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 acquir...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.展开更多
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 ...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.展开更多
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 hy...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.展开更多
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 channe...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.展开更多
This study explored the transformative potential of artificial intelligence(AI)in addressing the challenges posed by terahertz ultra-massive multiple-input multiple-output(UM-MIMO)systems.It begins by outlining the ch...This study explored the transformative potential of artificial intelligence(AI)in addressing the challenges posed by terahertz ultra-massive multiple-input multiple-output(UM-MIMO)systems.It begins by outlining the characteristics of terahertz UM-MIMO systems and identifies three primary challenges for transceiver design:computational complexity,modeling difficulty,and measurement limitations.The study posits that AI provides a promising solution to these challenges.Three systematic research roadmaps are proposed for developing AI algorithms tailored to terahertz UM-MIMO systems.The first roadmap,model-driven deep learning(DL),emphasizes the importance of leveraging available domain knowledge and advocates the adoption of AI only to enhance bottleneck modules within an established signal processing or optimization framework.Four essential steps are discussed:algorithmic frameworks,basis algorithms,loss function design,and neural architecture design.The second roadmap presents channel state information(CSI)foundation models,aimed at unifying the design of different transceiver modules by focusing on their shared foundation,that is,the wireless channel.The training of a single compact foundation model is proposed to estimate the score function of wireless channels,which serve as a versatile prior for designing a wide variety of transceiver modules.Four essential steps are outlined:general frameworks,conditioning,site-specific adaptation,and the joint design of CSI foundation models and model-driven DL.The third roadmap aims to explore potential directions for applying pretrained large language models(LLMs)to terahertz UM-MIMO systems.Several application scenarios are envisioned,including LLM-based estimation,optimization,search,network management,and protocol understanding.Finally,the study highlights open problems and future research directions.展开更多
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 pow...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.展开更多
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...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.展开更多
Near-field technology is increasingly recognized due to its transformative potential in communication systems,establishing it as a critical enabler for sixth-generation(6G)telecommunication development.This paper pres...Near-field technology is increasingly recognized due to its transformative potential in communication systems,establishing it as a critical enabler for sixth-generation(6G)telecommunication development.This paper presents a comprehensive survey of recent advancements in near-field technology research.First,we explore the near-field propagation fundamentals by detailing definitions,transmission characteristics,and performance analysis.Next,we investigate various near-field channel models—deterministic,stochastic,and electromagnetic information theory based models,and review the latest progress in near-field channel testing,highlighting practical performance and limitations.With evolving channel models,traditional mechanisms such as channel estimation,beamtraining,and codebook design require redesign and optimization to align with near-field propagation characteristics.We then introduce innovative beam designs enabled by near-field technologies,focusing on non-diffractive beams(such as Bessel and Airy)and orbital angular momentum(OAM)beams,addressing both hardware architectures and signal processing frameworks,showcasing their revolutionary potential in near-field communication systems.Additionally,we highlight progress in both engineering and standardization,covering the primary 6G spectrum allocation,enabling technologies for near-field propagation,and network deployment strategies.Finally,we conclude by identifying promising future research directions for near-field technology development that could significantly impact system design.This comprehensive review provides a detailed understanding of the current state and potential of near-field technologies.展开更多
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 architect...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.展开更多
Traditional wireless communication systems have extensively used far-field spatial resources.However,with the emergence of sixth-generation(6G)networks,the exploration and utilization of near-field resources have beco...Traditional wireless communication systems have extensively used far-field spatial resources.However,with the emergence of sixth-generation(6G)networks,the exploration and utilization of near-field resources have become imperative.These resources introduce novel physical spatial dimensions to wireless communication systems.By leveraging higher frequency bands—such as midband,millimeter-wave,and terahertz frequencies—and integrating technologies like reconfigurable intelligent surfaces(RISs),ultra-largescale multiple input multiple output(MIMO),and cellfree networks,near-field communication(NFC)is set to become a critical enabler for 6G networks.This paradigm shift challenges the conventional far-field plane wave assumptions,necessitating a reevaluation of strategies for spatial resource management.展开更多
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 ...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.展开更多
基金supported in part by the National Key Research and Development Program of China(Grant No.2020YFB1807205)in part by the National Natural Science Foundation of China(Grant No.62031019)in part by the European Commission through the H2020-MSCA-ITN META WIRELESS Research Project under Grant 956256。
文摘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.
基金supported by the National Natural Science Foundation of China for Outstanding Young Scholars (Grant No. 61722109)the National Natural Science Foundation of China (Grant No. 61571270)the Royal Academy of Engineering through the UK–China Industry Academia Partnership Programme Scheme (Grant No. UK-CIAPP\49)
文摘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.
