A True-Time-Delay Array Architecture for Wideband Multi-Beam Tracking

The true-time delay(TTD)units are critical for solving beam squint and frequency selective fading inWideband Large-Scale Antenna Systems(LSASs).In this work,we propose a TTD array architecture for wideband multi-beam tracking that eliminates the beam squint phenomenon and filters out interference signals by applying a spatial filter and time delay estimations(TDEs).The paper presents a novel approach to spatial filter design by introducing a transformation matrix that can optimize the beam response in a specific direction and at a specific frequency.Using the variable fractional delay(VFD)filters,we propose a TDE algorithm with a Newton-Raphson iteration update process that corrects the arrival time delay difference between sensors.Simulations and examples have demonstrated that the proposed architecture can achieve beam tracking within 10 ms at the low signalto-noise ratio(SNR)and demodulation loss is less than 0.5 dB in wideband multi-beam scenarios.

Near-Field Beam Training for Holographic MIMO Communications: Typical Methods, Challenges and Future Directions

Holographic multiple-input multiple-output(HMIMO)has become an emerging technology for achieving ultra-high frequency spectral efficiency and spatial resolution in future wireless systems.The increasing antenna aperture leads to a more significant characterization of the spherical wavefront in near-field communications in HMIMO scenarios.Beam training as a key technique for wireless communication is worth exploring in this near-field scenario.Compared with the widely researched far-field beam training,the increased dimensionality of the search space for near-field beam training poses a challenge to the complexity and accuracy of the proposed algorithm.In this paper,we introduce several typical near-field beam training methods:exhaustive beam training,hierarchical beam training,and multi-beam training that includes equal interval multi-beam training and hash multi-beam training.The performances of these methods are compared through simulation analysis,and their effectiveness is verified on the hardware testbed as well.Additionally,we provide application scenarios,research challenges,and potential future research directions for near-field beam training.

Joint Optimization of Satisfaction Index and Spectrum Efficiency with Cache Restricted for Resource Allocation in Multi-Beam Satellite Systems

Dynamic resource allocation(DRA) is a key technology to improve system performances in GEO multi-beam satellite systems. And, since the cache resource on the satellite is very valuable and limited, DRA problem under restricted cache resources is also an important issue to be studied. This paper mainly investigates the DRA problem of carrier resources under certain cache constraints. What's more, with the aim to satisfy all users' traffic demands as more as possible, and to maximize the utilization of the bandwidth, we formulate a multi-objective optimization problem(MOP) where the satisfaction index and the spectrum efficiency are jointly optimized. A modified strategy SA-NSGAII which combines simulated annealing(SA) and non-dominated sorted genetic algorithm-II(NSGAII) is proposed to approximate the Pareto solution to this MOP problem. Simulation results show the effectiveness of the proposed algorithm in terms of satisfaction index, spectrum efficiency, occupied cache, and etc.

User-Level Scheduling and Resource Allocation for Multi-Beam Satellite Systems with Full Frequency Reuse

Multi-beam satellite communication systems can improve the resource utilization and system capacity effectively.However,the inter-beam interference,especially for the satellite system with full frequency reuse,will degrade the system performance greatly due to the characteristics of multi-beam satellite antennas.In this article,the user scheduling and resource allocation of a multi-beam satellite system with full frequency reuse are jointly studied,in which all beams can use the full bandwidth.With the strong inter-beam interference,we aim to minimize the system latency experienced by the users during the process of data downloading.To solve this problem,deep reinforcement learning is used to schedule users and allocate bandwidth and power resources to mitigate the inter-beam interference.The simulation results are compared with other reference algorithms to verify the effectiveness of the proposed algorithm.

Multiple sub-array beamspace CAATI algorithm for multi-beam bathymetry system

This paper extends CAATI （Computed Angle-of-Arrival Transient Imaging） technique of Multi-angle Swath Bathymetry Sidesean Sonar （MSBSS） into Multi-Beam Bathymetry Sonar （MBBS） and presents a new Multiple Sub-array Beamspaee - CAATI （MSB-CAATI） algorithm. The method not only can achieve high resolution seafloor mapping in the whole wide swath, but also can work well in complex acoustic environments or geometries. Simulation results and processing results of sea-experiment data prove the validity and superiority of the algorithm.

