their deadlines, we say the system is overloaded under which some tasks will miss their deadlines. To alleviate the degrees of system performance degradation caused by the missed deadline tasks, the design of scheduling is crucial. Many design objectives can be considered. In this paper, we first focus on maximizing the total number of tasks that can be completed before their deadlines. A scheduling method based on satisfiability modulo theories (SMT) is proposed. In the method, the problem of scheduling is treated as a satisfiability problem. The key work is to formalize the satisfiability problem using first-order language. After the formalization, a SMT solver (e.g., Z3, Yices) is employed to solve this satisfiability problem. An optimal schedule can be generated based on the solution model returned by the SMT solver. The correctness of this method and the optimality of the generated schedule can be verified in a straightforward manner. The time efficiency of the proposed method is demonstrated through various simulations. Moreover, in the proposed SMT-based scheduling method, we define the scheduling constraints as system constraints and target constraints. This means if we want to design scheduling to achieve other objectives, only the target constraints need to be modified. To demonstrate this advantage, we adapt the SMT-based scheduling method to other design objectives: maximizing effective processor utilization and maximizing obtained values of completed tasks. Only very little changes are needed in the adaption procedure, which means the proposed SMT-based scheduling method is flexible and sufficiently general.

In this paper, we introduce the new concept of temporal diversity utilization based on asymmetric transmission to minimize network interference in wireless ad-hoc networks with a two-hop half-duplex relaying (HDR) protocol. Asymmetric transmission is an interference-aware backoff technique, in which each communication session (source-relay-destination link) adaptively chooses a certain subset of spectrally-orthogonal data streaming which should be delayed by the duration of one time-slot (i.e., half of one subframe). We design the problem in the HDR scenario by applying the concept of asymmetric transmission, and evaluate the game-theoretical algorithm, called asymmetric transmission game (ATG), to derive the suboptimal solution. We show that ATG is an exact potential game, and derive its convergence and optimality properties. Furthermore, we develop an approximated version of ATG (termed A-ATG) in order to reduce signaling and computational complexity. Numerical results verify that two algorithms proposed show significant synergistic effects when collaborating with the conventional methods in terms of interference coordination. Ultimately, the energy consumption to satisfy the rate requirement is reduced by up to 17.4% compared to the conventional schemes alone.

This paper proposes a null-space expansion scheme for multiuser massive MIMO transmission in order to suppress inter-user interference (IUI) triggered by the temporal variation of the channel. The downlink multiuser MIMO channel capacity of time varying channels is severely degraded since IUI must be suppressed at the transmitter side by using past estimated channel state information at the transmitter side (CSIT). Massive MIMO has emerged as one of the most promising technologies for further capacity enhancement by increasing the number of base station (BS) antenna elements. Exploiting the excess degrees of freedom (DoFs) inherent in massive MIMO, a BS with the proposed IUI suppression scheme performs multiple null-steering for each UE (User Equipment) antenna element, which expands the null-space dimension. Computer simulations show that the proposed scheme has superior IUI suppression performance to the existing channel prediction scheme in time varying channels.

With the advances in computer processing that have yielded an enormous increase in performance, numerical analytical approaches based on electromagnetic theory have recently been applied to mobile radio propagation analysis. One such approach is the ray-tracing method based on geometrical optics and the uniform geometrical theory of diffraction. In this paper, ray-tracing techniques that have been proposed in order to improve computational accuracy and speed are surveyed. First, imaging and ray-launching methods are described and their extended methods are surveyed as novel fundamental ray-tracing techniques. Next, various ray-tracing acceleration techniques are surveyed and categorized into three approaches, i.e., deterministic, heuristic, and brute force. Then, hybrid methods are surveyed such as those employing Physical optics, the Effective Roughness model, and the Finite-Difference Time-Domain method that have been proposed in order to improve analysis accuracy.

