Research of Multi-Rate LDPC Decoding in Optical Communication System

Low-density parity-check code (LDPC) not only has good performance approaching the Shannon limit, but also has low decoding complexity and flexible structure. It is a research hot-spot in the field of channel coding in recent years and has a wide range of application prospects in optical communication systems. In this paper, the decoding aspects and performance of LDPC codes are analyzed and compared according to the bit error rate (BER) of LDPC codes. The computer simulation was carried out under additive white Gaussian noise (AWGN) channel and binary phase shift keying (BPSK) modulation. Through theoretical analysis and simulation results, this paper explores the way of multi-rate LDPC decoding.

Image Tamper Detection and Multi-Scale Self-Recovery Using Reference Embedding with Multi-Rate Data Protection

This paper proposes a multi-scale self-recovery(MSSR)approach to protect images against content forgery.The main idea is to provide more resistance against image tampering while enabling the recovery process in a multi-scale quality manner.In the proposed approach,the reference data composed of several parts and each part is protected by a channel coding rate according to its importance.The first part,which is used to reconstruct a rough approximation of the original image,is highly protected in order to resist against higher tampering rates.Other parts are protected with lower rates according to their importance leading to lower tolerable tampering rate(TTR),but the higher quality of the recovered images.The proposed MSSR approach is an efficient solution for the main disadvantage of the current methods,which either recover a tampered image in low tampering rates or fails when tampering rate is above the TTR value.The simulation results on 10000 test images represent the efficiency of the multi-scale self-recovery feature of the proposed approach in comparison with the existing methods.

OPTIMAL FEED RATE CONTROL FOR MULTI-AXIS CNC MACHINING OF FREE FORM SURFACES

Considering machining efficiency, surface quality and wear of cutter and machine, it is necessary to maintain high, stable and constant surface feed rate as far as possible.The feed late control strategy for multi-axis CNC machining of free-form surfaces is presented. It comprises: ①the determination of effective feed rate; ②the adoption of suitable approaches to smooth feed rate. This strategy considers path geometry, actuator limitation and machine dynamics. The result shows that machining efficiency is improved effectively.

Study of multi-rate multi-user detection based on supervision decision

Multi-user detection (MUD) based on multirate transmission in code division multiple access (CDMA) system is discussed. Under the requirement of signal interference ratio (SIR) detection at base station and framework with parallel interference cancellation, a supervision decision algorithm based on pre-decision of probabilistic data association (PDA) and hard decision is proposed. The detection performance is analyzed and simulation is implemented to show that the supervision decision algorithm improves the detection performance effectively.

A SINGLE PROCESSOR MULTI-RATE VOCODER

This paper presents the design of a full-duplex multi-rate vocoder which implements an LPC-10, CELPC and VSELPC algorithms in real time. A single commercially available digital signal processor IC, the TMS320C25, is used to perform the digital processing. The channel interfaces are configured with the design of ASIC, and including timing and control logic circuits.

A NEW DESIGN METHOD OF CDMA SPREADING CODES BASED ON MULTI-RATE UNITARY FILTER BANK

It is well-known that the multi-valued CDMA spreading codes can be designed by means of a pair of mirror multi-rate filter banks based on some optimizing criterion. This paper indicates that there exists a theoretical bound in the performance of its circulating correlation property, which is given by an explicit expression. Based on this analysis, a criterion of maximizing entropy is proposed to design such codes. Computer simulation result suggests that the resulted codes outperform the conventional binary balanced Gold codes for an asynchronous CDMA system.

Multi-rate sensor fusion-based adaptive discrete finite-time synergetic control for flexible-joint mechanical systems

This paper proposes an adaptive discrete finite-time synergetic control （ADFTSC） scheme based on a multi-rate sensor fusion estimator for flexible-joint mechanical systems in the presence of unmeasured states and dynamic uncertainties. Multi-rate sensors are employed to observe the system states which cannot be directly obtained by encoders due to the existence of joint flexibilities. By using an extended Kalman filter （EKF）, the finite-time synergetic controller is designed based on a sensor fusion estimator which estimates states and parameters of the mechanical system with multi-rate measurements. The proposed controller can guarantee the finite-time convergence of tracking errors by the theoretical derivation. Simulation and experimental studies are included to validate the effectiveness of the proposed approach.

