Efficient unequal error protection for online fountain codes

In this paper,an efficient unequal error protection(UEP)scheme for online fountain codes is proposed.In the buildup phase,the traversing-selection strategy is proposed to select the most important symbols(MIS).Then,in the completion phase,the weighted-selection strategy is applied to provide low overhead.The performance of the proposed scheme is analyzed and compared with the existing UEP online fountain scheme.Simulation results show that in terms of MIS and the least important symbols(LIS),when the bit error ratio is 10-4,the proposed scheme can achieve 85%and 31.58%overhead reduction,respectively.

Rate Adaptation for Decoding-and-Forward Relay Channel by Random Projections Codes

This paper investigates rate adaptation schemes for decoding-and-forward (DF) relay system based on random projections codes (RPC). We consider a classic three node relay system model, where relay node performs on half-duplex mode. Then, we give out receiving diversity relay scheme and coding diversity relay scheme, and present their jointly decoding methods. Furthermore, we discuss the performance of the two schemes with different power allocation coefficients. Simulations show that our relay schemes can achieve different gain with the help of relay node. And, we should allocate power to source node to just guarantee relay node can decode successfully, and allocate remain power to relay node as far as possible. In this way, this DF relay system not only achieves diversity gain, but also achieves higher and smooth spectrum efficiency.

On Latency Reductions in Vehicle-to-Vehicle Networks by Random Linear Network Coding

In the Internet of vehicles(IoV),direct communication between vehicles,i.e.,vehicle-tovehicle(V2V)may have lower latency,compared to the schemes with help of Road Side Unit(RSU)or base station.In this paper,the scenario where the demands of a vehicle are satisfied by cooperative transmissions from those one in front is considered.Since the topology of the vehicle network is dynamic,random linear network coding is applied in such a multisource single-sink vehicle-to-vehicle network,where each vehicle is assumed to broadcast messages to others so that the intermediate vehicles between sources and sink can reduce the latency collaboratively.It is shown that the coding scheme can significantly reduce the time delay compared with the non-coding scheme even in the channels with high packet loss rate.In order to further optimize the coding scheme,one can increase the generation size,where the generation size means the number of raw data packets sent by the source node to the sink node in each round of communication.Under the premise of satisfying the coding validity,we can dynamically select the Galois field size according to the number of intermediate nodes.It is not surprised that the reduction in the Galois field size can further reduce the transmission latency.

Improved Adaptive Random Convolutional Network Coding Algorithm

To address the issue of field size in random network coding, we propose an Improved Adaptive Random Convolutional Network Coding (IARCNC) algorithm to considerably reduce the amount of occupied memory. The operation of IARCNC is similar to that of Adaptive Random Convolutional Network Coding (ARCNC), with the coefficients of local encoding kernels chosen uniformly at random over a small finite field. The difference is that the length of the local encoding kernels at the nodes used by IARCNC is constrained by the depth; meanwhile, increases until all the related sink nodes can be decoded. This restriction can make the code length distribution more reasonable. Therefore, IARCNC retains the advantages of ARCNC, such as a small decoding delay and partial adaptation to an unknown topology without an early estimation of the field size. In addition, it has its own advantage, that is, a higher reduction in memory use. The simulation and the example show the effectiveness of the proposed algorithm.

True random coded photon counting Lidar

A true random coded photon counting Lidar system is proposed in this paper,in which a single photon detector acts as the true random sequence signal generator instead of the traditional function generator.Compared with the traditional pseudo-random coded method,the true random coded method not only improves the anti-crosstalk capability of the system,but more importantly,it effectively overcomes the adverse effect of the detector’s dead time on the ranging performance.The experiment results show that the ranging performance of the true random coded method is obviously better than that of the pseudo-random coded method.As a result,a three-dimensional scanning imaging of a model car is completed by the true random coded method.

Robustness self-testing of states and measurements in the prepare-and-measure scenario with 3 → 1 random access code

Recently, Tavakoli et al.proposed a self-testing scheme in the prepare-and-measure scenario, showing that self-testing is not necessarily based on entanglement and violation of a Bell inequality [Phys.Rev.A 98 062307(2018)].They realized the self-testing of preparations and measurements in an N → 1(N ≥ 2) random access code(RAC), and provided robustness bounds in a 2 → 1 RAC.Since all N → 1 RACs with shared randomness are combinations of 2 → 1 and 3 → 1 RACs, the3 → 1 RAC is just as important as the 2 → 1 RAC.In this paper, we find a set of preparations and measurements in the3 → 1 RAC, and use them to complete the robustness self-testing analysis in the prepare-and-measure scenario.The method is robust to small but inevitable experimental errors.

