无线携能通信下mmWave协作通信小单元的能效最优策略

针对无线携能通信(SWIPT)网络中的能量与信息同时传输阶段的优化问题,以最大化链路能量效率为目标,提出一种SWIPT下mmWave协作通信小单元的能效最优策略。该策略在最小链路传输速率和最小收集能量的联合约束下,在能量受限型用户设备的接收端采用功率分流工作模式,通过优化发射功率控制和功率分流因子,最大化系统链路能量效率。针对原问题是一个非凸的分式规划问题,具有NP难性质,采用Dinkelbach方法将目标函数转化为易于求解的凸优化问题,并设计一个交叉迭代的算法求出最优解。仿真实验结果表明,提出的策略在优化系统能量效率性能上要优于传统功率控制方法和最大发射功率法。

Optimization-based mode selection scheme for OAM millimeter wave system in the off-axis misalignment case

Millimeter-wave transmission combined with Orbital Angular Momentum(OAM)has the advantage of reducing the loss of beam power and increasing the system capacity.However,to fulfill this advantage,the antennas at the transmitter and receiver must be parallel and coaxial;otherwise,the accuracy of mode detection at the receiver can be seriously influenced.In this paper,we design an OAM millimeter-wave communication system for overcoming the above limitation.Specifically,the first contribution is that the power distribution between different OAM modes and the capacity of the system with different mode sets are analytically derived for performance analysis.The second contribution lies in that a novel mode selection scheme is proposed to reduce the total interference between different modes.Numerical results show that system performance is less affected by the offset when the mode set with smaller modes or larger intervals is selected.

Artificial Intelligence Based Multi-Scenario mmWave Channel Modeling for Intelligent High-Speed Train Communications

A large amount of mobile data from growing high-speed train(HST)users makes intelligent HST communications enter the era of big data.The corresponding artificial intelligence(AI)based HST channel modeling becomes a trend.This paper provides AI based channel characteristic prediction and scenario classification model for millimeter wave(mmWave)HST communications.Firstly,the ray tracing method verified by measurement data is applied to reconstruct four representative HST scenarios.By setting the positions of transmitter(Tx),receiver(Rx),and other parameters,the multi-scenarios wireless channel big data is acquired.Then,based on the obtained channel database,radial basis function neural network(RBF-NN)and back propagation neural network(BP-NN)are trained for channel characteristic prediction and scenario classification.Finally,the channel characteristic prediction and scenario classification capabilities of the network are evaluated by calculating the root mean square error(RMSE).The results show that RBF-NN can generally achieve better performance than BP-NN,and is more applicable to prediction of HST scenarios.

Modeling and Performance Analysis of UAV-Aided Millimeter Wave Cellular Networks with Stochastic Geometry

UAV-aided cellular networks,millimeter wave(mm-wave) communications and multi-antenna techniques are viewed as promising components of the solution for beyond-5G(B5G) and even 6G communications.By leveraging the power of stochastic geometry,this paper aims at providing an effective framework for modeling and analyzing a UAV-aided heterogeneous cellular network,where the terrestrial base stations(TBSs) and the UAV base stations(UBSs) coexist,and the UBSs are provided with mm-wave and multi-antenna techniques.By modeling the TBSs as a PPP and the UBSs as a Matern hard-core point process of type Ⅱ(MPH-Ⅱ),approximated but accurate analytical results for the average rate of the typical user of both tiers are derived through an approximation method based on the mean interference-to-signal ratio(MISR) gain.The influence of some relevant parameters is discussed in detail,and some insights into the network deployment and optimization are revealed.Numerical results show that some trade-offs are worthy of being considered,such as the antenna array size,the altitude of the UAVs and the power control factor of the UBSs.

