An Overview of Key Technologies in Physical Layer Security

The open nature of radio propagation enables ubiquitous wireless communication. This allows for seamless data transmission. However, unauthorized users may pose a threat to the security of the data being transmitted to authorized users. This gives rise to network vulnerabilities such as hacking, eavesdropping, and jamming of the transmitted information. Physical layer security (PLS) has been identified as one of the promising security approaches to safeguard the transmission from eavesdroppers in a wireless network. It is an alternative to the computationally demanding and complex cryptographic algorithms and techniques. PLS has continually received exponential research interest owing to the possibility of exploiting the characteristics of the wireless channel. One of the main characteristics includes the random nature of the transmission channel. The aforesaid nature makes it possible for confidential and authentic signal transmission between the sender and the receiver in the physical layer. We start by introducing the basic theories of PLS, including the wiretap channel, information-theoretic security, and a brief discussion of the cryptography security technique. Furthermore, an overview of multiple-input multiple-output (MIMO) communication is provided. The main focus of our review is based on the existing key-less PLS optimization techniques, their limitations, and challenges. The paper also looks into the promising key research areas in addressing these shortfalls. Lastly, a comprehensive overview of some of the recent PLS research in 5G and 6G technologies of wireless communication networks is provided.     

On the transfer matrix of a MIMO system

We develop a deterministic ab initio model for the input–output relationship of a multiple‐input multiple‐output (MIMO) wireless channel, starting from the Maxwell equations combined with Ohm's law. The main technical tools are scattering and geometric perturbation theories. The derived relationship can lead us to a deep understanding of how the propagation conditions and the coupling effects between the elements of multiple‐element arrays affect the properties of an MIMO channel, e.g. its capacity and its number of degrees of freedom. Copyright © 2011 John Wiley & Sons, Ltd.     

无线通信系统设计中的两个优化问题和相关优化方法

无线通信系统设计中的许多问题可建模为优化问题.一方面,这些优化问题常常具有高度的非线性性,一般情况下难于求解;另一方面,它们又有自身的特殊结构,例如隐含的凸性、可分性等.利用优化的方法结合问题的特殊结构求解和处理无线通信系统设计问题是近年来学术界研究的热点.本文重点讨论无线通信系统设计中的两个优化问题和相关优化方法,包括多用户干扰信道最大最小准则下的联合传输/接收波束成形设计和多输入多输出(Multi-Input Multi-Output,MIMO)检测问题,主要介绍现代优化技术结合问题的特殊结构在求解和处理上述两个问题的最新进展.     

阵不变量匹配主动声呐目标深度辨识

水面/水下目标深度辨识可以在主动声呐探测过程中快速筛选感兴趣目标。根据目标多径返回信号到达时间与目标深度的关联性,该文提出了基于水平线阵的主动脉冲响应匹配目标深度辨识方法,该方法利用主动信号传播特性结合阵不变量理论提取脉冲响应,并与拷贝声场匹配实现目标深度估计。在校正了目标多径回波的方位变化后,该方法提取的时域特征较为稳定,并且只在时延估计距离处进行深度搜索。通过水平阵收集的宽带实验数据,在连续的多次回波中实现了对水面/水下目标92%的辨识成功率,验证了该方法在浅海环境下的目标深度估计能力。     

Rate analysis of ZF receiver for uplink cell-free massive MIMO systems with D2D communications

This paper proposes a transmission structure of zero forcing (ZF) receiver for uplink cell-free massive multiple-input multiple-output (MIMO) systems with device-to-device (D2D) communications, followed by a rate analysis. We assumed that D2D users (DUEs) can utilize orthogonal radio resources to improve the efficiency of the scarce utilization or repurpose the time–frequency-spectrum resources currently used by the cell-free users (CFUEs). Assuming that the imperfect channel state information (CSI) is realizable, after that, the use-and-forget bounding technique is then used to respectively obtain the closed-form expressions of the CFUEs and DUEs, which provide the lower bounds on the ergodic approximate realizable rate of both communication links. First, we calculate the minimum-mean-square error (MMSE) estimation for all channels. Then, the derived results of the achievable uplink sum rate provide us with a tool that enables us to explain how some important parameters, such as the number of access points (APs)/CFUEs, each AP/CFUE/antenna, and the density of DUEs, affect system performance, highlighting the significance of cooperation between cell-free massive MIMO and D2D communication.     

