Codebook Design and Beam Training for Extremely Large-Scale RIS:Far-Field or Near-Field?

Reconfigurable intelligent surface(RIS)is more likely to develop into extremely large-scale RIS(XL-RIS)to efficiently boost the system capacity for future 6 G communications.Beam training is an effective way to acquire channel state information(CSI)for XL-RIS.Existing beam training schemes rely on the far-field codebook.However,due to the large aperture of XL-RIS,the scatters are more likely to be in the near-field region of XL-RIS.The far-field codebook mismatches the near-field channel model.Thus,the existing far-field beam training scheme will cause severe performance loss in the XL-RIS assisted nearfield communications.To solve this problem,we propose the efficient near-field beam training schemes by designing the near-field codebook to match the nearfield channel model.Specifically,we firstly design the near-field codebook by considering the near-field cascaded array steering vector of XL-RIS.Then,the optimal codeword for XL-RIS is obtained by the exhausted training procedure.To reduce the beam training overhead,we further design a hierarchical nearfield codebook and propose the corresponding hierarchical near-field beam training scheme,where different levels of sub-codebooks are searched in turn with reduced codebook size.Simulation results show the proposed near-field beam training schemes outperform the existing far-field beam training scheme.

Modular Extremely Large-Scale Array Communication:Near-Field Modelling and Performance Analysis

This paper investigates the wireless communication with a novel architecture of antenna arrays,termed modular extremely large-scale array(XLarray),where array elements of an extremely large number/size are regularly mounted on a shared platform with both horizontally and vertically interlaced modules.Each module consists of a moderate/flexible number of array elements with the inter-element distance typically in the order of the signal wavelength,while different modules are separated by the relatively large inter-module distance for convenience of practical deployment.By accurately modelling the signal amplitudes and phases,as well as projected apertures across all modular elements,we analyse the near-field signal-to-noise ratio(SNR)performance for modular XL-array communications.Based on the non-uniform spherical wave(NUSW)modelling,the closed-form SNR expression is derived in terms of key system parameters,such as the overall modular array size,distances of adjacent modules along all dimensions,and the user's three-dimensional(3D)location.In addition,with the number of modules in different dimensions increasing infinitely,the asymptotic SNR scaling laws are revealed.Furthermore,we show that our proposed near-field modelling and performance analysis include the results for existing array architectures/modelling as special cases,e.g.,the collocated XL-array architecture,the uniform plane wave(UPW)based far-field modelling,and the modular extremely large-scale uniform linear array(XL-ULA)of onedimension.Extensive simulation results are presented to validate our findings.

A Large-Scale Survey for Extremely Cold Young Stellar Objects in the Galaxy

We conducted a large-scale survey of the extremely-cold infrared sources(ECISs) along the Galactic plane. There are 1912 (IRAS) sources selected on the basis of their color indices and their association with recent star formation. A quick survey was made toward 724 sources. There are 251 sources detected with significant CO emission during the quick survey above the detection limit of 0 9 K. Among the various sources detected, there are 147 sources found to have broad CO wing emission, including 116 newly detected sources. These sources comprise a new database for future study of star formation in our Galaxy. Using the known outflow sources as an effective indicator, we found the outflow detection rate of the quick survey is 62%, reasonably sensitive in survey for new outflow sources. Results from limited follow-up studies are introduced.

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.

Fairness-Oriented Hybrid Precoding for Massive MIMO Maritime Downlink Systems with Large-Scale CSIT

Different from conventional cellular networks, a maritime communication base station(BS) has to cover a much wider area due to the limitation of available BS sites. Accordingly the performance of users far away from the BS is poor in general. This renders the fairness among users a challenging issue for maritime communications. In this paper, we consider a practical massive MIMO maritime BS with hybrid digital and analog precoding. Only the large-scale channel state information at the transmitter(CSIT) is considered so as to reduce the implementation complexity and overhead of the system. On this basis, we address the problem of fairness-oriented precoding design. A max-min optimization problem is formulated and solved in an iterative way. Simulation results demonstrate that the proposed scheme performs much better than conventional hybrid precoding algorithms in terms of minimum achievable rate of all the users, for the typical three-ray maritime channel model.

