Resource Allocation for Massive Machine Type Communications in the Finite Blocklength Regime

Massive machine type communications(mMTC)have been regarded as promising applications in the future.One main feature of mMTC is short packet communication.Different from traditional long packet communication,short packet communication suffers from transmission rate degradation and a significant error rate is introduced.In this case,traditional resource allocation scheme for mMTC is no longer applicable.In this paper,we explore resource allocation for cellular-based mMTC in the finite blocklength regime.First,to mitigate the load of the base station(BS),we establish a framework for cellularbased mMTC,where MTCGs reuse the resources of cellular users(CUs),aggregate the packets generated by MTCDs,and forward them to the BS.Next,we adopt short packet theory to obtain the minimum required blocklength of a packet that transmits a certain amount of information.Then,by modeling the process of MTCGs-assisted communication as a queuing process,we derive the closed-form expression of the average delay of all MTCDs.Guided by this,we propose a joint power allocation and spectrum sharing scheme to minimize the average delay.Finally,the simulation results verify the correctness of the theoretical results and show that the proposed scheme can reduce the average delay efficiently.     

Traffic sign recognition based on deep convolutional neural network

Traffic sign recognition (TSR) is an important component of automated driving systems. It is a rather challenging task to design a high-performance classifier for the TSR system. In this paper, we propose a new method for TSR system based on deep convolutional neural network. In order to enhance the expression of the network, a novel structure (dubbed block-layer below) which combines network-in-network and residual connection is designed. Our network has 10 layers with parameters (block-layer seen as a single layer): the first seven are alternate convolutional layers and block-layers, and the remaining three are fully-connected layers. We train our TSR network on the German traffic sign recognition benchmark (GTSRB) dataset. To reduce overfitting, we perform data augmentation on the training images and employ a regularization method named “dropout”. The activation function we employ in our network adopts scaled exponential linear units (SELUs), which can induce self-normalizing properties. To speed up the training, we use an efficient GPU to accelerate the convolutional operation. On the test dataset of GTSRB, we achieve the accuracy rate of 99.67%, exceed-ing the state-of-the-art results.     

Chaos in the Fractional Order Logistic Delay System

In this paper, we study the chaotic behaviors in a fractional order logistic delay system. We find that chaos exists in the fractional order logistic delay system with an order being less than 1. In addition, we numerically simulate the continuances of the chaotic behaviors in the logistic delay system with orders from 0.1 to 0.9. The lowest order we find to have chaos in this system is 0.1. Then we further investigate two methods in controlling the fractional order chaotic logistic delay system based on feedback. Finally, we investigate a lag synchronization scheme in this system. Numerical simulations show the effectiveness and feasibility of our approach.     

Interference-aware uplink transmission schemes for multicell MIMO system

In this paper we consider interference-aware uplink transmission schemes for multicell multiple-input multiple-output (MIMO) system.Unlike conventional transmission schemes without considering the interference probably caused to other cell,we jointly optimize the transceiver beamforming vectors to maximize the desired signals while removing the intercell interference.Specifically,for a two-cell system where each transmitter is equipped with two antennas,we derive the closed-form expression for the transmit scheme called coordinated beamforming (CBF) via generalized-eigen analysis.Moreover,when asymmetric interference is considered,we give a balancing beamforming (BBF) scheme where the interfering transmitter is to strike a compromise between maximizing the desired signal andminimizing the generated interference.Simulation results show that both schemes perform better than conventional schemes under different scenarios.     

Large-Scale Traffic Characterization of Chinese Multimedia Messaging Service Using Hadoop

Recently, there have been many mo- bile value-added services in the Chinese mo- bile telecommunication market nowadays. Am- ong them, the characteristics of Multimedia Mes- saging Service （MMS） have not yet been fully understood. In this paper, with the help of a cloud computing platform, we investigated the flow-level charactefistcs of Chinese MMS. All of the experimental data were collected by the TMS equipment deployed in a major node in Sou- them China. The collection time spanned six mo- nths. We performed high-level analysis to show the basic distributions of MMS characteristics. Then, by analysing the detailed MMS features, we determined the distribution of personal MMS, and made a comprehensive comparison between 2G and 3G MMS. Finally, we tried to build a model on the personal MMS inter-arrival time, and we found that the Weibull distribution was optimum.     