A NOVEL CROSS-LAYER STRATEGY OF VIDEO TRANSMISSION TO SOLVE PERFORMANCE ANOMALY IN MULTI-RATE IEEE 802.11 NETWORKS

When wireless hosts use different rates to transmit data in IEEE 802.11 networks, it will take on the state of performance anomaly which will severely decrease the throughputs of all the higher rate hosts. Hence, it is bad for video service transmission. Considering that video is very sensitive to packet delivery delay but can tolerate some packet losses, we propose a novel cross-layer scheme which takes these two characteristics into consideration. Firstly, the maximum number of retransmissions for a video Medium Access Control (MAC) frame is computed in MAC layer according to video frame rate requirement of application layer and current access delay of MAC layer. Secondly, within the margin of the tolerant Packet Loss Rate (PLR) of application layer, several video MAC frames are allowed to drop so that we can adaptively select the transmission rate as high as possible for the rest of video MAC frames in terms of current channel quality and the maximum number of retransmissions. Experiment results show that the proposed method can reduce the delay and jitter of video service and improve the throughputs of fast hosts. Therefore, it increases the quality of reconstructed video to a certain extent and relieves the performance anomaly of network effectively.

On the Performance of Blind Chip Rate Estimation in Multi-Rate CDMA Transmissions Using Multi-Rate Sampling in Slow Flat Fading Channels

This paper considers blind chip rate estimation of DS-SS signals in multi-rate and multi-user DS-CDMA systems over channels having slow flat Rayleigh fading plus additive white Gaussian noise. Channel impulse response is estimated by a subspace method, and then the chip rate of each signal is estimated using zero crossing of estimated differential channel impulse response. For chip rate estimation of each user, an algorithm which uses weighted zero-crossing ratio is proposed. Maximum value of the weighted zero crossing ratio takes place in the Nyquist rate sampling frequency, which equals to the twice of the chip rate. Furthermore, bit time of each user is estimated using fluctuations of autocorrelation estimators. Since code length of each user can be obtained using bit time and chip time ratio. Fading channels reduce reliability factor of the proposed algo-rithm. To overcome this problem, a receiver with multiple antennas is proposed, and the reliability factor of the proposed algorithm is analyzed over both spatially correlated and independent fading channels.

Adaptive Rate Control for Multi-Antenna Multicast in OFDM Systems

We propose two rate control schemes for multi-antenna multicast in OFDM systems, which aim to maximize the minimum average rate over all users in a multicast group. In our system, we do not require all multicast users to successfully recover the signals received on each subcarrier. In contrast, we allow certain loss for multicast users, such that the multicast transmission rate can be increased. We assume that the loss-repairing can be completed at upper protocol layers via advanced fountain codes. Following this principle, we formulate the rate control problem via beamforming in multi-antenna multicast to optimize the minimum achievable rate for all multicast users. While the computation complexity to solve for the optimal beamformer is prohibitively high, we propose a suboptimal iterative rate control scheme. Moreover, we modify the above optimization problem by selecting a ?xed proportion of users on each subcarrier. The beamformer searching process will then be performed only based on the selected users on each subcarrier, such that the complexity can be further reduced. We also solve this new problem with a low complexity approach. Theoretical analyses and simulation results show that our proposed two rate control schemes can have higher minimum average rate than the baseline scheme without rate control, while achieving low complexity.

Joint routing and rate allocation for multiple video streams in ad-hoc wireless networks

The support for multiple video streams in an ad-hoc wireless network requires appropriate routing and rate allocation measures ascertaining the set of links for transmitting each stream and the encoding rate of the video to be delivered over the chosen links. The routing and rate allocation procedures impact the sustained quality of each video stream measured as the mean squared error (MSE) distortion at the receiver, and the overall network congestion in terms of queuing delay per link. We study the trade-off between these two competing objectives in a convex optimization formulation, and discuss both centralized and dis- tributed solutions for joint routing and rate allocation for multiple streams. For each stream, the optimal allocated rate strikes a balance between the selfish motive of minimizing video distortion and the global good of minimizing network congestions, while the routes are chosen over the least-congested links in the network. In addition to detailed analysis, network simulation results using ns-2 are presented for studying the optimal choice of parameters and to confirm the effectiveness of the proposed measures.