A Causality-guided Statistical Approach for Modeling Extreme Mei-yu Rainfall Based on Known Large-scale Modes——A Pilot Study

Extreme Mei-yu rainfall(MYR)can cause catastrophic impacts to the economic development and societal welfare in China.While significant improvements have been made in climate models,they often struggle to simulate local-to-regional extreme rainfall(e.g.,MYR).Yet,large-scale climate modes(LSCMs)are relatively well represented in climate models.Since there exists a close relationship between MYR and various LSCMs,it might be possible to develop causality-guided statistical models for MYR prediction based on LSCMs.These statistical models could then be applied to climate model simulations to improve the representation of MYR in climate models.In this pilot study,it is demonstrated that skillful causality-guided statistical models for MYR can be constructed based on known LSCMs.The relevancy of the selected predictors for statistical models are found to be consistent with the literature.The importance of temporal resolution in constructing statistical models for MYR is also shown and is in good agreement with the literature.The results demonstrate the reliability of the causality-guided approach in studying complex circulation systems such as the East Asian summer monsoon(EASM).Some limitations and possible improvements of the current approach are discussed.The application of the causality-guided approach opens up a new possibility to uncover the complex interactions in the EASM in future studies.

Antenna selection based on large-scale fading for distributed MIMO systems

An antenna selection algorithm based on large-scale fading between the transmitter and receiver is proposed for the uplink receive antenna selection in distributed multiple-input multiple-output(D-MIMO) systems. By utilizing the radio access units(RAU) selection based on large-scale fading,the proposed algorithm decreases enormously the computational complexity. Based on the characteristics of distributed systems,an improved particle swarm optimization(PSO) has been proposed for the antenna selection after the RAU selection. In order to apply the improved PSO algorithm better in antenna selection,a general form of channel capacity was transformed into a binary expression by analyzing the formula of channel capacity. The proposed algorithm can make full use of the advantages of D-MIMO systems,and achieve near-optimal performance in terms of channel capacity with low computational complexity.

Analysis on Precipitation Efficiency of the “21.7” Henan Extremely Heavy Rainfall Event

A record-breaking heavy rainfall event that occurred in Zhengzhou,Henan province during 19–21 July 2021 is simulated using the Weather Research and Forecasting Model,and the large-scale precipitation efficiency(LSPE)and cloud-microphysical precipitation efficiency(CMPE)of the rainfall are analyzed based on the model results.Then,the key physical factors that influenced LSPE and CMPE,and the possible mechanisms for the extreme rainfall over Zhengzhou are explored.Results show that water vapor flux convergence was the key factor that influenced LSPE.Water vapor was transported by the southeasterly winds between Typhoon In-Fa(2021)and the subtropical high,and the southerly flow of Typhoon Cempaka(2021),and converged in Zhengzhou due to the blocking by the Taihang and Funiu Mountains in western Henan province.Strong moisture convergence centers were formed on the windward slope of the mountains,which led to high LSPE in Zhengzhou.From the perspective of CMPE,the net consumption of water vapor by microphysical processes was the key factor that influenced CMPE.Quantitative budget analysis suggests that water vapor was mainly converted to cloud water and ice-phase particles and then transformed to raindrops through melting of graupel and accretion of cloud water by rainwater during the heavy precipitation stage.The dry intrusion in the middle and upper levels over Zhengzhou made the high potential vorticity descend from the upper troposphere and enhanced the convective instability.Moreover,the intrusion of cold and dry air resulted in the supersaturation and condensation of water vapor,which contributed to the heavy rainfall in Zhengzhou.

超大规模MIMO阵列可视区域空间分布数据集

可视区域(VR)信息可用于降低超大规模多输入多输出(XL-MIMO)系统传输设计复杂度,但现有理论分析与传输设计多基于简化的VR统计分布模型。为评估分析XL-MIMO在实际物理传播场景中的性能,该文公开了XL-MIMO阵列VR空间分布数据集,其由环境参数设置、射线追踪仿真、天线场强数据预处理和VR判定准则等步骤构建。该数据集针对典型城区无线传播场景,建立了用户位置采样与场强数据、VR数据之间的关联,总数据条目数量达上亿级。进一步对其中VR形态、VR分布进行了可视化展示与分析,并以基于VR的XL-MIMO用户接入协议为例,利用该数据集对其在真实传播场景中的性能进行了仿真,为该数据集的应用提供了典型样例。

