A semi-blind channel estimation algorithm based on subspace approach for orthogonal frequency division multiplexing（OFDM） systems over the frequency-selective channel is proposed. A linear preeoding is applied on ea...A semi-blind channel estimation algorithm based on subspace approach for orthogonal frequency division multiplexing（OFDM） systems over the frequency-selective channel is proposed. A linear preeoding is applied on each block before the IFFT operation and a low-rank structure is created in the received signal. Then subspace properties can be exploited to identify the channel up to a scalar ambiguity. The residual scalar ambiguities eliminated by inserting pilots into data stream. Simulation results illustrate the performance of the proposed semi-blind algorithm.展开更多
An adaptive bit loading and power-allocation scheme is proposed in order to augment the performance of the system based on orthogonal frequency division multiplexing （OFDM）, which is based on the maximum power margi...An adaptive bit loading and power-allocation scheme is proposed in order to augment the performance of the system based on orthogonal frequency division multiplexing （OFDM）, which is based on the maximum power margin. Coinciding with the adaptive loading scheme, a semi-blind channel estimation algorithm using subspace decomposition method is proposed, which uses the information in the cyclic prefix. An initial channel state information is estimated by using the training sequences with the method of interpolation filtering. The proposed adaptive scheme is simulated on an OFDM wireless local area network（WLAN） system in a time-varying channel. The performance is compared to the constant loading scheme.展开更多
Coordinated signal processing can obtain a huge transmission gain for Fog Radio Access Networks(F-RANs).However,integrating into large scale,it will lead to high computation complexity in channel estimation and spectr...Coordinated signal processing can obtain a huge transmission gain for Fog Radio Access Networks(F-RANs).However,integrating into large scale,it will lead to high computation complexity in channel estimation and spectral efficiency loss in transmission performance.Thus,a joint cluster formation and channel estimation scheme is proposed in this paper.Considering research remote radio heads(RRHs)centred serving scheme,a coalition game is formulated in order to maximize the spectral efficiency of cooperative RRHs under the conditions of balancing the data rate and the cost of channel estimation.As the cost influences to the necessary consumption of training length and estimation error.Particularly,an iterative semi-blind channel estimation and symbol detection approach is designed by expectation maximization algorithm,where the channel estimation process is initialized by subspace method with lower pilot length.Finally,the simulation results show that a stable cluster formation is established by our proposed coalition game method and it outperforms compared with full coordinated schemes.展开更多
In this paper, a quasi-Newton method fbr semi-blind estimation is derived for channel estimation in uplink cloud radio access networks （C-RANs）. Different from traditional pilot-aided estimation, semiblind estimatio...In this paper, a quasi-Newton method fbr semi-blind estimation is derived for channel estimation in uplink cloud radio access networks （C-RANs）. Different from traditional pilot-aided estimation, semiblind estimation utilizes the unknown data symbols in addition to the known pilot symbols to estimate the channel. An initial channel state information （CSI） obtained by least-squared （LS） estimation is needed in semi-blind estimation. BFGS （Brayben, Fletcher, Goldfarb and Shanno） algorithm, which employs data as well as pilot symbols, estimates the CSI though solving the problem provided by maximum-likelihood （ML） principle. In addition, mean-square-error （MSE） used to evaluate the estimation performance can be further minimized with an optimal pilot design. Simulation results show that the semi-blind estimation achieves a significant improvement in terms of MSE performance over the conventional LS estimation by utilizing data symbols instead of increasing the number of pilot symbols, which demonstrates the estimation accuracy and spectral efficiency are both improved by semiblind estimation for C-RANs.展开更多