Corrosion resistance of 2195 aluminum alloy treated by multi-step-heating-rate controlled process

2195 aluminum-lithium alloy was widely applied in the aviation and aerospace industry, but it is highly susceptible to pitting and intergranular corrosion undergoing sever corrosive circumstance and moisture atmosphere. To solve this problem and consequently to prolong its service life, a multi-step-heating-rate(MSRC) process was carried out. Investigations were carried out to find the effect of the MSRC process on the alloys corrosion resistance. It is found that the MSRC process is more favorable for the uniform phase precipitation by comparing the corrosion resistance of samples treated by traditional heat treatments. The potential difference between phases can be reduced and intergranular corrosion is able to be prohibited efficiently. Besides, the rare earth infiltration is beneficial to improving the corrosion resistance. As heating time increases, the corrosion resistance declines gradually, samples treated by artificial aging and solid solution also exhibit a better corrosion resistance.

Downlink call admission control with power allocation and rate scheduling for IDMA-based multi-beam satellite systems

Considering the advantage of interleave-division multiple-access(IDMA) technique and the technical bottlenecks in the existing satellite systems,IDMA is introduced into satellite communication networks.To further validate the IDMA into satellite systems,an effective call admission control(CAC) is proposed to maximize the resource utilization.After establishing the multi-beam satellite system model based on variable spreading gain(VSG) IDMA,the power allocation scheme based on SINR evolution technique and transmission rate adaptation for nonreal time interactive traffic are designed as integrated parts of the CAC,working together to improve the system performance in terms of power efficiency and throughput.Further,the analysis and simulation results show that IDMA under the proposed scheme can provide better QoS,in terms of the blocking/dropping probability,outage probability as well as delay performance.

Multi-h CPM体制误码和频谱性能研究

介绍了Multi-h CPM体制的基本原理,提出了基于维特比算法的最大似然序列检测方法,对各种调制指数下的CPM信号进行了仿真实验,得到其解调误码率曲线和频谱带宽,并与PCM-FM体制进行了比较分析。仿真分析结果表明,根据实际应用需求,通过合理选择调制指数,Multi-h CPM体制具有比PCM-FM更好的解调误码性能和带宽利用率,这在未来的高码率遥测系统中具有重要的应用价值。

Multi-agent System中多维度信誉模型设计

在multi-agent system(MAS)中引入信誉机制是解决Agent间复杂交互问题促进合作的有效途径.在构造信誉置信度和期望信誉级别两种信誉表示形式的基础上,提出第三方权威机构的资质评价作为第三种信誉信息来源,引入活动相似算子和信息来源权重,从评价目标多维性和信息来源多维性对初始信誉置信度评价进行修正,运用Dempster规则合成计算获得最终信誉评价,并以实例验证了模型的实用性.最后对模型的效率与抗威胁性进行了检验,结果表明模型解决了新进Agent的信誉赋值问题,可以在一定程度上激励Agent主动给出交互评价,并能很好地解决或缓解分布式系统中关键的8种安全威胁.

计及电-碳交易与综合贡献率的多微网合作运行优化策略

多微网协同互联能够提高系统运行的稳定性与可靠性。针对多微网(multi-microgrids,MMG)系统合作运行过程中由于各微网分属于不同的利益主体而产生的微电网之间的电能交易问题、碳交易问题与利益分配问题,提出一种计及电-碳交易与综合贡献率的多微网合作运行优化策略。首先,分析了含点对点(peer-to-peer,P2P)电-碳交易的多微网合作运行架构,并引入碳捕集系统(carbon capture system,CCS)与电转气(power to gas,P2G)装置,建立了微电网系统及设备模型。其次,在单微网模型构建之后,基于纳什议价理论,构建了含P2P电-碳交易的多微网系统合作运行模型,并将非凸非线性的纳什议价问题转化为易于求解的MMG合作成本最小化与支付收益最大化两个子问题。然后,在合作后的利益分配过程中,量化各微电网对MMG的综合贡献程度并计算出各自的综合贡献率,通过综合贡献率来分配各微网的收益。最后,采用交替方向乘子法(alternating direction multiplier method,ADMM)求解,有效保护了各微网隐私。算例分析与方案对比结果表明,所提策略能够实现微网间的P2P电-碳交易,有效降低MMG总运行成本,减少系统的碳排放量,并且采用的利益分配策略公平合理,能够有效提升各微网参与合作运行的积极性。