Low Complexity Hybrid Wideband Beamforming for Millimeter-Wave Massive MIMO-OFDM Systems

In mmWave massive multiple-input multiple-output(MIMO)communication systems,the extension of low-complexity narrowband precoding schemes to be operated on wideband systems under frequency-selective channels remains an important challenge at the current time.This paper investigates a low complexity wideband hybrid precoding scheme for mmWave massive MIMO multicarrier systems under a single-user,fully-connected hybrid architecture.We show that the radio frequency(RF)precoding/combining vectors can be directly derived from the eigenvectors of the optimal fully-digital covariance matrix over all subcarriers in order to maximize the sum rate of spectral efficiency.We also suggest a new method that iteratively reduces the residual error between the covariance matrix and the sum of products of precoding matrices over all the subcarriers to improve the performance in the case where the number of RF chains is higher than the number of streams.The results of the simulation show that the proposed schemes’complexity is low compared to the present methods,and their performance can almost reach the upper bound achieved by the optimal full-baseband design.

Gaussian Mixture-Learned Approximate Message Passing(GM-LAMP)Based Hybrid Precoders for mmWave Massive MIMO Systems

Hybrid precoder design is a key technique providing better antenna gain and reduced hardware complexity in millimeter-wave(mmWave)massive multiple-input multiple-output(MIMO)systems.In this paper,Gaussian Mixture learned approximate message passing(GM-LAMP)network is presented for the design of optimal hybrid precoders suitable for mmWave Massive MIMO systems.Optimal hybrid precoder designs using a compressive sensing scheme such as orthogonal matching pursuit(OMP)and its derivatives results in high computational complexity when the dimensionality of the sparse signal is high.This drawback can be addressed using classical iterative algorithms such as approximate message passing(AMP),which has comparatively low computational complexity.The drawbacks of AMP algorithm are fixed shrinkage parameter and non-consideration of prior distribution of the hybrid precoders.In this paper,the fixed shrinkage parameter problem of the AMP algorithm is addressed using learned AMP(LAMP)network,and is further enhanced as GMLAMP network using the concept of Gaussian Mixture distribution of the hybrid precoders.The simula-tion results show that the proposed GM-LAMP network achieves optimal hybrid precoder design with enhanced achievable rates,better accuracy and low computational complexity compared to the existing algorithms.

Off-Grid Compressed Channel Estimation with Parallel Interference Cancellation for Millimeter Wave Massive MIMO

Millimeter wave(mmWave)massive multiple-input multiple-output(MIMO)plays an important role in the fifth-generation(5G)mobile communications and beyond wireless communication systems owing to its potential of high capacity.However,channel estimation has become very challenging due to the use of massive MIMO antenna array.Fortunately,the mmWave channel has strong sparsity in the spatial angle domain,and the compressed sensing technology can be used to convert the original channel matrix into the sparse matrix of discrete angle grid.Thus the high-dimensional channel matrix estimation is transformed into a sparse recovery problem with greatly reduced computational complexity.However,the path angle in the actual scene appears randomly and is unlikely to be completely located on the quantization angle grid,thus leading to the problem of power leakage.Moreover,multiple paths with the random distribution of angles will bring about serious interpath interference and further deteriorate the performance of channel estimation.To address these off-grid issues,we propose a parallel interference cancellation assisted multi-grid matching pursuit(PIC-MGMP)algorithm in this paper.The proposed algorithm consists of three stages,including coarse estimation,refined estimation,and inter-path cyclic iterative inter-ference cancellation.More specifically,the angular resolution can be improved by locally refining the grid to reduce power leakage,while the inter-path interference is eliminated by parallel interference cancellation(PIC),and the two together improve the estimation accuracy.Simulation results show that compared with the traditional orthogonal matching pursuit(OMP)algorithm,the normalized mean square error(NMSE)of the proposed algorithm decreases by over 14dB in the case of 2 paths.