Model for cascading network failures based on the nodes with different tolerance parameter

Cascading failures are common in most of the networks,where traffic is rerouted to bypass malfunctioning routers,eventually leading to an avalanche of overloads on other routers that are not equipped to handle extra traffic,which can result in a congestion regime with degradation in the network performance.In order to investigate how a small shock can trigger avalanches mechanisms affecting a considerable fraction of the network,lots of failure models have been constructed,but they have focused only on the static properties of the network that can not reflect the performance affected by the avalanche exactly.In this paper,we proposed a simple model for cascading failures in the network to explore how the failures can have a great impact on the network performance,and we allocated every node a capacity by tolerance parameter based on the node importance,which is determined by node degree,the number of the shortest paths through a node,and the number of the shortest paths through the neighbors of a node,then we fixed every element a weight to compute the node importance by analytic hierarchy process(AHP)theory.Based on our model,we analyzed the influence of different types of attacks to the network performance,and also tabled some proposals for reducing the damage that the networks suffered from the cascading failures.     

Phase noise modeling in LC oscillators implemented in SiGe technology

This paper addresses phase noise analysis of a radiofrequency LC oscillator built around a SiGe het- erojunction bipolar transistor(HBT) realized in a 0.35μm BiCMOS process,as an active device.First,we give a brief background to SiGe HBT device physics.The key point is to initiate quantitative analysis on the influence of defects induced during extrinsic base implantation on electric performances of this device.These defects are responsible for the current fluctuations at the origin of low frequency noise in BiCMOS technologies.Next,we investigate the effect of implantation defects as a source of noise in semiconductors on the phase noise of a radiofrequency LC oscillator.We observe their influence on the oscillator phase noise,and we quantify the influence of their energy distribution in the semiconductor gap.Second,we give a behavioral model of an LC oscillator containing a SiGe HBT as an active device.The key goal is to study the susceptibility of a radiofrequency oscillator built around a SiGe HBT to phase noise disturbance sources.Based on the time variance behavior of phase noise in oscillators,transient simulations(in the time domain) were used to analyze the time-dependent noise sensitivity of the oscillator.     

Dynamic Cell Range Expansion-based Interference Coordination Scheme in Next Generation Wireless Networks

Deploying Picocell Base Station（PBS） throughout a Macrocell is a promising solution for capacity improvement in the next generation wireless networks.However,the strong received power from Macrocell Base Station（MBS） makes the areas of Picocell narrow and limits the gain of cell splitting.In this paper,we firstly propose a Dynamic Cell Range Expansion（DCRE） strategy.By expanding the coverage of the cell,we aim to balance the network load between MBS and PBS.Then,we present a cooperative Resource block and Power Allocation Scheme（coRPAS）based on DCRE.The objective of coRPAS is to decrease interference caused by MBS and Macrocell User Equipments,by which we can expand regions of Picocell User Equipments.Simulation results demonstrate the superiority of our method through comparing with other existing methods.     

Binary tree-based fault location algorithm for optical burst switching network

This paper proposes an effective method of fault location based on a binary tree for optical burst switching （OBS） network. To minimize the monitoring cost, we divide the network into several monitor domains by introducing monitoring-cycle algorithms. In order to generate an exclusive code, we modify the monitoring cycle algorithm when two nodes have the same code. Through the binary tree algorithm, a pre-computation of faults in the OBS network can be achieved. When a fault happens, we can locate it immediately and accurately. Examples have proved that the algorithm has general applicability.     