Due to the interdependency of frame synchronization(FS)and channel estimation(CE),joint FS and CE(JFSCE)schemes are proposed to enhance their functionalities and therefore boost the overall performance of wireless com...Due to the interdependency of frame synchronization(FS)and channel estimation(CE),joint FS and CE(JFSCE)schemes are proposed to enhance their functionalities and therefore boost the overall performance of wireless communication systems.Although traditional JFSCE schemes alleviate the influence between FS and CE,they show deficiencies in dealing with hardware imperfection(HI)and deterministic line-of-sight(LOS)path.To tackle this challenge,we proposed a cascaded ELM-based JFSCE to alleviate the influence of HI in the scenario of the Rician fading channel.Specifically,the conventional JFSCE method is first employed to extract the initial features,and thus forms the non-Neural Network(NN)solutions for FS and CE,respectively.Then,the ELMbased networks,named FS-NET and CE-NET,are cascaded to capture the NN solutions of FS and CE.Simulation and analysis results show that,compared with the conventional JFSCE methods,the proposed cascaded ELM-based JFSCE significantly reduces the error probability of FS and the normalized mean square error(NMSE)of CE,even against the impacts of parameter variations.展开更多
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 capa...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.展开更多
It is assumed that reconfigurable intelligent surface(RIS)is a key technology to enable the potential of mmWave communications.The passivity of the RIS makes channel estimation difficult because the channel can only b...It is assumed that reconfigurable intelligent surface(RIS)is a key technology to enable the potential of mmWave communications.The passivity of the RIS makes channel estimation difficult because the channel can only be measured at the transceiver and not at the RIS.In this paper,we propose a novel separate channel estimator via exploiting the cascaded sparsity in the continuously valued angular domain of the cascaded channel for the RIS-enabled millimeter-wave/Tera-Hz systems,i.e.,the two-stage estimation method where the cascaded channel is separated into the base station(BS)-RIS and the RIS-user(UE)ones.Specifically,we first reveal the cascaded sparsity,i.e.,the sparsity exists in the hybrid angular domains of BS-RIS and the RIS-UEs separated channels,to construct the specific sparsity structure for RIS enabled multi-user systems.Then,we formulate the channel estimation problem using atomic norm minimization(ANM)to enhance the proposed sparsity structure in the continuous angular domains,where a low-complexity channel estimator via Alternating Direction Method of Multipliers(ADMM)is proposed.Simulation findings demonstrate that the proposed channel estimator outperforms the current state-of-the-arts in terms of performance.展开更多
Orthogonal time frequency space(OTFS)technique, which modulates data symbols in the delayDoppler(DD) domain, presents a potential solution for supporting reliable information transmission in highmobility vehicular net...Orthogonal time frequency space(OTFS)technique, which modulates data symbols in the delayDoppler(DD) domain, presents a potential solution for supporting reliable information transmission in highmobility vehicular networks. In this paper, we study the issues of DD channel estimation for OTFS in the presence of fractional Doppler. We first propose a channel estimation algorithm with both low complexity and high accuracy based on the unitary approximate message passing(UAMP), which exploits the structured sparsity of the effective DD domain channel using hidden Markov model(HMM). The empirical state evolution(SE) analysis is then leveraged to predict the performance of our proposed algorithm. To refine the hyperparameters in the proposed algorithm,we derive the update criterion for the hyperparameters through the expectation-maximization(EM) algorithm. Finally, Our simulation results demonstrate that our proposed algorithm can achieve a significant gain over various baseline schemes.展开更多
An integrated sensing and communication(ISAC)scheme for a millimeter wave(mmWave)multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM)Vehicle-to-Infrastructure(V2I)system is presented,in...An integrated sensing and communication(ISAC)scheme for a millimeter wave(mmWave)multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM)Vehicle-to-Infrastructure(V2I)system is presented,in which both the access point(AP)and the vehicle are equipped with large antenna arrays and employ hybrid analog and digital beamforming structures to compensate the path loss,meanwhile compromise between hardware complexity and system performance.Based on the sparse scattering nature of the mmWave channel,the received signal at the AP is organized to a four-order tensor by the introduced novel frame structure.A CANDECOMP/PARAFAC(CP)decomposition-based method is proposed for time-varying channel parameter extraction,including angles of departure/arrival(AoDs/AoAs),Doppler shift,time delay and path gain.Then leveraging the estimates of channel parameters,a nonlinear weighted least-square problem is proposed to recover the location accurately,heading and velocity of vehicles.Simulation results show that the proposed methods are effective and efficient in time-varying channel estimation and vehicle sensing in mmWave MIMOOFDM V2I systems.展开更多
