A Summary of the Large-Scale Access Convergence Network Structure

Under the requirement of everything over IP, network service shows the following characteristics:(1) network service increases its richness;(2) broadband streaming media becomes the mainstream. To achieve unified multi-service bearing in the IP network, the largescale access convergence network architecture is proposed. This flat access convergence structure with ultra-small hops, which shortens the service transmission path, reduces the complexity of the edge of the network, and achieves IP strong waist model with the integration of computation, storage and transmission. The key technologies are also introduced in this paper, including endto-end performance guarantee for real time interactive services, fog storing mechanism, and built-in safety transmission with integration of aggregation and control.

Solutions for Large-Scale and Low-Cost Access to Space in the Future

The objective of this study is to identify the requirements of access to space for the future, the required methodology, key technologies and international cooperation mode. Firstly, the mission requirements and the challenges of current technologies to access to space are analyzed and summarized. The solutions and related key technologies to realize large-scale and low-cost access to space(L2 AS) are presented here, including the low-cost design of expendable launch vehicles and a reusable space transportation system, interface standardization, and new conceptual launchers. The mission modes based on launch vehicles to realize L2 AS and three future international collaboration modes are presented. Lastly, the relevant conclusions and suggestions are given.

Review of the development of power system out-of-step splitting control and some thoughts on the impact of large-scale access of renewable energy

Out-of-step oscillation is a very destructive physical phenomenon in power system, which could directly cause big blackout accompanied by serious sociology-economic impacts. Out-of-step splitting control is an indispensable means, which could protect the system from major shocks of out-of-step oscillation. After years of development, it has achieved certain amount of research results. Have the existing methods been able to meet the requirements of out-of-step splitting? What improvements are needed? Under this background, this review is written. It combs the development of out-of-step splitting control technologies and analyzes the technical routes and characteristics of different methods. It points out the contradiction between rapidity and optimality is the biggest technical problem, existing in both the traditional local measurement based out-of-step splitting protection and the wide-area information based out-of-step splitting protection. It further points out that the advantages of the two types of protections can be combined with the unique physical characteristics of the out-of-step center to form a more advantageous splitting strategy. Besides, facing the fact of large-scale renewable energy access to power grid in recent years, this review also analyzes the challenges brought by it and provides some corresponding suggestions. It is hoped to provide some guidance for the subsequent research work.

Three-Dimensional Simulations of RESET Operation in Phase-Change Random Access Memory with Blade-Type Like Phase Change Layer by Finite Element Modeling

An optimized device structure for reducing the RESET current of phase-change random access memory （PCRAM） with blade-type like （BTL） phase change layer is proposed. The electrical thermal analysis of the BTL cell and the blade heater contactor structure by three-dimensional finite element modeling are compared with each other during RESET operation. The simulation results show that the programming region of the phase change layer in the BTL cell is much smaller, and thermal electrical distributions of the BTL cell are more concentrated on the TiN/GST interface. The results indicate that the BTL cell has the superiorities of increasing the heating efficiency, decreasing the power consumption and reducing the RESET current from 0.67mA to 0.32mA. Therefore, the BTL cell will be appropriate for high performance PCRAM device with lower power consumption and lower RESET current.

Catalyzing Random Access at Physical Layer for Internet of Things:An Intelligence Enabled User Signature Code Acquisition Approach

Exploiting random access for the underlying connectivity provisioning has great potential to incorporate massive machine-type communication(MTC)devices in an Internet of Things(Io T)network.However,massive access attempts from versatile MTC devices may bring congestion to the IIo T network,thereby hindering service increasing of IIo T applications.In this paper,an intelligence enabled physical(PHY-)layer user signature code acquisition(USCA)algorithm is proposed to overcome the random access congestion problem with reduced signaling and control overhead.In the proposed scheme,the detector aims at approximating the optimal observation on both active user detection and user data reception by iteratively learning and predicting the convergence of the user signature codes that are in active.The crossentropy based low-complexity iterative updating rule is present to guarantee that the proposed USCA algorithm is computational feasible.A closed-form bit error rate(BER)performance analysis is carried out to show the efficiency of the proposed intelligence USCA algorithm.Simulation results confirm that the proposed USCA algorithm provides an inherent tradeoff between performance and complexity and allows the detector achieves an approximate optimal performance with a reasonable computational complexity.