Multi-Objective Deep Reinforcement Learning Based Time-Frequency Resource Allocation for Multi-Beam Satellite Communications

Resource allocation is an important problem influencing the service quality of multi-beam satellite communications.In multi-beam satellite communications, the available frequency bandwidth is limited, users requirements vary rapidly, high service quality and joint allocation of multi-dimensional resources such as time and frequency are required. It is a difficult problem needs to be researched urgently for multi-beam satellite communications, how to obtain a higher comprehensive utilization rate of multidimensional resources, maximize the number of users and system throughput, and meet the demand of rapid allocation adapting dynamic changed the number of users under the condition of limited resources, with using an efficient and fast resource allocation algorithm.In order to solve the multi-dimensional resource allocation problem of multi-beam satellite communications, this paper establishes a multi-objective optimization model based on the maximum the number of users and system throughput joint optimization goal, and proposes a multi-objective deep reinforcement learning based time-frequency two-dimensional resource allocation(MODRL-TF) algorithm to adapt dynamic changed the number of users and the timeliness requirements. Simulation results show that the proposed algorithm could provide higher comprehensive utilization rate of multi-dimensional resources,and could achieve multi-objective joint optimization,and could obtain better timeliness than traditional heuristic algorithms, such as genetic algorithm(GA)and ant colony optimization algorithm(ACO).

Landslide data mosaicking based on an airborne laser point cloud and multi-beam sonar images

Landslides are one of the most disastrous geological hazards in southwestern China.Once a landslide becomes unstable,it threatens the lives and safety of local residents.However,empirical studies on landslides have predominantly focused on landslides that occur on land.To this end,we aim to investigate ashore and underwater landslide data synchronously.This study proposes an optimized mosaicking method for ashore and underwater landslide data.This method fuses an airborne laser point cloud with multi-beam depth sounder images.Owing to their relatively high efficiency and large coverage area,airborne laser measurement systems are suitable for emergency investigations of landslides.Based on the airborne laser point cloud,the traversal of the point with the lowest elevation value in the point set can be used to perform rapid extraction of the crude channel boundaries.Further meticulous extraction of the channel boundaries is then implemented using the probability mean value optimization method.In addition,synthesis of the integrated ashore and underwater landslide data angle is realized using the spatial guide line between the channel boundaries and the underwater multibeam sonar images.A landslide located on the right bank of the middle reaches of the Yalong River is selected as a case study to demonstrate that the proposed method has higher precision thantraditional methods.The experimental results show that the mosaicking method in this study can meet the basic needs of landslide modeling and provide a basis for qualitative and quantitative analysis and stability prediction of landslides.

Numerical investigation of multi-beam laser heterodyne measurement with ultra-precision for linear expansion coefficient of metal based on oscillating mirror modulation

This paper proposes a novel method of multi-beam laser heterodyne measurement for metal linear expansion coefficient. Based on the Doppler effect and heterodyne technology, the information is loaded of length variation to the frequency difference of the multi-beam laser heterodyne signal by the frequency modulation of the oscillating mirror, this method can obtain many values of length variation caused by temperature variation after the multi-beam laser heterodyne signal demodulation simultaneously. Processing these values by weighted-average, it can obtain length variation accurately, and eventually obtain the value of linear expansion coefficient of metal by the calculation. This novel method is used to simulate measurement for linear expansion coefficient of metal rod under different temperatures by MATLAB, the obtained result shows that the relative measurement error of this method is just 0.4%.

Handover initiation performance of a new multi-cell cellular configuration with a developed base-station multi-beam antenna

A new multi-cell cellular configuration networks is provided for analysis of handover initiation probability, which is based on multi-beam base-station antenna splitting in the elevation-radiating plane. The sum of the received signal power in the mobile station, including both desired and interference signal power, has been introduced into the handover initiation algorithm. Along with the idea, we present three models of handover initiation algorithm with the shadowing process of Gaussian distribution. The formulation of handover initiation probability of those algorithms is also analyzed. The validity of the presented models has been checked through the comparison with simulation results. The results present the performance characteristics of handover initiation vary with cluster number and base-station antenna elevation angle.

Impact of Phase Noise on TDMS Based Calibration for Spaceborne Multi-Beam Antennas

For spaceborne multi-beam antennas(MBAs), time division multiplexed switching(TDMS) based calibration receiver can reduce implementation costs effectively and is very suitable for large-scale applications. However, in practice, random phase noise imposed by noisy local oscillators can cause significant performance degradation in TDMS-based calibration systems. Characterization of phase noise effects is therefore crucial for practical applications. In this paper, we analyze the impact of phase noise on the calibration performance for a MBA system. Specifically, we derive the relationship between the probability of correct amplitude/phase estimation and various practical factors involving the signal-to-noise ratio(SNR), the standard deviation of phase noise, the given tolerance region, and the length of the spreading code. The results provide high efficiency for evaluating the calibration performance of the MBAs based on TDMS, especially for precisely anticipating the impact of phase noise. Finally, the accuracy of the derived results is assessed by simulations in different scenarios.