Orthogonal Time Frequency and Space(OTFS) modulation is expected to provide high-speed and ultra-reliable communications for emerging mobile applications, including low-orbit satellite communications. Using the Dopple...Orthogonal Time Frequency and Space(OTFS) modulation is expected to provide high-speed and ultra-reliable communications for emerging mobile applications, including low-orbit satellite communications. Using the Doppler frequency for positioning is a promising research direction on communication and navigation integration. To tackle the high Doppler frequency and low signal-to-noise ratio(SNR) in satellite communication, this paper proposes a Red and Blue Frequency Shift Discriminator(RBFSD) based on the pseudo-noise(PN) sequence.The paper derives that the cross-correlation function on the Doppler domain exhibits the characteristic of a Sinc function. Therefore, it applies modulation onto the Delay-Doppler domain using PN sequence and adjusts Doppler frequency estimation by red-shifting or blue-shifting. Simulation results show that the performance of Doppler frequency estimation is close to the Cramér-Rao Lower Bound when the SNR is greater than -15dB. The proposed algorithm is about 1/D times less complex than the existing PN pilot sequence algorithm, where D is the resolution of the fractional Doppler.展开更多
Channel estimation is a well-known challenge for wireless orthogonal frequency division multiplexing(OFDM)communication systems with massive antennas on high speed rails(HSRs).This paper investigates this problem and ...Channel estimation is a well-known challenge for wireless orthogonal frequency division multiplexing(OFDM)communication systems with massive antennas on high speed rails(HSRs).This paper investigates this problem and design two practicable uplink and downlink channel estimators for orthogonal frequency division multiplexing(OFDM)communication systems with massive antenna arrays at base station on HSRs.Specifically,we first use pilots to estimate the initial angle of arrival(AoA)and channel gain information of each uplink path through discrete Fourier transform(DFT),and then refine the estimates via the angle rotation technique and suggested pilot design.Based on the uplink angel estimation,we design a new downlink channel estimator for frequency division duplexing(FDD)systems.Additionally,we derive the Cramér-Rao lower bounds(CRLBs)of the AoA and channel gain estimates.Finally,numerical results are provided to corroborate our proposed studies.展开更多
In this paper,we propose a joint channel estimation and symbol detection(JCESD)algorithm relying on message-passing algorithms(MPA)for orthogonal frequency division multiple access(OFDMA)systems.The channel estimation...In this paper,we propose a joint channel estimation and symbol detection(JCESD)algorithm relying on message-passing algorithms(MPA)for orthogonal frequency division multiple access(OFDMA)systems.The channel estimation and symbol detection leverage the framework of expectation propagation(EP)and belief propagation(BP)with the aid of Gaussian approximation,respectively.Furthermore,to reduce the computation complexity involved in channel estimation,the matrix inversion is transformed into a series of diagonal matrix inversions through the Sherman-Morrison formula.Simulation experiments show that the proposed algorithm can reduce the pilot overhead by about 50%,compared with the traditional linear minimum mean square error(LMMSE)algorithm,and can approach to the bit error rate(BER)performance bound of perfectly known channel state information within 0.1 dB.展开更多
