Semi-supervised learning based hybrid beamforming under time-varying propagation environments

Hybrid precoding is considered as a promising low-cost technique for millimeter wave(mm-wave)massive Multi-Input Multi-Output(MIMO)systems.In this work,referring to the time-varying propagation circumstances,with semi-supervised Incremental Learning(IL),we propose an online hybrid beamforming scheme.Firstly,given the constraint of constant modulus on analog beamformer and combiner,we propose a new broadnetwork-based structure for the design model of hybrid beamforming.Compared with the existing network structure,the proposed network structure can achieve better transmission performance and lower complexity.Moreover,to enhance the efficiency of IL further,by combining the semi-supervised graph with IL,we propose a hybrid beamforming scheme based on chunk-by-chunk semi-supervised learning,where only few transmissions are required to calculate the label and all other unlabelled transmissions would also be put into a training data chunk.Unlike the existing single-by-single approach where transmissions during the model update are not taken into the consideration of model update,all transmissions,even the ones during the model update,would make contributions to model update in the proposed method.During the model update,the amount of unlabelled transmissions is very large and they also carry some information,the prediction performance can be enhanced to some extent by these unlabelled channel data.Simulation results demonstrate the spectral efficiency of the proposed method outperforms that of the existing single-by-single approach.Besides,we prove the general complexity of the proposed method is lower than that of the existing approach and give the condition under which its absolute complexity outperforms that of the existing approach.

Joint Active and Passive Beamforming Design for Hybrid RIS-Aided Integrated Sensing and Communication

Integrated sensing and communication(ISAC) is considered an effective technique to solve spectrum congestion in the future. In this paper, we consider a hybrid reconfigurable intelligent surface(RIS)-assisted downlink ISAC system that simultaneously serves multiple single-antenna communication users and senses multiple targets. Hybrid RIS differs from fully passive RIS in that it is composed of both active and passive elements, with the active elements having the effect of amplifying the signal in addition to phase-shifting. We maximize the achievable sum rate of communication users by collaboratively improving the beamforming matrix at the dual function base station(DFBS) and the phase-shifting matrix of the hybrid RIS, subject to the transmit power constraint at the DFBS, the signal-to-interference-plus-noise-ratio(SINR) constraint of the radar echo signal and the RIS constraint are satisfied at the same time. The builtin RIS-assisted ISAC design problem model is significantly non-convex due to the fractional objective function of this optimization problem and the coupling of the optimization variables in the objective function and constraints. As a result, we provide an effective alternating optimization approach based on fractional programming(FP) with block coordinate descent(BCD)to solve the optimization variables. Results from simulations show that the hybrid RIS-assisted ISAC system outperforms the other benchmark solutions.

A deep learning driven hybrid beamforming method for millimeter wave MIMO system

The hybrid beamforming is a promising technology for the millimeter wave MIMO system,which provides high spectrum efficiency,high data rate transmission,and a good balance between transmission performance and hardware complexity.The most existing beamforming systems transmit multiple streams by formulating multiple orthogonal beams.However,the Neural network Hybrid Beamforming(NHB)adopts a totally different strategy,which combines multiple streams into one and transmits by employing a high-order non-orthogonal modulation strategy.Driven by the Deep Learning(DL)hybrid beamforming,in this work,we propose a DL-driven nonorthogonal hybrid beamforming for the single-user multiple streams scenario.We first analyze the beamforming strategy of NHB and prove it with better Bit Error Rate(BER)performance than the orthogonal hybrid beamforming even with the optimal power allocation.Inspired by the NHB,we propose a new DL-driven beamforming scheme to simulate the NHB behavior,which avoids time-consuming neural network training and achieves better BERs than traditional hybrid beamforming.Moreover,our simulation results demonstrate that the DL-driven nonorthogonal beamforming outperforms its traditional orthogonal beamforming counterpart in the presence of subconnected schemes and imperfect Channel State Information(CSI).