Thermal stability and data retention of resistive random access memory with HfOx/ZnO double layers

As an industry accepted storage scheme, hafnium oxide（HfO_x） based resistive random access memory（RRAM）should further improve its thermal stability and data retention for practical applications. We therefore fabricated RRAMs with HfO_x/ZnO double-layer as the storage medium to study their thermal stability as well as data retention. The HfO_x/ZnO double-layer is capable of reversible bipolar switching under ultralow switching current（〈 3 μA） with a Schottky emission dominant conduction for the high resistance state and a Poole–Frenkel emission governed conduction for the low resistance state. Compared with a drastically increased switching current at 120℃ for the single HfO_x layer RRAM, the HfO_x/ZnO double-layer exhibits excellent thermal stability and maintains neglectful fluctuations in switching current at high temperatures（up to 180℃）, which might be attributed to the increased Schottky barrier height to suppress current at high temperatures. Additionally, the HfO_x/ZnO double-layer exhibits 10-year data retention @85℃ that is helpful for the practical applications in RRAMs.

Construction of a reusable data access layer based on .NET

A new design solution of data access layer for N-tier architecture is presented. It can solve the problems such as low efficiency of development and difficulties in transplantation, update and reuse. The solution utilizes the reflection technology of .NET and design pattern. A typical application of the solution demonstrates that the new solution of data access layer performs better than the current N-tier architecture. More importantly, the application suggests that the new solution of data access layer can be reused effectively.

Hybrid Deep Learning-Based Adaptive Multiple Access Schemes Underwater Wireless Networks

Achieving sound communication systems in Under Water Acoustic(UWA)environment remains challenging for researchers.The communication scheme is complex since these acoustic channels exhibit uneven characteristics such as long propagation delay and irregular Doppler shifts.The development of machine and deep learning algorithms has reduced the burden of achieving reli-able and good communication schemes in the underwater acoustic environment.This paper proposes a novel intelligent selection method between the different modulation schemes such as Code Division Multiple Access(CDMA),Time Divi-sion Multiple Access(TDMA),and Orthogonal Frequency Division Multiplexing(OFDM)techniques using the hybrid combination of the convolutional neural net-works(CNN)and ensemble single feedforward layers(SFL).The convolutional neural networks are used for channel feature extraction,and boosted ensembled feedforward layers are used for modulation selection based on the CNN outputs.The extensive experimentation is carried out and compared with other hybrid learning models and conventional methods.Simulation results demonstrate that the performance of the proposed hybrid learning model has achieved nearly 98%accuracy and a 30%increase in BER performance which outperformed the other learning models in achieving the communication schemes under dynamic underwater environments.

Research on Physical Layer Security in Cognitive Wireless Networks with Multiple Eavesdroppers Based on Resource Allocation Algorithm

With the rapid development of the Internet of Things (IoT), non-Orthogonal Multiple Access (NOMA) technology and cognitive wireless network are two promising technologies to improve the spectral efficiency of the system, which have been widely concerned in the field of wireless communication. However, due to the importance of ownership and privacy protection, the IoT system must provide corresponding security mechanisms. From the perspective of improving the transmission security of CR-NOMA system based on cognitive wireless network, and considering the shortcomings of traditional relay cooperative NOMA system, this paper mainly analyzes the eavesdropping channel model of multi-user CR-NOMA system and derives the expressions of system security and rate to improve the security performance of CR-NOMA system. The basic idea of DC planning algorithm and the scheme of sub-carrier power allocation to improve the transmission security of the system were introduced. An algorithm for DC-CR-NOMA was proposed to maximize the SSR of the system and minimize the energy loss. The simulation results show that under the same complexity, the security and speed of the system can be greatly improved compared with the traditional scheme.