Low Complexity Multiuser Detection Algorithm for Multi-Beam Satellite Systems

The minimum mean square error-successive interference cancellation( MMSE-SIC) multiuser detection algorithm has high complexity and long processing latency. A multiuser detection algorithm is proposed for multi-beam satellite systems in order to decrease the complexity and latency. The spot beams are grouped base on the distance between them in the proposed algorithm. Some groups are detected in parallel after a crucial group-wise interference cancellation. Furthermore, the multi-stage structure is introduced to improve the performance. Simulation results show that the proposed algorithm can achieve better performance with less complexity compared with the existing group detection algorithm. Moreover,the proposed algorithm using one stage can reduce the complexity over the fast MMSE-SIC and existing group detection algorithm by 9% and20. 9%. The processing latency is reduced significantly compared with the MMSE-SIC.

A Quantitative Method for Active Fault Migration Distance Assessment on both Sides of Mid-Ocean Ridges——Based on Multi-Beam Data

Fracture-fissure systems found at mid-ocean ridges are dominating conduits for the circulation of metallogenic fluid.Ascertaining the distribution area of active faults on both sides of mid-ocean ridges will provide a useful tool in the search for potential hydrothermal vents,thus guiding the exploration of modern seafloor sulfides.Considering the MidAtlantic Ridge 20°N–24°N(NMAR)and North Chile Rise(NCR)as examples,fault elements such as Fault Spacing(?S)and Fault Heave(?X)can be identified and quantitatively measured.The methods used include Fourier filtering of the multi-beam bathymetry data,in combination with measurements of the topographic slope,curvature,and slope aspect patterns.According to the Sequential Faulting Model of mid-ocean ridges,the maximal migration distance of an active fault on either side of mid-ocean ridges—that is,the distribution range of active faults—can be measured.Results show that the maximal migration distance of active faults at the NMAR is 0.76–1.01 km(the distance is larger at the center than at the ends of this segment),and at the NCR,the distribution range of active faults is 0.38–1.6 km.The migration distance of active faults on the two study areas is positively related to the axial variation of magma supply.In the NCR study area,where there is an abundant magma input,the number of faults within a certain distance is mainly affected by the variation of lithospheric thickness.Here a large range of faulting clearly corresponds to a high proportion of magmatism to seafloor spreading near mid-ocean ridges(M)value,and in the study area of the NMAR,there is insufficient magmatism,and the number of faults may be controlled by both lithospheric thickness and magma supply,leading to a less obvious positive correlation between the distribution range of active faults and M.

Multi-beam Sonar and Side-scan Sonar Image Co-registering and Fusing

Multi-beam Sonar and Side-scan Sonar compensate each other. In order to fully utilize all information, it is necessary to fuse two kinds of image and data. And the image co-registration is an important and complicated job before fusion. This paper suggests combining bathymetric data with intensity image, obtaining the characteristic points through the minimal angles of lines, and then deciding the corresponding image points by the maximal correlate coefficient in searching space. Finally, the second order polynomial is applied to the deformation model. After the images have been co-registered, Wavelet is used to fuse the images. It is shown that this algorithm can be used in the flat seafloor or the isotropic seabed. Verification is made in the paper with the observed data.

Distortion of optical feedback signals in microchip Nd:YAG lasers subjected to external multi-beam interference feedback

This paper proposes a theoretical analysis for the characteristics of an external cavity Nd：YAG laser with feedback of multiple-beam interference, which is induced by the multi-reentrance of the light from the external Fabry-Perot cavity. The theoretical model considers the multiple beam interference of the external Fabry-Perot cavity. It is found that the optical feedback signals are distorted to pulse waveforms instead of the sinusoidal ones in conventional feedback. The experimental results are in good agreement with the theoretical analysis. The obtained theoretical and experimental results can advance the development of a laser feedback interferometer.

RECENT PROGRESS IN MULTI-BEAM KLYSTRON IN IECAS

Recent research progresses in Multi-Beam Klystron (MBK) in IECAS are briefly introduced in the letter. The S-band MBKs of IECAS have peak power of 120-250 kW, average power of 4-9 kW, efficiency of 35-45%, gain of 41-46 dB, beam voltage of 15-19 kV, and weight of 40-45 kg. Some key technical problems of MBK are also described and discussed. Among them,improving the design of MBK to obtain the required bandwidth, raising beam transmission to increase average power, eliminating oscillation and spray spectrum, overcoming window breakdown caused by magic mode, reducing breakdown times of electrongun, are most important things for the practical MBK. Besides, further research work in MBK in IECAS is commented.