Reconfigurable intelligent surface(RIS)can manipulate the wireless propagation environment by smartly adjusting the amplitude/phase in a programmable panel,enjoying the improved performance.The accurate acquisition of...Reconfigurable intelligent surface(RIS)can manipulate the wireless propagation environment by smartly adjusting the amplitude/phase in a programmable panel,enjoying the improved performance.The accurate acquisition of the instantaneous channel state information(CSI)in the cascaded RIS chain makes an indispensable contribution to the performance gains.However,it is quite challenging to estimate the CSI in a time-variant scenario due to the limited signal processing capability of the passive elements embedded in a RIS pannel.In this work,a channel estimation scheme for the RIS-assisted wireless communication system is proposed,which is demonstrated to perform well in a time-variant scenario.The cascaded RIS channel is modeled as a state-space model based upon the mobility situations.In addition,to fully exploit the time correlation of channel,Kalman filter is employed by taking the prior information of channels into account.Further,the optimal reflection coefficients are derived according to the minimum mean square error(MMSE)criterion.Numerical results show that the proposed methods exhibit superior performance if compared with a conventional channel estimation scheme.展开更多
Since orthogonal time-frequency space(OTFS)can effectively handle the problems caused by Doppler effect in high-mobility environment,it has gradually become a promising candidate for modulation scheme in the next gene...Since orthogonal time-frequency space(OTFS)can effectively handle the problems caused by Doppler effect in high-mobility environment,it has gradually become a promising candidate for modulation scheme in the next generation of mobile communication.However,the inter-Doppler interference(IDI)problem caused by fractional Doppler poses great challenges to channel estimation.To avoid this problem,this paper proposes a joint time and delayDoppler(DD)domain based on sparse Bayesian learning(SBL)channel estimation algorithm.Firstly,we derive the original channel response(OCR)from the time domain channel impulse response(CIR),which can reflect the channel variation during one OTFS symbol.Compare with the traditional channel model,the OCR can avoid the IDI problem.After that,the dimension of OCR is reduced by using the basis expansion model(BEM)and the relationship between the time and DD domain channel model,so that we have turned the underdetermined problem into an overdetermined problem.Finally,in terms of sparsity of channel in delay domain,SBL algorithm is used to estimate the basis coefficients in the BEM without any priori information of channel.The simulation results show the effectiveness and superiority of the proposed channel estimation algorithm.展开更多
A superimposed training （ST） based channel estimation method is presented that provides accurate estimation of a sparse underwater acoustic orthogonal frequency-division multiplexing （OFDM） channel while improving...A superimposed training （ST） based channel estimation method is presented that provides accurate estimation of a sparse underwater acoustic orthogonal frequency-division multiplexing （OFDM） channel while improving bandwidth transmission efficiency. A periodic low power training sequence is superimposed on the information sequence at the transmitter. The channel parameters can be estimated without consuming any extra system bandwidth, but an unknown information sequence can interfere with the ST channel estimation method, so in this paper, an iterative method was adopted to improve estimation performance. An underwater acoustic channel＇s properties include large channel dimensions and a sparse structure, so a matching pursuit （MP） algorithm was used to estimate the nonzero taps, allowing the performance loss caused by additive white Gaussian noise （AWGN） to be reduced. The results of computer simulations show that the proposed method has good channel estimation performance and can reduce the peak-to-average ratio of the OFDM channel as well.展开更多
Relay in full-duplex(FD) mode can achieve higher spectrum efficiency than that in half-duplex mode,while it is crucial to suppress relay self-interference to ensure transmission quality which requires instantaneous ch...Relay in full-duplex(FD) mode can achieve higher spectrum efficiency than that in half-duplex mode,while it is crucial to suppress relay self-interference to ensure transmission quality which requires instantaneous channel state information(CSI). In this paper,the channel estimation issue in FD amplify-andforward relay networks is considered,where the training-based estimation technique is adopted. Firstly,the least square(LS) estimation is implemented to obtain composite channel coefficients of source-relay-destination(SRD) channel and relay loop-interference(LI) channel in order to assist destination in performing data detection. Secondly,both LS and maximum likelihood estimation methods are utilized to perform individual channel estimation aiming at supporting successive interference cancelation at destination. Finally,simulation results demonstrate the effectiveness of both composite and individual channel estimation,and the presented ML method can achieve lower MSEs than LS solution.展开更多