无人机辅助边缘计算安全通信能力最大化方案

针对无人机辅助移动边缘计算系统下用户信息容易泄露的问题,设计了一种基于非正交多址接入技术(Non-orthogonal Multiple Access,NOMA)的无人机辅助边缘计算系统的安全通信方案。在保证每个地面用户的最小安全计算要求下,通过联合优化信道系数、发射功率、中央处理单元计算频率、本地计算和无人机轨迹来最大化系统的平均安全计算能力。由于窃听者位置的不确定性、多变量的耦合以及问题的非凸性,利用逐次凸逼近和块坐标下降方法来解决该问题。仿真结果表明,与基准方案相比,所提方案在系统安全计算性能方面优于基准方案。

全双工主动窃听非正交多址接入系统智能超表面辅助物理层安全传输技术

针对全双工被动窃听和主动干扰攻击下的多用户非正交多址接入(NOMA)系统,该文提出一种智能超表面(RIS)辅助的鲁棒波束赋形方案以实现物理层安全通信。考虑在仅已知窃听者统计信道状态信息的条件下,以系统传输中断概率和保密中断概率作为约束,通过联合优化基站发射波束赋形、RIS相移矩阵、传输速率和冗余速率,来最大化系统的保密速率。为解决上述多变量耦合非凸优化问题,提出一种有效的交替优化算法得到联合优化问题的次优解。仿真结果表明,所提方案可实现较高的保密速率,且通过增加RIS反射单元数,系统保密性能更佳。

基于可达性的多层动态航空网络鲁棒性分析

为更准确地描述航空网络以分析其鲁棒性,提出1种以同一始发机场及其离场航班为子网络层,随出发时刻动态变化的多层动态航空网络模型。针对我国国内(不含港澳台)多层动态航空网络,以可达性、度中心性和加权介数中心性为节点特征指标,网络效率为网络性能测度指标,从随机攻击和蓄意攻击2种策略下对网络进行鲁棒性分析。研究结果表明:我国国内(不含港澳台)航空网络的鲁棒性主要由20%的机场提供,且在不同时间段内鲁棒性不同,在2023年夏秋航季,7∶00~20∶00间鲁棒性较好,4∶00~7∶00和20∶00~24∶00鲁棒性较差;用可达性指标衡量航空网络中机场节点的重要程度比度中心性和加权介数中心性指标更准确。研究结果可为保障航空运输网络安全提供一定参考。

基于混合协作NOMA的安全MEC能耗优化

非正交多址接入(non-orthogonal multiple access,NOMA)技术的广泛应用改变了传统物理层安全对用户传输速率的限制,在降低时延的同时会引起系统能耗增加。针对安全通信与降低能耗问题,提出一种基于混合协作NOMA的安全边缘计算传输方法。该方法对每个用户数据处理过程设计了多时隙混合协作方案,根据不同用户的信道条件分别设置卸载决策,保证用户间公平,并推导出系统保密中断概率的闭合表达式。然后以最小化系统能耗为目标,采用基于块坐标下降的三步迭代优化算法求得最优卸载方案。仿真结果显示,所提出的传输方法能在保证信息安全的条件下有效地减少系统能耗。

STAR-RIS辅助的NOMA系统物理层安全性能优化

针对实际通信场景中非理想信道状态信息以及非理想串行干扰删除等非理想因素的强耦合特性使可同时反射和透射的可重构智能超表面(STAR-RIS)辅助的非正交多址接入(NOMA)传输系统安全性能无法准确衡量的问题,提出了基于惩罚对偶分解(PDD)和块坐标下降(BCD)的融合算法,联合优化基站的波束成形矢量和STAR-RIS相移系数,实现系统最低安全传输速率的最大化。结果表明,所提融合算法相比BCD算法可以明显增加最低安全传输速率,性能至少提升10%。

