Continuous-Time Channel Prediction Based on Tensor Neural Ordinary Differential Equation

Channel prediction is critical to address the channel aging issue in mobile scenarios.Existing channel prediction techniques are mainly designed for discrete channel prediction,which can only predict the future channel in a fixed time slot per frame,while the other intra-frame channels are usually recovered by interpolation.However,these approaches suffer from a serious interpolation loss,especially for mobile millimeter-wave communications.To solve this challenging problem,we propose a tensor neural ordinary differential equation(TN-ODE)based continuous-time channel prediction scheme to realize the direct prediction of intra-frame channels.Specifically,inspired by the recently developed continuous mapping model named neural ODE in the field of machine learning,we first utilize the neural ODE model to predict future continuous-time channels.To improve the channel prediction accuracy and reduce computational complexity,we then propose the TN-ODE scheme to learn the structural characteristics of the high-dimensional channel by low-dimensional learnable transform.Simulation results show that the proposed scheme is able to achieve higher intra-frame channel prediction accuracy than existing schemes.

Geometric Mean Decomposition Based Hybrid Precoding for Millimeter-Wave Massive MIMO

Hybrid precoding can reduce the number of required radio frequency(RF)chains in millimeter-Wave(mmWave) massive MIMO systems. However, existing hybrid precoding based on singular value decomposition(SVD) requires the complicated bit allocation to match the different signal-to-noise-ratios(SNRs) of different sub-channels. In this paper,we propose a geometric mean decomposition(GMD)-based hybrid precoding to avoid the complicated bit allocation. Specifically,we seek a pair of analog and digital precoders sufficiently close to the unconstrained fully digital GMD precoder. To achieve this, we fix the analog precoder to design the digital precoder, and vice versa. The analog precoder is designed based on the orthogonal matching pursuit(OMP) algorithm, while GMD is used to obtain the digital precoder. Simulations show that the proposed GMD-based hybrid precoding achieves better performance than the conventional SVD-based hybrid precoding with only a slight increase in complexity.

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.

Wideband Channel Estimation for THz Massive MIMO

Terahertz(THz)communication is considered to be a promising technology for future 6G network.To overcome the severe attenuation and relieve the high power consumption,massive multipleinput multiple-output(MIMO)with hybrid precoding has been widely considered for THz communication.However,accurate wideband channel estimation,which is essential for hybrid precoding,is challenging in THz massive MIMO systems.The existing wideband channel estimation schemes based on the ideal assumption of common sparse channel support will suffer from a severe performance loss due to the beam split effect.In this paper,we propose a beam split pattern detection based channel estimation scheme to realize reliable wideband channel estimation in THz massive MIMO systems.Specifically,a comprehensive analysis on the angle-domain sparse structure of the wideband channel is provided by considering the beam split effect.Based on the analysis,we define a series of index sets called as beam split patterns,which are proved to have a one-to-one match to different physical channel directions.Inspired by this one-to-one match,we propose to estimate the physical channel direction by exploiting beam split patterns at first.Then,the sparse channel supports at different subcarriers can be obtained by utilizing a support detection window.This support detection window is generated by expanding the beam split pattern which is determined by the obtained physical channel direction.The above estimation procedure will be repeated path by path until all path components are estimated.Finally,the wideband channel can be recovered by calculating the elements on the total sparse channel support at all subcarriers.The proposed scheme exploits the wideband channel property implied by the beam split effect,i.e.,beam split pattern,which can significantly improve the channel estimation accuracy.Simulation results show that the proposed scheme is able to achieve higher accuracy than existing schemes.

Focusing Ability Enhancement in Broadside Direction of Array:From UCA to UCCA

To meet the ever-increasing demand for the data rates of wireless communications,extremely large-scale antenna array(ELAA)has emerged as one of the candidate technologies for future 6G communications.The significantly increased number of antennas in ELAA gives rise to near-field communications,necessitating tailored beamforming techniques within the near-field regions to accommodate the spherical-wave propagation characteristics.Among various array geometries of ELAA,uniform circular array(UCA)has gained much attention for its distinct capability of maintaining uniform beam pattern across different azimuth angles.However,existing analysis of near-field UCA beamforming indicates that the near-field region severely declines in the broadside of UCA,where the system fails to benefit from near-field communications.To tackle this problem,the near-field beamforming technique of uniform concentric circular arrays(UCCAs)is investigated in this paper,which has the potential to enlarge the near-field region in the broadside direction.First,the analysis of beamforming gain in the 3D space with UCA and UCCA is provided.Then,the distinct beamforming characteristics that set UCCA apart from UCA are delineated,revealing the superiority of UCCA in extending the near-field region in broadside at the cost of slightly reduced near-field region in the coplane.Simulation results are provided to verify the effectiveness of the theoretical analysis of beamforming gain with UCCA and the enhanced focusing ability of UCCA in the broadside direction.