基金supported in part by the National Key Research and Development Program of China(Grant No.2020YFB1805005)the National Natural Science Foundation of China(Grant No.62031019)the European Commission through the H2020-MSCA-ITN META WIRELESS Research Project under Grant 956256.
文摘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.
基金supported in part by the National Key Research and Development Program of China(Grant No.2020YFB1805005)in part by the National Natural Science Foundation of China(Grant No.62031019)in part by the European Commission through the H2020-MSCA-ITN META WIRELESS Research Project under Grant 956256。
文摘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.
基金supported in part by the Hong Kong Research Grant Council(16209023)。
文摘This study explored the transformative potential of artificial intelligence(AI)in addressing the challenges posed by terahertz ultra-massive multiple-input multiple-output(UM-MIMO)systems.It begins by outlining the characteristics of terahertz UM-MIMO systems and identifies three primary challenges for transceiver design:computational complexity,modeling difficulty,and measurement limitations.The study posits that AI provides a promising solution to these challenges.Three systematic research roadmaps are proposed for developing AI algorithms tailored to terahertz UM-MIMO systems.The first roadmap,model-driven deep learning(DL),emphasizes the importance of leveraging available domain knowledge and advocates the adoption of AI only to enhance bottleneck modules within an established signal processing or optimization framework.Four essential steps are discussed:algorithmic frameworks,basis algorithms,loss function design,and neural architecture design.The second roadmap presents channel state information(CSI)foundation models,aimed at unifying the design of different transceiver modules by focusing on their shared foundation,that is,the wireless channel.The training of a single compact foundation model is proposed to estimate the score function of wireless channels,which serve as a versatile prior for designing a wide variety of transceiver modules.Four essential steps are outlined:general frameworks,conditioning,site-specific adaptation,and the joint design of CSI foundation models and model-driven DL.The third roadmap aims to explore potential directions for applying pretrained large language models(LLMs)to terahertz UM-MIMO systems.Several application scenarios are envisioned,including LLM-based estimation,optimization,search,network management,and protocol understanding.Finally,the study highlights open problems and future research directions.
基金supported by the National Key Research and Development Program of China(No.2020YFB1805005)the National Natural Science Foundation of China(No.62031019)the European Commission through the H2020-MSCA-ITN META WIRELESS Research Project(No.956256)。
文摘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.
基金supported by the National Natural Science Foundation of China(No.62031019)the European Commission through the H2020-MSCA-ITN META WIRELESS Research Project(No.956256).
文摘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.
基金Project supported by the Natural Science Foundation of Hunan Province,China(No.2022JJ40561)the Scientific Research Program of National University of Defense Technology,China(No.ZK22-46)the National Natural Science Foundation of China(Nos.61890542,62001481,and 62071475)。
文摘Near-field technology is increasingly recognized due to its transformative potential in communication systems,establishing it as a critical enabler for sixth-generation(6G)telecommunication development.This paper presents a comprehensive survey of recent advancements in near-field technology research.First,we explore the near-field propagation fundamentals by detailing definitions,transmission characteristics,and performance analysis.Next,we investigate various near-field channel models—deterministic,stochastic,and electromagnetic information theory based models,and review the latest progress in near-field channel testing,highlighting practical performance and limitations.With evolving channel models,traditional mechanisms such as channel estimation,beamtraining,and codebook design require redesign and optimization to align with near-field propagation characteristics.We then introduce innovative beam designs enabled by near-field technologies,focusing on non-diffractive beams(such as Bessel and Airy)and orbital angular momentum(OAM)beams,addressing both hardware architectures and signal processing frameworks,showcasing their revolutionary potential in near-field communication systems.Additionally,we highlight progress in both engineering and standardization,covering the primary 6G spectrum allocation,enabling technologies for near-field propagation,and network deployment strategies.Finally,we conclude by identifying promising future research directions for near-field technology development that could significantly impact system design.This comprehensive review provides a detailed understanding of the current state and potential of near-field technologies.
基金This work was supported by the National Key Research and Development Program of China(No.2020YB1807201)the National Natural Science Foundation of China(No.62031019)the European Commission through the H2020-MSCA-ITN META WIRELESS Research Project(No.956256).
文摘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.
文摘Traditional wireless communication systems have extensively used far-field spatial resources.However,with the emergence of sixth-generation(6G)networks,the exploration and utilization of near-field resources have become imperative.These resources introduce novel physical spatial dimensions to wireless communication systems.By leveraging higher frequency bands—such as midband,millimeter-wave,and terahertz frequencies—and integrating technologies like reconfigurable intelligent surfaces(RISs),ultra-largescale multiple input multiple output(MIMO),and cellfree networks,near-field communication(NFC)is set to become a critical enabler for 6G networks.This paradigm shift challenges the conventional far-field plane wave assumptions,necessitating a reevaluation of strategies for spatial resource management.
文摘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.