基于MEC服务器优先服务的路侧单元MAC层调度策略

针对多接入边缘计算(MEC)服务器高可靠、低时延和大数据量的数据传输要求,基于无冲突接入、优先级架构和弹性服务技术,提出一种适用于车辆边缘计算场景下的媒体访问控制(MAC)调度策略。所提策略由车联网(IoV)路侧单元(RSU)集中协调信道接入权,优先确保车载网络中车载通信单元(OBU)与MEC服务器之间的链路传输质量,以及时传输车辆到网络(V2N)业务数据;同时,对本地OBU之间的业务采取弹性服务方式,增强密集车辆接入时应急消息传输的可靠性。首先,构建调度策略的排队分析模型;其次,根据各时刻系统状态变量的无后效性特点建立嵌入式马尔可夫链,并通过概率母函数的分析方法对系统进行理论分析,得到MEC服务器通信单元和OBU的平均排队队长、平均等待时延和RSU查询周期等关键指标的精确解析表达式。计算机仿真实验结果表明,统计分析结果与理论计算结果一致,所提调度策略在高负载情况下能够提高IoV的稳定性和灵活性。

基于双层网络频率控制的分布式风电并网研究

为研究含通信控制层的双层电网中分布式风电入网位置的选择,电网层采用二阶类Kuramoto模型进行建模,通信控制层收集发电机及其邻居节点信息形成控制信号并调整发电机的频率。根据负荷到原电网发电机节点的平均距离定义了3种并网方式,研究比较了含功率波动的分布式风电并网时最佳的入网位置。研究表明,加入双层网络频率控制可有效提高电网的同步性能和抗扰能力;分布式风电选择离原电网发电机节点平均距离小的负荷并网可提高电网稳定性。

中继选择NOMA无线系统的物理层安全

针对解码转发协作非正交多址接入(non-orthogonal multiple access,NOMA)系统物理层安全(physical layer security,PLS)性能较差,以及在多窃听者场景下PLS性能恶化的问题,提出了一种采用修改转发(modify-and-forward,MF)协议的多中继选择NOMA无线系统PLS模型。利用高斯-切比雪夫正交定理推导了非合谋或合谋窃听场景下多中继选择MF-NOMA无线系统的安全中断概率和渐近安全中断概率的近似表达式。仿真结果验证了多中继选择MF-NOMA无线系统PLS性能分析的准确性。结果同时也表明中继数目越多或窃听者数目越少,多中继选择MF-NOMA无线系统的PLS性能越好;合谋窃听比非合谋窃听更不利于多中继MF-NOMA无线系统的安全传输。

硬件损伤下多窃听器NOMA系统平均保密容量分析

研究了非正交多址(Non‑orthogonal‑multiple‑access,NOMA)接入通信系统的物理层安全性能。当基站采用下行NOMA方案发送信息时,由于信道的开放性,信息容易被窃听,而当存在多个随机分布的窃听者时,安全性能会进一步降低。为了增强存在硬件损伤系统的物理层安全性能,本文考虑保护区的方法,针对地面用户与基站之间存在直连链路的情况,采用莱斯衰落来建模小尺度衰落。本文还假设多个窃听者的位置遵循齐次泊松点过程(Homogeneous Poisson point process,HPPP),借助高斯切比雪夫积分公式,推导了平均保密容量的闭式表达式,并给出了在高信噪比情况下的渐近表达式来获得进一步见解。仿真结果验证了保护区方法在增强安全性能方面的有效性,并说明了不同参数对系统保密性能的影响。

基于DF-NOMA辅助的PLC系统安全性能分析

为了探求影响电力通信系统数据安全传输的关键因素,构建基于解码转发(decode-and-forward,DF)中继和非正交多址接入(non-orthogonal multiple access,NOMA)技术辅助的电力线通信(power line communication,PLC)系统,并研究其安全传输性能.针对外部窃听和内部窃听两种情况,联合考虑背景噪声和脉冲噪声的影响,分析系统的可达速率、遍历安全速率和安全中断概率等性能,并利用高斯-切比雪夫求积方法获得其相应的闭合表达式.结果表明:较高的脉冲噪声会降低系统的频谱效率和安全传输性能;功率分配系数以及源用户到中继用户的距离均对系统安全传输产生显著影响.进一步地,通过蒙特卡罗仿真实验验证了理论分析的正确性.