近场信道下毫米波MIMO-NOMA网络性能优化

超大规模多输入多输出(Extremely Large-Scale Multiple Input Multiple Output,XL-MIMO)、非正交多址(NonOrthogonal Multiple Access,NOMA)、混合波束成形(Hybrid Beamforming,HBF)是6G的关键技术。随着天线数量的大幅增加,大规模MIMO系统向XL-MIMO系统的转变不仅意味着天线数量的变化,而且电磁波的传输特性发生了根本性变化,基于平面波模型的远场信道将不再适用。因此,考虑基于球面波传输模型的近场通信场景,在该模型下采用群体串行干扰删除(Group-level Successive Interference Cancellation,GSIC)的毫米波MIMO-NOMA网络能量效率。首先,基于近场信道建立上行链路毫米波XL-MIMO-HBF-NOMA系统模型,并给出优化的用户分组方案。其次,提出以最大化能量效率为目标的优化问题,并通过波束扫描和迫零技术完成HBF设计。为求解该非凸优化问题,采用嵌套的二次变换技术,并设计关于HBF与功率分配的迭代优化算法。最后,通过仿真验证所提架构在近场通信中的有效性。

面向Sub-7 GHz频段分布式超大规模MIMO技术

下一代移动通信系统将在新的频段进一步提升整体性能。面向未来6G系统在Sub-7 GHz频段部署所面临的连续覆盖、容量提升以及部署困难等潜在难题,提出了一种创新的总体方案。这一方案结合了以用户为中心的接入网架构与分布式超大规模MIMO技术,旨在实现更高效的通信性能和用户体验。在所提出的以用户为中心的网络构架中,系统能够突破中心化限制,构建出中心网络与边缘分布式网络结合的以用户为中心的端到端分布式自治网络,智能自适应端到端用户需求。基于该构架可通过动态调整小区的覆盖范围和容量,更好地应对不同场景下的用户需求。通过优化连接管理策略,可以有效减少连接中断和延迟,提升系统的稳定性和用户的满意度。针对上述接入网络构架,给出了分布式超大规模系统中的灵活小区构建、链接管理及接入过程方案,并对CSI测量上报、分布式天线校准等底层核心问题进行了分析。

超大规模非平稳MIMO信道估计问题研究与设计

超大规模MIMO(Multiple-Input Multiple-Output)系统在未来的通信发展有巨大的潜力,随着天线阵列规模的增大,天线阵列的近场效应和无线信道的空间非平稳性对信道估计带来了更大的挑战。对于近场效应,不仅需要估计角度,还需要估计距离,本文提出将所需估计的角度和距离分开估计,减少估计的复杂度;对于非平稳性,需要判断散射体的可见子阵列的范围,本文提出对每个子阵列分别估计角度,根据角度和对子阵列接收信号的协方差矩阵做特征值分解得到的特征值大小,来判断散射体的可见子阵列范围,然后根据已得到的角度来估计距离。进一步分析发现,靠近中心的子阵列角度估计更准确,靠近边缘的子阵列距离估计更准确。在此基础上,本文给出了不同散射情况下超大规模阵列角度和距离的确定方案。仿真结果表明,所提出的针对近场效应和非平稳性的信道估计方案有更小的均方误差。

超大规模MIMO系统中稀疏度自适应的极化域信道估计

针对超大规模多输入多输出(Multiple-Input Multiple-Output, MIMO)系统中的极化域信道估计调整,提出了一种基于压缩感知的自适应极化域稀疏度同步正交匹配追踪(Adaptive Polar-domain Simultaneous Orthogonal Matching Pursuit, AP-SOMP)算法。AP-SOMP算法利用信道相关度设计合理的判决准则来估计极化域信道稀疏度,从而能在极化域信道稀疏度未知的情况下完成信道估计。该算法有效地克服了传统算法对信道稀疏度的依赖,具有更强的实用性。仿真结果表明,AP-SOMP算法在归一化均方误差性能表现上优于传统的基于网格的极化域同步正交匹配追踪(Polar-domain Simultaneous Orthogonal Matching Pursuit, P-SOMP)算法,且算法复杂度并未明显增加。

Contrasts between the Interannual Variations of Extreme Rainfall over Western and Eastern Sichuan in Mid-summer