Neuromorphic vision sensors: Principle,progress and perspectives

Conventional frame-based image sensors suffer greatly from high energy consumption and latency.Mimicking neurobiological structures and functionalities of the retina provides a promising way to build a neuromorphic vision sensor with highly efficient image processing.In this review article,we will start with a brief introduction to explain the working mechanism and the challenges of conventional frame-based image sensors,and introduce the structure and functions of biological retina.In the main section,we will overview recent developments in neuromorphic vision sensors,including the silicon retina based on conventional Si CMOS digital technologies,and the neuromorphic vision sensors with the implementation of emerging devices.Finally,we will provide a brief outline of the prospects and outlook for the development of this field.     

Passive Beamforming Design for Intelligent Reflecting Surface Assisted MIMO Systems

Intelligent reflecting surfaces(IRSs)constitute passive devices,which are capable of adjusting the phase shifts of their reflected signals,and hence they are suitable for passive beamforming.In this paper,we conceive their design with the active beamforming action of multiple-input multipleoutput(MIMO)systems used at the access points(APs)for improving the beamforming gain,where both the APs and users are equipped with multiple antennas.Firstly,we decouple the optimization problem and design the active beamforming for a given IRS configuration.Then we transform the optimization problem of the IRS-based passive beamforming design into a tractable non-convex quadratically constrained quadratic program(QCQP).For solving the transformed problem,we give an approximate solution based on the technique of widely used semidefinite relaxation(SDR).We also propose a low-complexity iterative solution.We further prove that it can converge to a locally optimal value.Finally,considering the practical scenario of discrete phase shifts at the IRS,we give the quantization design for IRS elements on basis of the two solutions.Our simulation results demonstrate the superiority of the proposed solutions over the relevant benchmarks.     

Converting a Display Screen into a Touchscreen

A method is presented to convert any display screen into a touchscreen by using a pair of cameras. Most state of art touchscreens make use of special touch-sensitive hardware or depend on infrared sensors in various configurations. We describe a novel computer-vision-based method that can robustly identify fingertips and detect touch with a precision of a few millimeters above the screen. In our system, the two cameras capture the display screen image simultaneously. Users can interact with a computer by the fingertip on the display screen. We have two important contributions: first, we develop a simple and robust hand detection method based on predicted images. Second, we determine whether a physical touch takes places by the homography of the two cameras. In this system, the appearance of the display screen in camera images is inherently predictable from the computer output images. Therefore, we can compute the predicted images and extract human hand precisely by simply subtracting the predicted images from captured images.     

Describing fuzzy sets using a new concept: fuzzify functor

This paper proposed a fuzzify functor as an extension of the concept of fuzzy sets.The fuzzify functor and the first-order operated fuzzy set are defined.From the theory analysis,it can be observed that when the fuzzify functor acts on a simple crisp set,we get the first order fuzzy set or type-1 fuzzy set.By operating the fuzzify functor on fuzzy sets,we get the higher order fuzzy sets or higher type fuzzy sets and their membership functions.Using the fuzzify functor we can exactly describe the type-1 fuzz...     

Weighted Discriminative Sparse Coding for Image Classification

In the discriminative sparse coding, the reconstruction residual over each class-specific sub- dictionary can provide great discriminative and label in- formation. In this paper, we propose a weighted discrim- inative sparse coding method by using the residual as the weight. For a test sample, we first compute its sparse code over each learnt sub-dictionary, and then use the recon- struction residual over each sub-dictionary to weight the corresponding sub-dictionary,thereby forming a weighted sample-specific structure dictionary, over which we com- pute a new sparse code for the test sample. This code car- ries more discriminative information about interclass dif- ference. Our method yields a unique structure dictionary for each test sample, so that samples with the same class labels have more similar distributions of dictionary atom contributions. Experimental results demonstrate that the proposed method outperforms some state-of-the-art meth- ods under the same learning conditions.     