ESG评级能否提高企业韧性?--基于ESG评级事件的准自然实验

在充满不确定性的商业环境中,企业韧性成为组织管理和战略规划中的关键议题。以商道融绿公布ESG评级为准自然实验,基于2010—2020年沪深A股上市公司数据,探讨ESG评级对企业韧性的影响。研究发现:ESG评级可以显著增强企业韧性;ESG评级通过缓解融资约束、降低信息不对称和提升创新能力来增强企业韧性;对于管理层短视程度较低、破产风险较大和市场关注度较高的企业,ESG评级驱动企业韧性提升的作用更为显著;ESG评级对企业的高绩效增长和低财务波动均具有影响,但对前者的影响具有滞后性;ESG评级对ESG得分较高和较低企业的韧性均有正向影响;ESG评级对企业韧性的增强效应尚未呈现出明显的溢出效应;新冠疫情削弱了ESG评级对企业韧性的增强效应。研究结论为企业提供了在不确定环境中增强韧性的有效途径,也为ESG策略制订和实施提供有力支持。

RM-RT^(2)NI:融合评论时效与可信近邻影响力的推荐模型

基于矩阵分解的推荐模型虽然能够处理高维评分数据,但容易遭受评分数据稀疏性的困扰。基于评分和评论的推荐模型通过外加隐藏在评论中的用户偏好与物品属性信息,缓解了评分数据的稀疏性,但在特征提取时大多没有关注评论时效性和可信近邻影响力,无法获得更丰富的用户和物品特征。为进一步提高推荐精度,提出了融合评论时效与可信近邻影响力的推荐模型RM-RT^(2)NI。基于评分矩阵,该模型使用矩阵分解提取了用户偏好和物品属性的浅层特征,利用云模型和修正的用户相似度评估模型和新构建的信度评估模型提取出可信近邻影响力;基于评论文本,该模型利用BERT模型获得每条评论的隐表达,利用双向GRU提取评论间的联系,利用新构建的融合时间因子的注意力机制识别各评论的时效贡献度,以获取用户和物品的深层特征。在此基础上,将用户浅层特征、深层特征以及可信近邻影响力特征融合成用户特征,将物品浅层特征和深层特征融合成物品特征,并将它们输入全连接神经网络以预测用户-物品评分。在5组公开数据集上对RM-RM-RT^(2)NI的推荐性能进行了实验评估,结果显示,与7个基线模型相比,RM-RT^(2)NI具有更高的评分预测精度,且RMSE平均降低了3.0657%。

Consensus Control With a Constant Gain for Discrete-time Binary-valued Multi-agent Systems Based on a Projected Empirical Measure Method

This paper studies the consensus control of multiagent systems with binary-valued observations.An algorithm alternating estimation and control is proposed.Each agent estimates the states of its neighbors based on a projected empirical measure method for a holding time.Based on the estimates,each agent designs the consensus control with a constant gain at some skipping time.The states of the system are updated by the designed control,and the estimation and control design will be repeated.For the estimation,the projected empirical measure method is proposed for the binary-valued observations.The algorithm can ensure the uniform boundedness of the estimates and the mean square error of the estimation is proved to be at the order of the reciprocal of the holding time(the same order as that in the case of accurate outputs).For the consensus control,a constant gain is designed instead of the stochastic approximation based gain in the existing literature for binary-valued observations.And,there is no need to make modification for control since the uniform boundedness of the estimates ensures the uniform boundedness of the agents’states.Finally,the systems updated by the designed control are proved to achieve consensus and the consensus speed is faster than that in the existing literature.Simulations are given to demonstrate the theoretical results.

改进的MVO-GRNN神经网络岩爆预测模型研究

准确预测岩爆烈度等级能有效指导岩爆灾害的防控。根据影响岩爆发生及烈度等级的3个因素构建岩爆评价指标体系,提出一种基于改进多元宇宙算法(Improved Multi-Verse Optimizer,IMVO)优化广义回归神经网络(General Regression Neural Network,GRNN)的岩爆预测模型。在普通多元宇宙算法(MVO)的基础上,运用自适应平衡机制调节MVO算法中的虫洞存在概率(V_(WEP))和旅行距离率(V_(TDR))两个重要参数来改进该算法;再运用改进的多元宇宙算法优化广义回归神经网络的光滑度,通过训练数据优选出最佳光滑因子σ,得到IMVO-GRNN神经网络岩爆烈度预测模型;最后结合工程实例验证模型的性能。研究表明,该模型相比传统模型寻优能力更强,精度更高,为岩爆预测提供了一种新的思路。