Hybrid millimeter wave heterogeneous networks with spatially correlated user equipment

In this paper,we analyze a hybrid Heterogeneous Cellular Network(HCNet)framework by deploying millimeter Wave(mmWave)small cells with coexisting traditional sub-6GHz macro cells to achieve improved coverage and high data rate.We consider randomly-deployed macro base stations throughout the network whereas mmWave Small Base Stations(SBSs)are deployed in the areas with high User Equipment(UE)density.Such user centric deployment of mmWave SBSs inevitably incurs correlation between UE and SBSs.For a realistic scenario where the UEs are distributed according to Poisson cluster process and directional beamforming with line-of-sight and non-line-of-sight transmissions is adopted for mmWave communication.By using tools from stochastic geometry,we develop an analytical framework to analyze various performance metrics in the downlink hybrid HCNets under biased received power association.For UE clustering we considered Thomas cluster process and derive expressions for the association probability,coverage probability,area spectral efficiency,and energy efficiency.We also provide Monte Carlo simulation results to validate the accuracy of the derived expressions.Furthermore,we analyze the impact of mmWave operating frequency,antenna gain,small cell biasing,and BSs density to get useful engineering insights into the performance of hybrid mmWave HCNets.Our results show that network performance is significantly improved by deploying millimeter wave SBS instead of microwave BS in hot spots.

A Compact Millimeter Wave Antenna Array with Defected Ground Structure for 5G Applications

The transition towards the fifth generation(5G)of communication systems has been fueled by the need for compact,high-speed and wide-bandwidth systems.These advancements necessitate the development of novel and highly efficient antenna designs characterized by the compact size.In this paper,a novel antenna design with a hexagonal-shaped resonating element and two U-shaped open-ended stubs is presented.Millimeter-wave(mmWave)frequency range suffers from attenuation due to atmosphere and path loss because of higher frequencies.To address these issues,the deployment of a high-gain antenna is imperative.This design is created through an evolutionary process to work best in the mmWave frequency range with a high gain.A thin Rogers RT5880 substrate with a thickness of 0.254 mm,a dielectric constant of 2.3 and a loss tangent of 0.0009 supports the copper-based radiating element.A partial ground plane with a square slot and trimmed corners at the bottom enhances the antenna’s bandwidth.The single-element antenna exhibits a wide bandwidth of nearly 6 GHz and a gain of 4.58 dBi.By employing the proposed antenna array,the antenna gain is significantly enhanced to 14.90 dBi while maintaining an ultra-compact size of 24 mm×46 mm at the resonant frequency of 31 GHz.The antenna demonstrates a wider impedance bandwidth of 15.73%(28-34 GHz)and an efficiency of 94%.The proposed design works well for 5G communication and satellite communication,because it has a simple planar structure and focused dual-beam radiation patterns from a simple feeding network.

Detection technique of moving target based on passive millimeter wave

To solve the problem of insufficient ability when detecting the high-speed moving target with passive millimeter wave technology, a direct-detection passive millimeter wave detecting system using the monolithic microwave integrated cir- cuit （MMIC） millimeter wave radiometer is built, and the measured data are obtained by experiment under different condi- tions. Based on feature analysis of testing signals, it points out that the peak of the first pulse and interval of two peak pulses are valid features which can reflect the motion characteristic of target. A method to calculate the moving speed of target is put forward. The calculating results indicate that the proposed method has enough accuracy and is feasible to determine the parameters of the moving target using for passive millimeter wave system.

Low Complexity Joint Hybrid Precoding for Millimeter Wave MIMO Systems

In millimeter wave(mmWave) multiple-input multiple-output(MIMO) systems, hybrid precoding has been widely used to overcome the severe propagation loss. In order to improve the spectrum efficiency with low complexity, we propose a joint hybrid precoding algorithm for single-user mmWave MIMO systems in this paper. By using the concept of equivalent channel, the proposed algorithm skillfully utilizes the idea of alternating optimization to complete the design of RF precoder and combiner. Then, the baseband precoder and combiner are computed by calculating the singular value decomposition of the equivalent channel. Simulation results demonstrate that the proposed algorithm can achieve satisfactory performance with quite low complexity. Moreover, we investigate the effects of quantization on the analog components and find that the proposed scheme is effective even with coarse quantization.