Rainfall amount in mid-summer(July and August)is much greater over eastern than western Sichuan,which are characterized by basin and plateau,respectively.It is shown that the interannual variations of extreme rainfall over these two regions are roughly independent,and they correspond to distinct anomalies of both large-scale circulation and sea surface temperature(SST).The enhanced extreme rainfall over western Sichuan is associated with a southward shift of the Asian westerly jet,while the enhanced extreme rainfall over eastern Sichuan is associated with an anticyclonic anomaly in the upper troposphere over China.At low levels,on the other hand,the enhanced extreme rainfall over western Sichuan is related to two components of wind anomalies,namely southwesterly over southwestern Sichuan and northeasterly over northeastern Sichuan,which favor more rainfall under the effects of the topography.Relatively speaking,the enhanced extreme rainfall over eastern Sichuan corresponds to the low-level southerly anomalies to the east of Sichuan,which curve into northeasterly anomalies over the basin when they encounter the mountains to the north of the basin.Therefore,it can be concluded that the topography in and around Sichuan plays a crucial role in inducing extreme rainfall both over western and eastern Sichuan.Finally,the enhanced extreme rainfall in western and eastern Sichuan is related to warmer SSTs in the Maritime Continent and cooler SSTs in the equatorial central Pacific,respectively.

Extreme large-scale atmospheric circulation associated with the“21·7”Henan flood

From July 19 to 21,2021,Henan,a province in northern China(NC),was affected by severe flooding(referred to hereafter as“21·7”)caused by a prolonged record-breaking extreme precipitation(EP)event.Understanding the extremes of the large-scale circulation pattern during“21·7”is essential for predicting EP events and preventing future disasters.In this study,daily atmospheric large-scale circulations over NC in the summers from 1979 to 2021 were investigated using the circulation classification method of an obliquely rotated principal component analysis in T-mode(PCT).The geopotential heights at 500 hPa and 925 hPa were applied successively in classification.Among the nine summer circulation patterns found at 500 hPa,the three days of“21·7”belonged to the Type 8 pattern,which had the second highest probability of EP days among all patterns.It was characterized by a southeasterly wind toward North China Plain driven by a dipole geopotential height field,with the West Pacific subtropical high(WPSH)extending far north to 30°N and low pressure to the south near NC.Tropical cyclones(TCs)occurred on 72.5%of EP days,in which larger amounts of precipitation and a longer duration of EP days were found along the mountains in NC,as compared with other patterns.The distribution of EP events under this pattern was mainly influenced by the location of the low pressure at 925 hPa in the dipole.The subtype 8-3 circulation,with low pressure in the east of Taiwan Island,included“21·7”and accounted for 1.6%of all summer days.Typhoon In-fa,together with the WPSH,gave rise to intense column integrated moisture flux convergence(IMFC)via the southeasterly wind to Henan,which occurred continuously during the 3 days of“21·7”,resulting in the largest(second largest)mean IMFC among 3 consecutive EP days under type 8(all types)during the past 43 summers in NC.Further analysis revealed that the large-scale dynamic process could not completely explain the record-breaking EP during“21·7”,indicating possible contributions of other dynamic processes related to meso-scale convective storms.

Anomalous Features of Extreme Meiyu in 2020 over the Yangtze-Huai River Basin and Attribution to Large-Scale Circulations

Extremely anomalous features of Meiyu in 2020 over the Yangtze-Huai River basin(YHRB)and associated causes in perspective of the large-scale circulation are investigated in this study,based on the Meiyu operational monitoring information and daily data of precipitation,global atmospheric reanalysis,and sea surface temperature(SST).The main results are as follows.(1)The 2020 YHRB Meiyu exhibits extremely anomalous characteristics,which are the most prominent since the 1980 s.The 2020 Meiyu season features the fourth earliest onset,the third latest retreat,the longest duration,the maximum Meiyu rainfall,the strongest mean rainfall intensity,and the maximum number of stations/days with rainstorm.(2)The extremely long duration of the 2020 Meiyu season lies in the farily early onset and late retreat of Meiyu in this particular year.The early onset of Meiyu is due to the earlier-than-normal first northward shift and migration of the key influential systems including the northwestern Pacific subtropical high(NWPSH)and the South Asian high(SAH)along with the East Asian summer monsoon,induced by weak cold air activities from late May to early mid-June.However,the extremely late retreat of Meiyu is because of later-than-normal second northward shift of the associated large-scale circulation systems accompanied with strong cold air activities,and extremely weak and southward located ITCZ over Northwest Pacific in July.(3)The extremely more than normal Meiyu rainfall is represented by its long duration and strong rainfall intensity.The latter is likely attributed to extreme anomalies of water vapor convergence and vertical ascending motion over the YHRB,resulting from the compound effects of the westward extended and enlarged NWPSH,the eastward extended and expanded SAH,and the strong water vapor transport associated with the low-level southerly wind.The extremely warm SST in the tropical Indian Ocean seems to be the key factor to induce the above-mentioned anomalous large-scale circulations.The results from this study serve to improve understanding of formation mechanisms of the extreme Meiyu in China and may help forecasters to extract useful large-scale circulation features from numerical model products to improve medium-extended-range operational forecasts.