Hybrid Architecture and Beamforming Optimization for Millimeter Wave Systems

Hybrid beamforming(HBF)has become an attractive and important technology in massive multiple-input multiple-output(MIMO)millimeter-wave(mmWave)systems.There are different hybrid architectures in HBF depending on different connection strategies of the phase shifter network between antennas and radio frequency chains.This paper investigates HBF optimization with different hybrid architectures in broadband point-to-point mmWave MIMO systems.The joint hybrid architecture and beamforming optimization problem is divided into two sub-problems.First,we transform the spectral efficiency maximization problem into an equivalent weighted mean squared error minimization problem,and propose an algorithm based on the manifold optimization method for the hybrid beamformer with a fixed hybrid architecture.The overlapped subarray architecture which balances well between hardware costs and system performance is investigated.We further propose an algorithm to dynamically partition antenna subarrays and combine it with the HBF optimization algorithm.Simulation results are presented to demonstrate the performance improvement of our proposed algorithms.

Energy-Efficient Large-Scale Antenna Systems with Hybrid Digital-Analog Beamforming Structure

A largescale antenna system （LSAS） with digital beamforming is expected to significantly increase energy efficiency （EE） and spectral efficiency （SE） in a wireless communication system. However, there are many challenging issues related to calibration, energy consumption, and cost in implementing a digital beamforming structure in an LSAS. In a practical LSAS deployment, hybrid digitalanalog beamforming structures with active antennas can be used. In this paper, we investigate the optimal antenna configuration in an N ＆#215; M beamforming structure, where N is the number of transceivers, M is the number of active antennas per transceiver, where analog beamforming is introduced for individual transceivers and digital beamforming is introduced across all N transceivers. We analyze the green point, which is the point of maximum EE on the EESE curve, and show that the logscale EE scales linearly with SE along a slope of lg2/N. We investigate the effect of M on EE for a given SE value in the case of fixed NM and independent N and M. In both cases, there is a unique optimal M that results in optimal EE. In the case of independent N and M, there is no optimal （N, M） combination for optimizing EE. The results of numerical simulations are provided, and these results support our analysis.

时延反馈下的自适应STBC-Beamforming跨层设计

为提高无线通信网络的频谱效率,提出一种自适应空时分组编码波束成形(STBC-beamforming)跨层设计方案.该方案利用自适应编码调制技术与混合自动重传技术交互协作,使发射端可以根据反馈延时信息自适应调节调制模式,选择发射权以及自动重传数据.推导了系统在时延反馈条件下的频谱效率和中断概率的闭合表达式,分析了时延反馈对系统性能的影响.仿真结果表明,对比单发/单收跨层系统和Alamouti’s跨层系统,自适应STBC-beamforming跨层系统的性能有明显提高.

Hybrid Beamforming Design and Signal Processing with Fully-Connected Architecture for mmWave Integrated Sensing and Communications

Millimeter-wave (mmWave) is capable of achieving gigabit/second communication capacity and centimeter-level sensing accuracy and has become one of the main frequency bands for integrated sensing and communications (ISAC) research. Hybrid beamforming techniques have attracted much attention for solving the high path loss of mmWave and further reducing the hardware cost of the system. However, the related studies based on multicarrier and fully-connected hybrid architectures are still limited. For this reason,this paper investigates the orthogonal frequency division multiplexing (OFDM) based mmWave fully-connected hybrid architecture ISAC system to form a stable communication beam and dynamically varying sensing beam. In order to realize the aforementioned multifunctional beams, the hybrid beamformer design problem based on weighted error minimization of multicarrier is proposed and solved efficiently using the penalty dual decomposition (PDD) algorithm. Meanwhile, based on the echo model, the multicarrier multiple signal classification (MUSIC) algorithm for target angle of arrival estimation and the two-dimensional discrete Fourier transform(2D-DFT)algorithm for distance and velocity estimation are proposed, respectively. Numerical simulation results show that by adjusting the weighting factor,a flexible trade-off can be formed between the communication spectrum efficiency and the sensing accuracy error.