Radio Propagation and Wireless Coverage of LSAA-Based 5G Millimeter-Wave Mobile Communication Systems

Millimeter-wave(mm Wave) communications will be used in fifth-generation(5G) mobile communication systems, but they experience severe path loss and have high sensitivity to physical objects, leading to smaller cell radii and complicated network architectures. A coverage extension scheme using large-scale antenna arrays(LSAAs) has been suggested and theoretically proven to be cost-efficient in combination with ultradense small cell networks. To analyze and optimize the LSAA-based network deployments, a comprehensive survey of recent advances in statistical mmWave channel modeling is first presented in terms of channel parameter estimation, large-scale path loss models, and small-scale cluster models. Next, the measurement and modeling results at two 5G candidate mmWave bands(e.g., 28 GHz and 39 GHz) are reviewed and compared in several outdoor scenarios of interest, where the propagation characteristics make crucial contributions to wireless network designs. Finally, the coverage behaviors of systems employing a large number of antenna arrays are discussed, as well as some implications on future mmWave cellular network designs.

Hybrid Precoder and Combiner Design with Finite Resolution PSs for mmWave MIMO Systems

Hybrid precoding and combining have been considered as a promising technology, which can provide a compromise between hardware complexity and system performance in millimeter wave multiple-input multiple-output systems. However, most existing hybrid precoder and combiner designs generally assume that infinite resolution phase shifters(PSs) are used to produce the analog beamformers. In a practical scene, the design with accurate PSs can lead to high hardware cost and power consumption. In this paper, we investigate the hybrid precoder and combiner design with finite resolution PSs in millimeter wave systems. We employ alternate optimization as the main strategy to jointly design analog precoder and combiner. In addition, we propose a low complexity algorithm, where the analog beamformers are implemented only by finite resolution PSs to maximize spectral efficiency. Then, the digital precoder and combiner are designed based on the obtained analog beamformers to improve the spectral efficiency. Finally, simulation results and mathematical analysis show that the proposed algorithm with low-resolution PSs can achieve near-optimal performance and have low complexity.

Quantized Hybrid Precoding Design for Millimeter-Wave Large-Scale MIMO Systems

Millimeter wave(mmWave) and large-scale multiple input multiple output(MIMO) are two emerging technologies in fifth-generation wireless communication systems. The power consumption and hardware cost of radio frequency(RF) chains increase exponentially with the bit resolution of analog-to-digital converters(ADCs) and digital-to-analog converters(DACs). One promising solution is to employ few RF chains with low-bit ADCs and DACs. In this paper, we consider mmWave large-scale MIMO systems with low bits DACs and ADCs. Leveraging on the Bussgang theorem and the additive quantization noise model(AQNM), a closed-form expression of the achievable rate is derived to show the effect of the ADCs? and DACs? resolution. Moreover, an orthogonal matching pursuit(OMP) based hybrid precoding algorithm is proposed to increase the achievable rate. Our results show that the impact of DACs is more pronounced than the impact of ADCs. Furthermore, 5-bit ADCs and DACs are sufficient at the transceiver to operate without a significant performance loss.

Study on the Technique of Passive Millimeter Wave Detector

In order to initiate the flight immediately when it reaches the top of the pedrail vehicle, technical parameters of radiometer have been designed and speedy effective signal processing method has been adopted. After analyzing the difference of signal characteristic between the main jam and the target, a method of identifying target in time domain is given. The target distinguishing rules are set up by extracting the magnitude, the slope and the width of the signal, combining with distinguishing the dimension of the target. The result of the theoretic analysis shows that the detecting scheme adopted can ensure the detector to identify and orientate the pedrail vehi cle＇s top armour, as well as control the detonation precisely.

User Assisted Cooperative Relaying in Beamspace Massive MIMO NOMA Based Systems for Millimeter Wave Communications

A novel scheme‘user assisted cooperative relaying in beamspace massive multiple input multiple output(M-MIMO)non-orthogonal multiple access(NOMA)system’has been proposed to improve coverage area,spectrum and energy efficiency for millimeter wave(mmWave)communications.A downlink system for M users,where base station(BS)is equipped with beamforming lens antenna structure having NRF radio frequency(RF)chains,has been considered.A dynamic cluster of users is formed within a beam and the intermediate users(in that cluster)between beam source and destination(user)act as relaying stations.By the use of successive interference cancellation(SIC)technique of NOMA within a cluster,the relaying stations relay the symbols with improved power to the destination.For maximizing achievable sum rate,transmit precoding and dynamic power allocation for both intra and inter beam power optimization are implemented.Simulations for performance evaluation are carried out to validate that the proposed system outperforms the conventional beamspace M-MIMO NOMA system for mmWave communications in terms of spectrum and energy efficiency.