USING ERROR-CORRECTING ENCODERS TO DESIGN LOCAL-RANDOM SEQUENCE GENERATORS

This paper proved the statement that a good linear block encoder is in fact a good local-random sequence generator. Furthermore, this statement discovers the deep relationship between the error-correcting coding theory and the modern cryptography.

Quasi-cyclic Random Projection Code and Hardware Implementation

Random Projection Code (RPC) is a mechanism that combines channel coding and modulation together and realizes rate adaptation in the receiving end. Random projection code’s mapping matrix has significant influences on decoding performance as well as hardware implementation complexity. To reduce hardware implementation complexity, we design a quasi-cyclic mapping matrix for RPC codes. Compared with other construction approaches, our design gets rid of data filter component, thus reducing chip area 7284.95 um2, and power consumption 331.46 uW in 0.13 um fabrication. Our simulation results show that our method does not cause any performance loss and even gets 0.2 dB to 0.5 dB gain at BER 10-4.

End-to-end verifiable electronic voting scheme of blockchain based on random linear block code

Blockchain is an emerging decentralized technology of electronic voting.The current main consensus protocols are not flexible enough to manage the distributed blockchain nodes to achieve high efficiency of consensus.For practical implementation,the consensus based on random linear block code(RLBC)is proposed and applied to blockchain voting scheme.Along with achieving the record correctness and consistency among all nodes,the consensus method indicates the active and inactive consensus nodes.This ability can assist the management of consensus nodes and restrain the generating of chain forks.To achieve end-to-end verifiability,cast-or-audit and randomized partial checking(RPC)are used in the proposed scheme.The voter can verify the high probability of correctness in ballot encryption and decryption.The experiments illustrate that the efficiency of proposed consensus is suitable for blockchain.The proposed electronic voting scheme is adapted to practical implementation of voting.

Algebraic Approach to Random Convolutional Network Coding over Wireless Packet Networks

To characterize the algebraic structure of wireless network coding, a hypergragh is utilized to model wireless packet networks from network layer. The algebraic description of random convolutional network coding is deduced, and the coding condition is also presented. Analyses and simulations show that random convolutional coding is capacity-achieving with probability approaching 1.

Pseudo-Random Coding Side-Lobe Suppression Method Based on CLEAN Algorithm

A pseudo-random coding side-lobe suppression method based on CLEAN algorithm is introduced.The CLEAN algorithm mainly processes pulse compression results of a pseudo-random coding,and estimates a target＇s distance by a method named interpolation method,so that we can get an ideal pulse compression result of the target,and then use the adjusted ideal pulse compression side-lobe to cut the actual pulse compression result,so as to achieve the remarkable performance of side-lobe suppression for large targets,and let the adjacent small targets appear.The computer simulations by MATLAB with this method analyze the effect of side-lobe suppression in an ideal or noisy environment.It is proved that this method can effectively solve the problem due to the side-lobe of pseudo-random coding being too high,and can enhance the radar＇s multi-target detection ability.

Performance Analysis Concerning Antinoise for Several Pseudo-random Code Fuzes

Introduces in brief the principle of three kinds pseudo-random code fuzes, viz. the pseudo-random code phase modulation fuze,the pseudo-random code phase modulation and pulse amplitude modulation(PAM) combined fuze,and the pseudo-random code phase modulation and random(pseudo-random) pulse position modulation(PPM) combined fuze. On this basis, their SNR gains in signal processing after band pass filter to the correlation detection, and the overall SNR gains of the whole procedure after correlation detection are deduced in detail. The results show that the latter two kinds of fuzes have the same performances concerning antinoise that are stronger than that of the pseudo-random code phase modulation fuze.

Modulation for Digital Radio Broadcasting Using Amplitude Autocorrelation of Pseudo Random Noise Codes to Carry Information

The frequency bands used in mobile communications are allocated according to the type of application. With the need for more channels, the frequency spectrum has become a scarce natural resource. This study shows the results of a proposed modulation using a variation of the autocorrelation of pseudo-random codes to carry information. The work also presents the generation of multiple orthogonal axes to increase the bit rate thus improving the channel efficiency.

A CLASS OF LDPC CODE'S CONSTRUCTION BASED ON AN ITERATIVE RANDOM METHOD

This letter gives a random construction for Low Density Parity Check (LDPC) codes, which uses an iterative algorithm to avoid short cycles in the Tanner graph. The construction method has great flexible choice in LDPC code's parameters including codelength, code rate, the least girth of the graph, the weight of column and row in the parity check matrix. The method can be applied to the irregular LDPC codes and strict regular LDPC codes. Systemic codes have many applications in digital communication, so this letter proposes a construction of the generator matrix of systemic LDPC codes from the parity check matrix. Simulations show that the method performs well with iterative decoding.