A joint Doppler shift and channel estimation method for the millimeter-wave communication system of an unmanned aerial vehicle(UAV) equipped with a large-scale uniform linear antenna(ULA) array has been proposed. Sinc...A joint Doppler shift and channel estimation method for the millimeter-wave communication system of an unmanned aerial vehicle(UAV) equipped with a large-scale uniform linear antenna(ULA) array has been proposed. Since Doppler shift induces intercarrier interference, the parameters of the channel paths have been decomposed into the Doppler shift and the channel information. In order to obtain the Doppler shift, a new estimation algorithm based on a combination of discrete Fourier transform and phase rotation has been proposed, which can determine the appropriate number of antennas. In addition to estimating the channel information, a low-complexity joint Doppler shift and channel estimation method has been designed that can quickly obtain accurate estimates. Furthermore, the achievable sum rate, the theoretical bounds of the mean squared errors, and the Cram?er-Rao lower bounds of the estimation method have been derived. The analysis and simulation results prove that the performance of the proposed approach is close to the theoretical inference.展开更多
Orthogonal time frequency space(OTFS)modulation has been proven to be superior to traditional orthogonal frequency division multiplexing(OFDM)systems in high-speed communication scenarios.However,the existing channel ...Orthogonal time frequency space(OTFS)modulation has been proven to be superior to traditional orthogonal frequency division multiplexing(OFDM)systems in high-speed communication scenarios.However,the existing channel estimation schemes may results in poor peak to average power ratio(PAPR)performance of OTFS system or low spectrum efficiency.Hence,in this paper,we propose a low PAPR channel estimation scheme with high spectrum efficiency.Specifically,we design a multiple scattered pilot pattern,where multiple low power pilot symbols are superimposed with data symbols in delay-Doppler domain.Furthermore,we propose the placement rules for pilot symbols,which can guarantee the low PAPR.Moreover,the data aided iterative channel estimation was invoked,where joint channel estimation is proposed by exploiting multiple independent received signals instead of only one received signal in the existing scheme,which can mitigate the interference imposed by data symbols for channel estimation.Simulation results shows that the proposed multiple scattered pilot aided channel estimation scheme can significantly reduce the PAPR while keeping the high spectrum efficiency.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
The deep convolutional neural network(CNN)is exploited in this work to conduct the challenging channel estimation for mmWave massive multiple input multiple output(MIMO)systems.The inherent sparse features of the mmWa...The deep convolutional neural network(CNN)is exploited in this work to conduct the challenging channel estimation for mmWave massive multiple input multiple output(MIMO)systems.The inherent sparse features of the mmWave massive MIMO channels can be extracted and the sparse channel supports can be learnt by the multi-layer CNN-based network through training.Then accurate channel inference can be efficiently implemented using the trained network.The estimation accuracy and spectrum efficiency can be further improved by fully utilizing the spatial correlation among the sparse channel supports of different antennas.It is verified by simulation results that the proposed deep CNN-based scheme significantly outperforms the state-of-the-art benchmarks in both accuracy and spectrum efficiency.展开更多
文摘A semi-blind channel estimation algorithm based on subspace approach for orthogonal frequency division multiplexing（OFDM） systems over the frequency-selective channel is proposed. A linear preeoding is applied on each block before the IFFT operation and a low-rank structure is created in the received signal. Then subspace properties can be exploited to identify the channel up to a scalar ambiguity. The residual scalar ambiguities eliminated by inserting pilots into data stream. Simulation results illustrate the performance of the proposed semi-blind algorithm.