Multi-Proxy Signature Without Random Oracles

In a multi-proxy signature scheme, an original signer delegates his or her signing capability to a group of proxy signers, in such a way that only the cooperation of all the proxy signers can generate a valid proxy signa-ture on behalf of the original signer. Several multi-proxy signature schemes have been proposed so far. However, these works either only provide informal security analysis, or provide a security proof in the random oracle model,which has received a lot of criticism that the proofs in the random oracle model are not proofs. In this paper, we propose a new construction of multi-proxy signature that can be proven secure without using the random oracles. As for the security, we divide the potential adversaries into three kinds according to their attack power, and prove that the proposed scheme is unforgeable against all kinds of adver-saries, assuming the Computational Diffl-Hellman problem is intractable. Furthermore, the new scheme has the property that the size of a multi-proxy signature is inde- pendent on the number of the proxy signers. As far as we know, this is the first multi-proxy signature scheme that can be proven secure in the standard model.     

Small Components of the Wave Function of Electron

In this paper, via an analogy between the wave functions of free electron and free electromagnetic fields, we study the relation between the large components and the small components of the wave function of electron, and show that in some cases the small components cannot be ignored. As an application, we will demonstrate that not only the spin quantum states of a moving electron but also those of a motionless electron can be affected by some special electrostatic fields. This may provide a ne…     

Double-branch forgery image detection based on multi-scale feature fusion

Most of existing methods exhibit poor performance in detecting forged images due to the small size of tampered areas and the limited pixel difference between untampered and tampered regions. To alleviate the above problem, a double-branch tampered image detection based on multi-scale features is proposed. Firstly, we introduce a fusion module based on attention mechanism in the first branch to enhance the network’s sensitivity towards tampered regions. Secondly, we construct a second branch spec...     

基于共扼编码的量子概率加密方案(英文)

We present a quantum probabilistic encryption algorithm for a private-key encryption scheme based on conjugate coding of the qubit string. A probabilistic encryption algorithm is generally adopted in public-key encryption protocols. Here we consider the way it increases the unicity distance of both classical and quantum private-key encryption schemes. The security of quantum probabilistic privatekey encryption schemes against two kinds of attacks is analyzed. By using the no-signalling postulate, we show that the scheme can resist attack to the key. The scheme’s security against plaintext attack is also investigated by considering the information-theoretic indistinguishability of the encryption scheme. Finally, we make a conjecture regarding Breidbart’s attack.     

无线体域网节能MAC协议综论(英文)

In this paper, we provide a comprehensive survey of key energy-efficient Medium Access Control (MAC) protocols for Wireless Body Area Networks (WBANs). At the outset, we outline the crucial attributes of a good MAC protocol for WBAN. Several sources that contribute to the energy inefficiency of WBAN are identified, and features of the various MAC protocols qualitatively compared. Then, we further investigate some representative TDMA-based energy-efficient MAC protocols for WBAN by emphasizing their strength...     

RIS-Aided Constant-Envelope Beamforming for Multiuser Wireless Power Transfer:A Max-Min Approach

As a revolutionary hardware technology that can reconfigure the propagation environment,reconfigurable intelligent surfaces(RISs)have been regarded as a promising solution to enhance wireless networks.In this paper,we consider a multiuser multiple-input single-output(MISO)wireless power transfer(WPT)system,which is assisted by several RISs.In order to improve energy efficiency and reduce hardware cost,we consider that the energy transmitter(ET)in the WPT system is equipped with a constant-envelope analog beamformer,instead of a digital beamformer.Focusing on user fairness,we study a minimum received power maximization problem by jointly optimizing the ET beamforming and the RIS phase shifts,subject to the constant-envelope constraints.We iteratively solve this non-convex maxmin problem by leveraging both the successive convex approximation(SCA)method and the alternating direction method of multipliers(ADMM)algorithm.Numerical results demonstrate the effectiveness of the proposed algorithm and show attractive performance gain brought by RISs.