A novel zero-payload downlink CSI feedback scheme for closed-loop beamforming system

A novel downlink channel state information(CSI)feedback scheme is proposed for the closed-loopbeamforming system.In the proposed scheme,mobile terminal(MT)superposes the uplink pilot on thereceived downlink pilot,forms the hybrid pilot(HP),and then transmits the HP to base station(BS)viathe uplink pilot channel.Because downlink CSI can be recovered from HP at BS side without consumingextra uplink bandwidth,the proposed scheme can achieve zero-payload CSI feedback,effectively solvingthe traditional bottleneck problems,i.e.,the heavy burden for transmitting CSI.Moreover,both MT'scomplexity and feedback delays can be reduced since the downlink channel needs not to be estimated atMT any more.Simulations verify that the proposed scheme can achieve the better MSE performance forthe uplink channel estimation than the traditional scheme,and the cost for the zero-payload CSI feedbackis some acceptable loss of feedback precision.

一种基于有限内存拟牛顿法的混合波束成形算法

针对现有混合波束成形算法运行时间长、频谱效率低、误码率高的问题,该文提出一种基于有限内存拟牛顿法的混合波束成形算法(LBFGS)。该算法首先通过数字预编码器的最小二乘解构建单变量目标函数;然后采用目标函数的梯度近似黑塞矩阵的逆得到搜索方向并沿搜索方向更新模拟预编码器,直到满足停止条件;最后固定模拟预编码器得到数字预编码器。MATLAB仿真结果表明,LBFGS算法较现有MO算法减少了28%的运行时间,频谱效率提高了1.05%,误码率降低了1.06%。

基于去蜂窝毫米波MIMO的通感一体化混合波束设计

针对通信频谱资源的匮乏以及去蜂窝MIMO在资源利用方面的优势,提出了一种毫米波(millimeter-wave,mmWave)场景下的去蜂窝MIMO通感一体化(intergraded sensing and communication,ISAC)系统。在该系统中,基站为用户提供服务的同时,多天线用户设备能够主动检测多个目标。研究目标是设计模拟和数字波束形成器,以优化通信和雷达波束形成误差的加权和。研究中考虑了2种功率约束,并采用改进的正交匹配追踪算法和黎曼共轭梯度算法进行优化。对通信频谱效率和雷达波束方向图进行仿真分析,结果表明,混合波束方案能在频谱利用和波束指向方面实现折中的性能,这种方案对于提高系统性能具有潜在的应用前景。

一种基于SIC-CDM的低复杂度混合波束赋形方案

为了平衡毫米波大规模多输入多输出系统的性能和硬件开销,降低系统功耗,以频谱效率为优化目标,在部分连接结构下提出了一种收发端联合设计的低复杂度混合波束赋形方案。首先,基于连续干扰消除将原始优化问题转化为多个子阵的速率优化问题;然后,利用坐标下降法完成模拟波束赋形矩阵设计;最后,引入等效信道矩阵大幅降低矩阵维度,再对其进行奇异值分解获得数字波束赋形矩阵。仿真结果表明,与其他算法相比,所提算法在系统功耗降低的同时保持了较优的性能,且性能逼近部分连接结构的最优方案。

面向混合波束成形结构的改进SLM算法

在大规模多输入多输出系统中,峰均功率比(PAPR)是影响发射机性能的主要因素之一。传统的PAPR降低方法都是基于全数字编码结构,无法有效地降低混合波束成形结构中发射天线端信号的PAPR。为解决这一问题,提出一种改进选择性映射(SLM)算法,该方法对输入信号进行独立的相位旋转并计算发射天线端信号的PAPR,最后选取PAPR最小的一组信号进行发送。此外,还分析了使用该算法下发射天线端信号PAPR的上界和下界。理论分析与仿真结果显示,改进SLM算法能够有效地降低混合波束成形结构发射天线端信号的PAPR。