A Low Power,High Sensitivity SiGe HBT Static Frequency Divider up to 90 GHz for Millimeter-Wave Application

A layout and connection optimization for static frequency divider is presented. The layout optimization provides a new circle topology transistors placement and reasonable connection structure, which reduces the parasitic effectively and enables self-oscillation frequency enhancement. Besides, bandwidth enhancement techniques based on a center-tap capacitor in input balun design and inductive peaking in latch design are adopted to improve further high frequency performance with low power consumption. As a proof of concept, design of a divide-by-2 static frequency divider in 0.13 μm SiGe BiCMOS technology is reported. With single-ended input clock signal, the divider is measured to be operated from 40 to 90 GHz. Phase noise measurements of a 90 GHz input clock signal indicate ideal behavior with no measurable noise contribution from the divider. The divider followed by a buffer that can deliver more than-10 dBm output power, which is sufficient to drive succeeding stage. To the author's knowledge, the divider exhibits a competitive power dissipation and the highest FOM among silicon based frequency dividers that operating higher than 70 GHz.

面向RIS-mmWave系统的机器学习辅助高效波束训练及信道估计方法

面向B5G及6G无线通信系统的高速无线信息传输,本文研究了智能超表面辅助毫米波(RIS-mmWave)系统的高效能波束训练及信道估计方法。特别地,基于RIS-mmWave波束管理及有效信道获取的内生关联性,本文创新性地提出一种机器学习辅助的RIS-mmWave系统高效波束训练及信道估计方法。具体而言,在第一阶段,设计了一种新颖的半监督学习模型,实现位置信息辅助的在线快速波束训练,并且免估计地直接获取粗略角度域信息以驱动精细化信道估计;在第二阶段中,提出半监督学习辅助的压缩感知级联信道估计算法,利用半监督学习模型直接输出的粗略角度域信息驱动块正交匹配追踪算法进行信道估计。仿真结果表明,所提波束训练及信道估计方法在系统开销和信道估计误差等方面的性能均优于代表性参考方案。

Modeling Human Blockers in Millimeter Wave Radio Links

In this paper, we investigate the loss caused by multiple humans blocking millimeter wave frequencies. We model human blockers as absorbing screens of infinite height with two knife-edges, We take a physical optics approach to computing the diffraction around the absorbing screens, This approach differs to the geometric optics approach described in much of the literature. The blocking model is validated by measuring the gain from multiple-human blocking configurations on an indoor link. The blocking gains predicted using Piazzi ＇ s numerical integration method （a physical optics method） agree well with measurements taken from approximately 2.7 dB to -50 dB. Thereofre, this model is suitable for real human blockers, The mean prediction error for the method is approximately -1.2 dB, and the standard deviation is approximately 5 dB.

Multi-Task Deep Learning Based Hybrid Precoding for mmWave Massive MIMO System

Due to the different signal-to-noise ratio(SNR)of each subchannel,the bit error rate(BER)of hybrid precoding based on singular value decomposition(SVD)decreases.In this paper,we propose a multi-task learning based precoding network(PN)model to solve the BER loss problem caused by SVD based hybrid precoding under imperfect channel state information(CSI).Specifically,we firstly generate a dataset including imcomplete CSI input channel matrix and corresponding output labels to train the PN model.The output labels are designed based on uniform channel decomposition(UCD)which decomposes the channel into multiple subchannels with same gain,while the vertical-bell layered space-time structure(V-BLAST)signal processing technology is combined to eliminate the inner interference of the subchannels.Then,the PN model is trained to design the analog and digital precoding/combining matrix simultaneous.Simulation results show that the proposed scheme has only negligible gap in spectrum efficiency compared with the fully digital precoding,while achieves better BER performance than SVD based hybrid precoding.