Secrecy energy efficiency optimization for multiuser massive MIMO wiretap systems with transmit antenna selection

Massive multiple-input-multiple-output (Massive MIMO) significantly improves the capacity of wireless communication systems. However, large-scale antennas bring high hardware costs, and security is a vital issue in Massive MIMO networks. To deal with the above problems, antenna selection (AS) and artificial noise (AN) are introduced to reduce energy consumption and improve system security performance, respectively. In this paper, we optimize secrecy energy efficiency (SEE) in a downlink multi-user multi-antenna scenario, where a multi-antenna eavesdropper attempts to eavesdrop the information from the base station (BS) to the multi-antenna legitimate receivers. An optimization problem is formulated to maximize the SEE by jointly optimizing the transmit beamforming vectors, the artificial noise vector and the antenna selection matrix at the BS. The formulated problem is a nonconvex mixed integer fractional programming problem. To solve the problem, a successive convex approximation (SCA)-based joint antenna selection and artificial noise (JASAN) algorithm is proposed. After a series of relaxation and equivalent transformations, the nonconvex problem is approximated to a convex problem, and the solution is obtained after several iterations. Simulation results show that the proposed algorithm has good convergence behavior, and the joint optimization of antenna selection and artificial noise can effectively improve the SEE while ensuring the achievable secrecy rate.     

一种实用的使用铁磁材料匀场的开放式超导MRI磁体的优化方法(英文)

磁共振成像(MRI)系统是一种重要的医学诊断设备。作者提出了一种针对使用铁磁材料匀场的开放式超导MRI主磁场匀场的优化方法。在这种方法中,为了使这种包含非线性铁磁轭结构的MRI磁体产生高均匀度的磁场,集成了改进的多输入多输出负反馈控制理论和有限元方法,来计算匀场区非线性铁磁材料的形状。特别要指出的是,这种方法对初始值的要求不高,一定可以收敛,如果配置得当,可以快速收敛。另外,由于收敛速度快,这种方法也可以应用于大型的非轴对称三维模型优化分析。在文中,作者在一个二维轴对称磁体模型上测试了该方法,表现良好。     

Sum rates for multi-user MIMO vector perturbation precoding with regularization

In this paper, we analyze the sum rate performance of multiuser multi-antenna downlink channel. We consider Rayleigh fading environment when regularized vector perturbation precoding (R-VPP) method is used at the transmitter. We derive expressions for the sum rate in terms of the variance of the received signal. We also provide a closed form approximation for the mean squared error (MSE) which is shown to work well for the whole range of SNR. Further, we also propose a simpler expression for R-VPP sum rate based on MSE. The simulation results show that the proposed expressions for R-VPP sum rate closely match the sum rate found by the entropy estimation. Our results show that when compared with other linear and non-linear precoding methods (like zero-forcing precoder, linear minimum mean square error (MMSE) precoder and VPP), R-VPP sum rate performance is very close to DPC for all SNR values. It is also noted that the sum rate performance of the linear MMSE precoder is very close to the R-VPP at low to medium SNR range. Finally we also compared the merits of performing regularization for VPP as compared to the greedy rate maximizing user scheduling. It turns out that the R-VPP with or without user selection performs better than the VPP systems with user selection.     

温跃层及其变化对被动声纳检测概率的影响

根据被动声纳工作原理,构建被动声纳探测水下目标物概率数学模型。利用声学调查实测数据,综合考虑传播损失、环境噪声、和水文环境分布及季节变化,研究温跃层垂直分布及季节变化对声纳检测概率的影响。结果表明:温跃层对被动声纳影响巨大,逆温跃层环境中,声纳检测概率从海表向下逐渐减小;正温跃层对声纳总的影响与逆温跃层相反,在正温跃层上界,检测概率从表层向下先减小后增大;逆温跃层对被动声纳检测概率的影响随目标物与声纳距离的增大而增大,正温跃层影响相反。     

Decision-directed Kalman particle filter with application to the MIMO phase noise channel

Demodulation of data transmitted over time-varying channels with a free running hidden Markov state, like the phase noise channel or the fading channel, requires that the receiver tracks the hidden channel state. The tracking technique adopted in the paper is based on non-data-aided sequential importance sampling, also known as particle filtering.The paper proposes a new particle filtering framework for data communication receivers based on an importance distribution such that each individual particle becomes a decision-directed Kalman filter relying upon its local symbol-by-symbol hard decisions. In this framework, different particles are left free to take different sequences of decisions. This leaves to the receiver the possibility of exploring different sequences of transmitted modulation symbols. The weight of the particle will be high for those particles that took in the past the correct sequence of decisions, while will be low for those particles that took wrong decisions. In the resampling procedure, particles with high weight will survive, while particles with low weight will be terminated, leaving space to the birth of new particles resampled from the surviving ones.The crucial point in importance sampling is the choice of the importance distribution and the main novelty of the paper is the proposal of an importance distribution such that the particles of the particle filter become decision-directed Kalman filters. One important benefit brought by our proposed method is that, being non-data-aided, it does not need pilot symbols, thus allowing to preserve the transmission rate. A significant application example, presented and developed in the paper, is constituted by MIMO systems affected by phase noise, where the channel state vector consists of many parameters.