一种星载数模混合阵列结构及波束形成算法

6G星地融合网络对卫星通信系统提出了高速率低时延低能耗的要求,由于星地链路信道环境复杂多变且容易受到干扰,需要研究干扰场景下的低成本可实现阵列架构及算法。针对这一问题,设计了一种数模混合阵列结构,子阵采用50%稀疏馈电以及最小二乘波束形成算法,超阵采用最小二乘与线性约束最小方差波束形成算法,并理论分析了阵列结构的可行性,证明子阵的零点能够抑制超阵的栅瓣。仿真结果表明,该结构以更低的复杂度实现了大规模阵列的效果,波束方向图指向明确且零陷深度足够,对干扰的抑制明显,获得了接近理想阵列增益的BER性能。

部分连接宽带毫米波全双工MIMO系统混合波束成形设计

毫米波全双工MIMO系统是满足未来无线通信大带宽、低时延等需求的一种可行方案.本文针对采用有限精度移相器和部分连接结构的宽带毫米波全双工MIMO系统的混合波束成形问题进行研究,提出了一种可行的混合波束成形方法.首先,不考虑自干扰信号,利用上行/下行各子信道的奇异值分解和注水算法得到各子带最优全数字发送和接收波束成形矩阵;然后,将得到的全数字波束成形矩阵分解为满足部分连接结构的模拟波束成形矩阵和各子带数字波束成形矩阵;最后,利用最小均方误差准则更新各子带数字接收波束成形矩阵以降低自干扰信号对频谱效率的影响.分析表明,所提方法的算法复杂度较低;仿真结果表明,所提方法的频谱效率要优于相关研究和半双工毫米波通信.

混合智能反射面辅助的通信感知一体化:高能效波束成形设计

能量效率(EE)是5G+/6G无线通信的重要设计指标,而智能反射面(RIS)被普遍认为是改善EE的潜在手段。不同于被动RIS,混合RIS由有源和无源元件组成,对来波移相的同时可放大信号强度,能够有效克服被动RIS引起的“乘性衰落”效应。鉴于此,该文提出一种混合RIS辅助通信感知一体化(ISAC)的下行链路传输系统。为探究数据传输速率与能耗之间的内在关联,该文以RIS辅助ISAC网络能量效率最大化为目标,在满足基站(BS)发射功率、波束图增益以及混合RIS功率和幅值约束的条件下,联合优化基站端的波束赋形和混合RIS的相移。为解决该复杂的分数规划问题,提出基于交替优化(AO)的算法来求解。为克服AO算法中引入辅助变量造成算法复杂度高的难题,利用耦合优化变量的关联,提出一种基于级联深度学习网络的求解算法。仿真结果表明,提出的混合RIS辅助ISAC方案在和速率、能效方面皆优于现有方案,且算法收敛速度快。

自持续HIRS辅助的MU-MISO系统公平性研究

针对自持续智能反射面(Intelligent Reflecting Surface,IRS)存在牺牲系统性能和实施难度大等问题,提出了一种包含被动元件和主动元件的混合IRS(Hybrid IRS,HIRS)自持续辅助多用户多输入单输出(Multi-User Multiple Input Single Output, MU-MISO)系统的公平性传输方案。为了实现多用户通信的公平,联合考虑基站的主动波束成形和HIRS系数矩阵,建立了以最大化最小用户速率为目标的优化问题。然而,由于约束条件和目标问题中存在多变量耦合,导致优化问题是非凸的。因此,将原始问题分解为2个单变量的子问题,然后利用逐次凸近似和半正定松弛方法获得每个子问题的近似解,最后利用交替优化算法迭代求解每个子问题。仿真结果表明,所提优化方案可有效提高系统的最小速率。