基于长度可变密钥的光学图像加密方法

为提升光学图像加密效果,设计了一种基于长度可变密钥的光学图像加密方法。基于混沌方程构成混沌序列均匀化普适算法,运用该算法生成均匀化伪随机序列,以此作为长度可变密钥,经空间光调制器调制后,转换此类密钥为伪随机相位掩模(PRPM),运用两个转换后PRPM双重随机相位编码初始光学图像,并结合变形分数傅里叶变换(AFrFT),相位转换编码后光学图像,获得加密光学图像,完成光学图像加密。实验结果显示,该方法可针对不同光学图像生成敏感性与唯一性密钥,实现不同光学图像的加密处理,加密效果显著,加密光学图像的像素频数分布均匀,且解密后光学图像与初始光学图像几乎一致,整体加解密效果理想,可有效保障光学图像的安全性,而且本方法可以在最短3 s的时间内完成光学图像的加密和解密,加解密效率更高,综合效果更佳。

基于ECOC平衡随机森林的雷达降水粒子分类

针对数据不平衡情况下的降水粒子分类问题,提出了一种基于纠错输出码(error correcting output code,ECOC)平衡随机森林的双偏振气象雷达降水粒子分类方法。首先,将多类别降水粒子数据集编码为多个二分类数据集;然后,对二分类数据集进行有放回的平衡重采样,构建多棵分类回归树;最后,利用所有的分类回归树联合进行降水粒子分类。对实测数据的处理结果表明,所提方法能够在保证总体准确率较高的情况下,大幅提高少数类的分类效果。

基于小波压缩深度学习重构的多图像光学加密

为解决多图像加密算法密文体积大、加密效果差、重构效果不理想等问题,提出一种基于小波压缩和深度学习重构的多图像光学加密方法。利用小波压缩提取多图像的低频部分,将重排后的新图放入改进的FDT-DRPE光学加密系统中得到密文;利用矢量分解和螺旋相位变换克服FDT-DRPE不敏感问题;构造的L_S混沌系统提高密钥敏感性。提出新型深度学习网络模型BHCN,解决传统图像重构精度不高问题。实验结果表明,密文体积可压缩至原图的1/4,重构图像的峰值信噪比为34.57 dB,结构相似性为0.9521,与同类文献相比,速度更快,重构效果更好,安全性更高。

基于基模图的码率兼容广义稀疏随机码及空天通信应用

空天通信信道时变性强且包含复杂干扰,而经典信道编码以高斯信道为假设设计,其直接应用将带来通信资源效率低、灵活性差、传输可靠性难以保障等问题.本文针对这一问题提出了一种基于基模图的广义稀疏随机编码构造及实现方法,通过在基于基模图随机编码架构上引入高维代数约束,提升了在极低码率下的编码纠错性能;进一步通过动态调整高维约束阶次和维数实现码率兼容,支持对信道非高斯特征以及传输业务需求的适配.测试结果表明,该编码可实现码率范围1/40~1可变、信息位长度104~20000 bit可变、速率25 Kbps~10 Gbps可变的编译码,可在SNR=-37.1 dB(对应E_(b)/N_(0)=-0.79 dB)的低信噪比下实现误帧率优于1.0×10^(‒4)的高可靠通信.

面向二进制代码的细粒度软件多样化方法

现有软件多样化方法大多需要源代码,基于编译器生成变体二进制,而对二进制代码直接进行转换时由于缺乏调试信息导致难以正确逆向,且易造成高额的性能开销。为此,提出一种面向二进制代码的细粒度软件多样化方法。通过静态二进制重写技术以函数块为单位进行重排序,随机化函数在代码段中的原始位置,同时使程序的内存片段gadgets位置发生改变,使得攻击者对程序的先验知识失效,以防御大规模代码重用攻击。为了进一步提高攻击者破解难度,对基本块内的指令进行依赖性分析,实现基本块内指令随机化,同时使得随机化后基本块的原始语义不变。性能测试结果表明,函数重排序对gadgets存活率的影响大于基本块内指令重排序,两者同时使用时程序的gadgets平均存活率为5.71%;模糊哈希算法Tlsh比较结果显示,该方法能够有效躲避同源性检测;使用工具Bindiff进行测试的结果表明,多样化后基本块内指令重排序的异构度大于函数重排序,且在基准测试集SPEC CPU2006上函数重排序和指令重排序同时使用时平均运行开销仅为3.1%,具有良好的实用性。