Spatiotemporal Variability in Extreme Temperature Events in an Arid-Semiarid Region of China and Their Teleconnections with Large-Scale Atmospheric Circulation

With a warming climate,temperature extremes have been a main global issue in recent decades due to their potential influence on the sustainable development of human life and natural ecosystems.In this study,12 indicators of extreme temperature events are used to evaluate the spatiotemporal distribution,periodic structure and teleconnections with large-scale atmospheric circulation in Xinjiang,Northwest China by combining wavelet coherence(WTC) analysis based on continuous wavelet transform(CWT) analysis with the sequential Mann-Kendall test.We find that over the past six decades,the climate in Xinjiang has become warmer and has suffered from increases in the frequency of warm extremes and decreases in the frequency of cold extremes.Warm extremes have mainly occurred in the southern Tianshan Mountains surrounding the Tarim Basin and western part of the Taklamakan Desert,and cold extremes have primarily occurred in the southwestern Altai Mountains and northern foot of the Tianshan Mountains.Extreme temperature events,including warm extremes,cold extremes,and other temperature indices,have significant interannual variability,with the main oscillation periods at smaller(2–4-year band),intermediate(4–7-year band),and greater time scales in recent decades.Furthermore,cold-extreme indices,including frost days,cool days,and cool nights all show a clear changepoint during 1990–1997 at the 95% confidence level,and both ice days and cold spell duration indicator have a potential changepoint during 1981–1986.However,the changing points for warmextreme indices are detected during 1992–1998.The temperature variables are significantly correlated with the EI Ni?o-Southern Oscillation(ENSO) and Arctic Oscillation(AO),but less well correlated with the Pacific Decadal Oscillation(PDO).The phase difference in the WTC spectra is not uniform between temperature extremes and climatic oscillations.Our findings will have important implications for local governments in taking effective measures to mitigate the potential effects of regional climate warming due to human activities in Xinjiang.

Towards Near-Field Communications for 6G:Challenges and Opportunities

Extremely large-scale multiple-input multiple-output(XL-MIMO)and terahertz(THz)communications are pivotal candidate technologies for supporting the development of 6G mobile networks.However,these techniques invalidate the common assumptions of far-field plane waves and introduce many new properties.To accurately understand the performance of these new techniques,spherical wave modeling of near-field communications needs to be applied for future research.Hence,the investigation of near-field communication holds significant importance for the advancement of 6G,which brings many new and open research challenges in contrast to conventional far-field communication.In this paper,we first formulate a general model of the near-field channel and discuss the influence of spatial nonstationary properties on the near-field channel modeling.Subsequently,we discuss the challenges encountered in the near field in terms of beam training,localization,and transmission scheme design,respectively.Finally,we point out some promising research directions for near-field communications.

Non-orthogonal pilot pattern for sparse channel estimation in large-scale MIMO-OFDM system

From the perspective of compressed sensing（CS） theory, the channel estimation problem in large-scale multiple input multiple output（MIMO）-orthogonal frequency division multiplexing（OFDM） system is investigated. According to the theory, the smaller mutual coherence the reconstruction matrix has, the higher success probability the estimation can obtain. Aiming to design a pilot that can make the system reconstruction matrix having the smallest mutual coherence, this paper proposes a low complexity joint algorithm and obtains a kind of non-orthogonal pilot pattern. Simulation results show that compared with the conventional orthogonal pilot pattern, applying the proposed pattern in the CS channel estimation can obtain the better normalized mean square error performance. Moreover, the bit error rate performance of the large-scale MIMO-OFDM system is also improved.

MMSE-based random sampling for iterative detection for large-scale MIMO systems

Although large-scale MIMO can offer a high spectral efficie ncy,there are a number of difficulties in its implementation.Among those,the computational complexity of MIMO detection is crucial and may limit its use at devices of limited computing power such as users’mobile devices.Random sampling for large-scale MIMO detection of low complexity were studied.In particular,a MMSE approach for random sampling,was formulated from which an iterative detector can be derived for better performances.