Reconfigurable Intelligent Surfaces for 6G:Nine Fundamental Issues and One Critical Problem

Thanks to the recent advances in metamaterials,Reconfigurable Intelligent Surface(RIS)has emergedas a promising technology for future 6G wireless communications.Benefiting from its high array gain,low cost,and low power consumption,RISs are expected to greatly enlarge signal coverage,improve system capacity,andincrease energy efficiency.In this article,we systematically overview the emerging RIS technology with the focuson its key basics,nine fundamental issues,and one critical problem.Specifically,we first explain the RIS basics,including its working principles,hardware structures,and potential benefits for communications.Based on thesebasics,nine fundamental issues of RISs,such as“What’s the differences between RISs and massive MIMO?”and“Is RIS really intelligent?”,are explicitly addressed to elaborate its technical features,distinguish it from existingtechnologies,and clarify some misunderstandings in the literature.Then,one critical problem of RISs is revealedthat,due to the“multiplicative fading”effect,existing passive RISs can hardly achieve visible performance gains inmany communication scenarios with strong direct links.To address this critical problem,a potential solution calledactive RISs is introduced,and its effectiveness is demonstrated by numerical simulations.

Joint Beamforming Design for RIS-Assisted Cell-Free Network with Multi-Hop Transmissions

The collaboration of multiple Reconfigurable Intelligent Surfaces(RISs)and Access Points(APs)enjoys advantages of capacity enhancement,power saving,etc.,making the RIS-assisted cell-free network an important architecture for future communications.Similar to most existing works on RIS-assisted communications,the multi-hop link among RISs,i.e.,the reflecting link including more than one RISs,is usually ignored in RIS-assisted cell-free networks.In these scenarios,however,since multiple RISs are closely deployed,we find that the multi-hop channels should not be simply ignored due to their potential for capacity improvement.Unfortunately,to the best of our knowledge,there is no work exploring the multi-hop transmission of RIS-assisted cell-free networks.To fill in this blank,we investigate the multi-hop transmission of RIS-assisted cell-free networks,including the multi-hop channel model and the corresponding beamforming design.Specifically,we propose a general multi-hop transmission model,which takes the direct links,single-reflecting links,and multi-hop links into account.Based on this model,we formulate a beamforming design problem in an RIS-assisted cell-free network,which allows us to maximize the multi-user sum-rate with considering the impact of multi-hop channels.To address the non-convexity of the formulated problem,a joint active and passive beamforming scheme is proposed to solve the problem.Particularly,by utilizing fractional programming,we decouple the coupled beamforming parameters in the problem,and then these parameters are alternately optimized until the convergence of the sum-rate.Simulation results verify that the consideration for multi-hop links is necessary,and the capacity performance of the proposed scheme is 20%higher than those of the existing schemes.

Editorial

Reconfigurable Intelligent Surface(RIS),also known as intelligent reflecting surface or large intelligent surface,is an emerging new physical-layer technology in the field of wireless communications.The basic idea of RIS is to deploy a reconfigurable passive array in the environment to manipulate the propagation of electron-magnetic waves.RIS promises a new design paradigm for wireless communications,where the wireless propagation environment can be dynamically controlled,which is substantially different from the conventional design that focuses only on the transmitter and receiver.For RIS-aided wireless communications,some of the current methodologies in conventional communication systems need to be revised,and some novel solutions are required to realize the potential benefits of the RIS.Although the number of publications about RIS has recently sharply increased,there are still many challenging issues to be extensively investigated,such as the RIS channel modeling,fundamental performance limits,the system design,joint optimization of the RIS and the transceivers,channel state information acquisition,and interdisciplinary applications.