文摘An adaptive bit loading and power-allocation scheme is proposed in order to augment the performance of the system based on orthogonal frequency division multiplexing （OFDM）, which is based on the maximum power margin. Coinciding with the adaptive loading scheme, a semi-blind channel estimation algorithm using subspace decomposition method is proposed, which uses the information in the cyclic prefix. An initial channel state information is estimated by using the training sequences with the method of interpolation filtering. The proposed adaptive scheme is simulated on an OFDM wireless local area network（WLAN） system in a time-varying channel. The performance is compared to the constant loading scheme.
基金supported in part by the State Major Science and Technology Special Project(Grant No.2018ZX03001025)the National Natural Science Foundation of China(No.61831002 and No.61671074)the Fundamental Research Funds for the Central Universities under Grant No.2018XKJC01
文摘Coordinated signal processing can obtain a huge transmission gain for Fog Radio Access Networks(F-RANs).However,integrating into large scale,it will lead to high computation complexity in channel estimation and spectral efficiency loss in transmission performance.Thus,a joint cluster formation and channel estimation scheme is proposed in this paper.Considering research remote radio heads(RRHs)centred serving scheme,a coalition game is formulated in order to maximize the spectral efficiency of cooperative RRHs under the conditions of balancing the data rate and the cost of channel estimation.As the cost influences to the necessary consumption of training length and estimation error.Particularly,an iterative semi-blind channel estimation and symbol detection approach is designed by expectation maximization algorithm,where the channel estimation process is initialized by subspace method with lower pilot length.Finally,the simulation results show that a stable cluster formation is established by our proposed coalition game method and it outperforms compared with full coordinated schemes.
基金supported in part by the the National High Technology Research and Devel-opment Program of China(Grant No.2014AA01A701)National Natural Science Foundation of China(Grant No.61361166005)+2 种基金the State Major Science and Technology Special Projects(Grant No.2016ZX03001020006)the National Program for Support of Top-notch Young Pro-fessionalsthe Science and Technology Development Project of Beijing Municipal Education Commission of China(Grant No.KZ201511232036)
文摘In this paper, a quasi-Newton method fbr semi-blind estimation is derived for channel estimation in uplink cloud radio access networks （C-RANs）. Different from traditional pilot-aided estimation, semiblind estimation utilizes the unknown data symbols in addition to the known pilot symbols to estimate the channel. An initial channel state information （CSI） obtained by least-squared （LS） estimation is needed in semi-blind estimation. BFGS （Brayben, Fletcher, Goldfarb and Shanno） algorithm, which employs data as well as pilot symbols, estimates the CSI though solving the problem provided by maximum-likelihood （ML） principle. In addition, mean-square-error （MSE） used to evaluate the estimation performance can be further minimized with an optimal pilot design. Simulation results show that the semi-blind estimation achieves a significant improvement in terms of MSE performance over the conventional LS estimation by utilizing data symbols instead of increasing the number of pilot symbols, which demonstrates the estimation accuracy and spectral efficiency are both improved by semiblind estimation for C-RANs.
基金supported in part by the Sichuan Science and Technology Program(Grant No.2023YFG0316)the Industry-University Research Innovation Fund of China University(Grant No.2021ITA10016)+1 种基金the Key Scientific Research Fund of Xihua University(Grant No.Z1320929)the Special Funds of Industry Development of Sichuan Province(Grant No.zyf-2018-056).
文摘Due to the interdependency of frame synchronization(FS)and channel estimation(CE),joint FS and CE(JFSCE)schemes are proposed to enhance their functionalities and therefore boost the overall performance of wireless communication systems.Although traditional JFSCE schemes alleviate the influence between FS and CE,they show deficiencies in dealing with hardware imperfection(HI)and deterministic line-of-sight(LOS)path.To tackle this challenge,we proposed a cascaded ELM-based JFSCE to alleviate the influence of HI in the scenario of the Rician fading channel.Specifically,the conventional JFSCE method is first employed to extract the initial features,and thus forms the non-Neural Network(NN)solutions for FS and CE,respectively.Then,the ELMbased networks,named FS-NET and CE-NET,are cascaded to capture the NN solutions of FS and CE.Simulation and analysis results show that,compared with the conventional JFSCE methods,the proposed cascaded ELM-based JFSCE significantly reduces the error probability of FS and the normalized mean square error(NMSE)of CE,even against the impacts of parameter variations.