Spatial Correlation Characteristics Analysis of Multi-Beam Channels of Mobile Satellite System

Due to the influence of scatterers around the receiving antenna, the multipath signal in satellite mobile communication systems is correlated with each other which would influence the system performance. There is no systematic standard on the channel modelling of the wideband satellite channel at present, so the study of the modelling of the wideband satellite channel is of great importance. In this paper, firstly we created a multi-beam model which can figure out the antenna gain of the nth component beam. Secondly, we combined the characteristics of multi-beam satellite channel and the distribution of the scatterers, and set up a three-dimension random channel model. This model is more realistic for satellite communication system since it considers the height of scatterers. According to the channel models, we had the formula of spatial correlation coefficient. We used the formula to calculate the relationship between spatial correlation coefficient and the interval of antennas. The result shows that the spatial correlation exists and cannot be ignored while modeling for mobile satellite system.

TE Connectivity全新MULTI-BEAM卡缘连接器

TE Connectivity(TE)推出全新MULTI-BEAM卡缘连接器,该产品可提供卓越的总体功率和信号密度以满足数据通信市场对性能、尺寸和成本的更高要求。与通用型产品相比,新一代电源卡缘连接器的密度提高了30%,具有更佳连接容限,从而实现更可靠连接。TE的独有设计具有模组化、可扩展的特点,支持配置和PCB设计的更高灵活性。此类产品是下一代卡缘连接器,可替代当前的SEC-II电源卡缘产品。

用于5G多波束MIMO系统的先进低温共烧陶瓷封装的39 GHz双信道收发器芯片组

本文介绍了一种用于5G多输入多输出(MIMO)应用的39 GHz收发器前端芯片组。每个芯片包括两个可变增益的频率转换通道,可以同时支持两个独立波束,芯片还集成了一个本地振荡器链和数字模块,用于多芯片扩展和增益状态控制。为了提高射频性能,对前端系统的关键模块提出了几种电路级改进技术。此外,开发了一种先进的低温共烧陶瓷工艺来封装39 GHz双通道收发器芯片组,实现了低封装损耗和两个发射(TX)/接收(RX)通道之间的高隔离。进行了芯片级和系统级封装(SIP)测量,以演示收发器芯片组的性能。测量结果表明,TX SIP的最大增益为11 dB,饱和输出功率为10 dBm;RX SIP的最大增益为52 dB,噪声系数为5.4 dB,输出压缩点为7.2 dBm。该收发器的单通道通信链路测试表明,64正交调幅(QAM)调制的误差矢量幅度(EVM)为3.72%,频谱效率为3.25 bit·s^(−1)·Hz^(−1);256-QAM调制在1 m距离上的误差矢量幅度(EVM)为3.76%,频谱效率为3.9 bit·s^(−1)·Hz^(−1)。基于该芯片组,还开发了39 GHz多波束原型,用于执行5G毫米波应用的MIMO操作。单流和双流传输的空中通信链路表明,多波束原型机可以覆盖5~150 m的距离,吞吐量相当。

Dual-band multi-beam reconfigurable terahertz antenna based on graphene frequency selective surface

In this paper,a dual-band graphene-based frequency selective surface(GFSS)is investigated and the operating mechanism of this GFSS is analyzed.By adjusting the bias voltage to control the graphene chemical po-tential between 0 eV and 0.5 eV,the GFSS can achieve four working states:dual-band passband,high-pass lowimpedance,low-pass high-impedance,and band-stop.Based on this GFSS,a hexagonal radome on a broadband omnidirectional monopole antenna is proposed,which can achieve independent 360°six-beam omnidirectional scanning at 1.08 THz and 1.58 THz dual bands.In addition,while increasing the directionality,the peak gains of the dual bands reach 7.44 dBi and 6.67 dBi,respectively.This work provides a simple method for realizing multi-band terahertz multi-beam reconfigurable antennas.

Demand-based dynamic bandwidth allocation in multi-beam satellites using machine learning concepts

In the realm of satellite communication,where the importance of efficient spectrum utilization is growing day by day due to the increasing significance of this technology,dynamic resource management has emerged as a pivotal consideration in the design of contemporary multi-beam satellites,facilitating the flexible allocation of resources based on user demand.This research paper delves into the pivotal role played by machine learning and artificial intelligence within the domain of satellite communication,particularly focusing on spot beam satellites.The study encompasses an evaluation of machine learning’s application,whereby an extensive dataset capturing user demand across a specific geographical area is subjected to analysis.This analysis involves determining the optimal number of beams/clusters,achieved through the utilization of the knee-elbow method predicated on within-cluster sum of squares.Subsequently,the demand data are equitably segmented employing the weighted k-means clustering technique.The proposed solution introduces a straightforward yet efficient model for bandwidth allocation,contrasting with conventional fixed beam illumination models.This approach not only enhances spectrum utilization but also leads to noteworthy power savings,thereby addressing the growing importance of efficient resource management in satellite communication.