一种高频系统信道矩阵低复杂度估计方法

毫米波/太赫兹通信支持超大工作带宽和超高通信速率,是具备高应用潜力和影响因子的6G关键候选技术。提出了一种高频通信系统混合赋形架构下的信道矩阵估计方法,可有效估计信道信息,对上下行信道互易性无要求,且通过构造特殊权矢量矩阵,在估计信道矩阵时通过矩阵相乘运算来完成信道矩阵估计,避免了统计协方差矩阵求逆或特征分解运算,大幅度降低信道估计算法的计算复杂度和运算量。

基于混合波束成形的mMIMO低轨卫星信道切换策略

低地轨道(low earth orbit,LEO)卫星通信(satellite communication,SATCOM)是最有希望与未来6G及更先进的无线网络相结合的系统之一。将大规模多输入多输出(massive multiple-input multiple-output,mMIMO)应用于LEO SATCOM,从mMIMO低轨卫星信道模型出发,重点研究单颗mMIMO低轨卫星内的信道切换问题,根据不同用户终端(user terminal,UT)的服务质量(quality of service,QoS)要求,构建了3种不同的信道切换场景,充分利用mMIMO的强波束成形能力,以波束跟踪和波束小区动态调整为技术核心,提出了基于混合波束成形的信道切换策略。仿真结果表明,与典型的铱星系统相比,所提出的信道切换策略更具优势。

A Universal Hybrid Precoding Scheme for Massive MIMO Communications

Based on an analog radio frequency(RF)network,hybrid precoding(HPC)for massive MIMO can achieve very high spectral efficiencies with moderate hardware cost and power consumption.Despite the extensive research efforts in recent years,the practioners are still looking for HPCs that are efficient and easy-to-implement.In this paper,we present a new method termed as the universal hybrid precoding(UHP),which is nearly optimal,computationally efficient,and applicable to various types of RF network(thus,the name universal):the components of the network can be phase shifters(with finite or infinite resolutions),switches,or their combinations;the topology of the network can be fully-connected or partiallyconnected.Besides the standard UHP,we also propose a simplified version termed as sUHP to trade a negligible performance loss for much reduced computational complexity.The analysis shows that the computational complexity of the proposed UHP/sUHP is one to two orders of magnitude lower than the state-of-theart methods.Simulation results verify the(near-)optimality of the proposed UHP scheme for various forms of the analog networks.

Improved Hybrid Precoding Technique with Low-Resolution for MIMO-OFDM System

This paper proposes an improved hybrid beamforming system based on multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM)system.The proposed beamforming system improves energy efficiency compared to the conventional hybrid beamforming system.Both sub-connected and full-connected structure are considered to apply the proposed algorithm.In the conventional hybrid beamforming,the usage of radio frequency(RF)chains and phase shifter(PS)gives high power and hardware complexity.In this paper,the phase over sampling(POS)with switches(SW)is used in hybrid beamforming system to improve the energy efficiency.The POS-SW structure samples the value of analog beamformer to make lower resolution than conventional system.The number of output data in POS is decided by the resolution of POS system.The limited number of POS decides the resolution of antenna array and the values of POSs are designed from maximum and minimum phase angle antenna array.Energy efficiency without the phase shifter is high although channel capacity is nearly similar with conventional system.Also,the amplifier with POS-SW system is proposed to improve the BER performance.According to the data bits,the output signals of POS are decided.The system with 2,3 and 4 bits is simulated to prove the proposed algorithm.In order to overcome the loss of low-resolution system,the amplifier with POS-SW system using channel information is proposed.The average sum-rate of 4 bits system shows the similar performance with the conventional hybrid beamforming system.This structure can play an important role by increasing the energy efficiency of the wireless communication system that many antennas are used.It is shown that the BER,average sum rate and energy efficiency of the proposed scheme are more improved than the conventional hybrid beamforming system.