We propose a wideband reconfigurable circular-polarized single-port antenna to realize high-density linear integration for use in ground penetrating radars. We switch PIN diodes at a T-shaped probe to change its polarization. The forward- and reverse-biased probes work in cooperation to generate circular polarization. Experiments demonstrate the working bandwidths of 20.0% and 18.6% in the left- and right-hand polarization states, respectively, with 7.2 GHz center frequency. They are wider than those of conventional reconfigurable single-port circular-polarized antennas.

The purpose of DNA sequencing is to determine the order of nucleotides within a DNA molecule of target. The target DNA molecules are fragmented into short reads, which are short fixed-length subsequences composed of ‘A’, ‘C’, ‘G’ ‘T’, by next generation sequencing (NGS) machine. To reconstruct the target DNA from the short reads using a reference genome, which is a representative example of a species that was constructed in advance, it is necessary to determine their locations in the target DNA from where they have been extracted by aligning them onto the reference genome. This process is called short read mapping, and it is important to improve the performance of the short read mapping to realize fast DNA sequencing. We propose three types of FPGA acceleration methods based on hash table; (1) sorting and parallel comparison, (2) matching that allows one mutation to reduce the number of the candidates, (3) optimized hash function using variable masks. The first one reduces the number of accesses to off-chip memory to avoid the bottleneck by access latency. The second one enables to reduce the number of the candidates without degrading mapping sensitivity by allowing one mutation in the comparison. The last one reduces hash collisions using a table that was calculated from the reference genome in advance. We implemented the three methods on Xilinx Virtex-7 and evaluated them to show their effectiveness of them. In our experiments, our system achieves 20 fold of processing speed compared with BWA, which is one of the most popular mapping tools. Furthermore, we shows that the our system outperforms one of the fastest FPGA short read mapping systems.

The paper presents a small reversible language R-CORE, a structured imperative programming language with symbolic tree-structured data (S-expressions). The language is reduced to the core of a reversible language, with a single command for reversibly updating the store, a single reversible control-flow operator, a limited number of variables, and data with a single atom and a single constructor. Despite its extreme simplicity, the language is reversibly universal, which means that it is as powerful as any reversible language can be, while it is linear-time self-interpretable, and it allows reversible programming with dynamic data structures. The four-line program inverter for R-CORE is among the shortest existing program inverters, which demonstrates the conciseness of the language. The translator to R-CORE, which is used to show the formal properties of the language, is clean and modular, and it may serve as a model for related reversible translation problems. The goal is to provide a language that is sufficiently concise for theoretical investigations. Owing to its simplicity, the language may also be used for educational purposes.

Improving robustness in electrostatic discharge (ESD) protection by inserting drain-side isolated silicon-controlled rectifiers (SCRs) in a high-voltage (HV) p-channel lateral-diffused MOSFET (pLDMOS) device was investigated in this paper. Additionally, the effects of anti-ESD reliability in the HV pLDMOS transistors provided by this technique were evaluated. From the experimental data, it was determined that the holding voltage (Vh) values of the pLDMOS with an embedded npn-arranged SCR and discrete thin-oxide (OD) layout on the cathode side increased as the parasitic SCR OD row number decreased. Moreover, the trigger voltage (Vt1) and the Vh values of the pLDMOS with a parasitic pnp-arranged SCR and discrete OD layout on the drain side fluctuated slightly as the SCR OD-row number decreased. Furthermore, the secondary breakdown current (It2) values (i.e., the equivalent ESD-reliability robustness) of all pLDMOS-SCR npn-arranged types increased (>408.4%) to a higher degree than those of the pure pLDMOS, except for npn-DIS_3 and npn-DIS_2, which had low areas of SCRs. All pLDMOS-SCR pnp-arranged types exhibited an increase of up to 2.2A-2.4A, except for the pnp_DIS_3 and pnp_DIS_2 samples; the pnp_DIS_91 increased by approximately 2000.9% (249.1%), exhibiting a higher increase than that of the reference pLDMOS (i.e., the corresponding pnp-stripe type). The ESD robustness of the pLDMOS-SCR pnp-arranged type and npn-arranged type with a discrete OD layout on the SCR cathode side was greater than that of the corresponding pLDMOS-SCR stripe type and a pure pLDMOS, particularly in the pLDMOS-SCR pnp-arranged type.

We propose a microphone array speech enhancement method that integrates spatial-cue-based source power spectral density (PSD) estimation and statistical speech model-based PSD estimation. The goal of this research was to clearly pick up target speech even in noisy environments such as crowded places, factories, and cars running at high speed. Beamforming with post-Wiener filtering is commonly used in many conventional studies on microphone-array noise reduction. For calculating a Wiener filter, speech/noise PSDs are essential, and they are estimated using spatial cues obtained from microphone observations. Assuming that the sound sources are sparse in the temporal-spatial domain, speech/noise PSDs may be estimated accurately. However, PSD estimation errors increase under circumstances beyond this assumption. In this study, we integrated speech models and PSD-estimation-in-beamspace method to correct speech/noise PSD estimation errors. The roughly estimated noise PSD was obtained frame-by-frame by analyzing spatial cues from array observations. By combining noise PSD with the statistical model of clean-speech, the relationships between the PSD of the observed signal and that of the target speech, hereafter called the observation model, could be described without pre-training. By exploiting Bayes' theorem, a Wiener filter is statistically generated from observation models. Experiments conducted to evaluate the proposed method showed that the signal-to-noise ratio and naturalness of the output speech signal were significantly better than that with conventional methods.

In this letter, a simple and robust synchronization algorithm for second generation terrestrial digital video broadcasting (DVB-T2) receivers is proposed. In the proposed detection scheme, the coarse symbol timing is estimated by decimating a correlation output to give a sharper peak timing detection metric. Such a design can improve the timing synchronization accuracy as well as enhance its robustness to frequency selective channels.

In general, tunnel diodes exhibit various types of oscillation mode: the sinusoidal mode or the nonsinusoidal mode which is known as the relaxation oscillation (RO) mode. We derive a condition for generating the RO in resonant tunneling diodes (RTDs) with essential components for equivalent circuit model. A conditional equation to obtain sufficient nonlinearity towards the robust RO is clarified. Moreover, its condition also can be applied in case of a bow-tie antenna integrated RTD, thus a design policy to utilize the RO region for the antenna integrated RTD is established by numerical evaluations of time-domain large-signal nonlinear analysis towards a terahertz transmitter for broadband wireless communications.

To improve the quality of waveforms and achieve a high input power factor (IPF) for matrix rectifier, a novel quasi sliding mode control (SMC) with adaptive compensation is proposed in this letter. Applying quasi-SMC can effective obviate the disturbances of time delay and spatial lag, and SMC based on continuous function is better than discontinuous function to eliminate the chattering. Furthermore, compared with conventional compensation, an adaptive quasi-SMC compensation without any accurate detection for internal parameters is easier to be implementated, which has shown a superior advance. Theoretical analysis and experiments are carried out to validate the correctness of the novel control scheme.

Image interpolation is one of the image upsampling technologies from a single input image. This technology obtains high resolution images by fitting functions or models. Although image interpolation methods are faster than other upsampling technologies, they tend to cause jaggies and blurs in edge and texture regions. Multi-surface Fitting is one of the image upsampling techniques from multiple input images. This algorithm utilizes multiple local functions and the weighted means of the estimations in each local function. Multi-surface Fitting obtains high quality upsampled images. However, its quality depends on the number of input images. Therefore, this method is used in only limited situations. In this paper, we propose an image interpolation method with both high quality and a low computational cost which can be used in many situations. We adapt the idea of Multi-surface Fitting for the image upsampling problems from a single input image. We also utilize local functions to reduce blurs. To improve the reliability of each local function, we introduce new weights in the estimation of the local functions. Besides, we improve the weights for weighted means to estimate a target pixel. Moreover, we utilize convolutions with small filters instead of the calculation of each local function in order to reduce the computational cost. Experimental results show our method obtains high quality output images without jaggies and blurs in short computational time.