基金supported in part by the Beijing Natural Science Foundation under Grant No.L202003the National Natural Science Foundation of China under Grant U22B2001 and 62271065the Project of China Railway Corporation under Grant N2022G048.
文摘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.
文摘It is assumed that reconfigurable intelligent surface(RIS)is a key technology to enable the potential of mmWave communications.The passivity of the RIS makes channel estimation difficult because the channel can only be measured at the transceiver and not at the RIS.In this paper,we propose a novel separate channel estimator via exploiting the cascaded sparsity in the continuously valued angular domain of the cascaded channel for the RIS-enabled millimeter-wave/Tera-Hz systems,i.e.,the two-stage estimation method where the cascaded channel is separated into the base station(BS)-RIS and the RIS-user(UE)ones.Specifically,we first reveal the cascaded sparsity,i.e.,the sparsity exists in the hybrid angular domains of BS-RIS and the RIS-UEs separated channels,to construct the specific sparsity structure for RIS enabled multi-user systems.Then,we formulate the channel estimation problem using atomic norm minimization(ANM)to enhance the proposed sparsity structure in the continuous angular domains,where a low-complexity channel estimator via Alternating Direction Method of Multipliers(ADMM)is proposed.Simulation findings demonstrate that the proposed channel estimator outperforms the current state-of-the-arts in terms of performance.
基金supported by the Key Scientific Research Project in Colleges and Universities of Henan Province of China(Grant Nos.21A510003)Science and the Key Science and Technology Research Project of Henan Province of China(Grant Nos.222102210053)。
文摘Orthogonal time frequency space(OTFS)technique, which modulates data symbols in the delayDoppler(DD) domain, presents a potential solution for supporting reliable information transmission in highmobility vehicular networks. In this paper, we study the issues of DD channel estimation for OTFS in the presence of fractional Doppler. We first propose a channel estimation algorithm with both low complexity and high accuracy based on the unitary approximate message passing(UAMP), which exploits the structured sparsity of the effective DD domain channel using hidden Markov model(HMM). The empirical state evolution(SE) analysis is then leveraged to predict the performance of our proposed algorithm. To refine the hyperparameters in the proposed algorithm,we derive the update criterion for the hyperparameters through the expectation-maximization(EM) algorithm. Finally, Our simulation results demonstrate that our proposed algorithm can achieve a significant gain over various baseline schemes.
文摘An integrated sensing and communication(ISAC)scheme for a millimeter wave(mmWave)multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM)Vehicle-to-Infrastructure(V2I)system is presented,in which both the access point(AP)and the vehicle are equipped with large antenna arrays and employ hybrid analog and digital beamforming structures to compensate the path loss,meanwhile compromise between hardware complexity and system performance.Based on the sparse scattering nature of the mmWave channel,the received signal at the AP is organized to a four-order tensor by the introduced novel frame structure.A CANDECOMP/PARAFAC(CP)decomposition-based method is proposed for time-varying channel parameter extraction,including angles of departure/arrival(AoDs/AoAs),Doppler shift,time delay and path gain.Then leveraging the estimates of channel parameters,a nonlinear weighted least-square problem is proposed to recover the location accurately,heading and velocity of vehicles.Simulation results show that the proposed methods are effective and efficient in time-varying channel estimation and vehicle sensing in mmWave MIMOOFDM V2I systems.
文摘Orthogonal Time Frequency and Space(OTFS) modulation is expected to provide high-speed and ultra-reliable communications for emerging mobile applications, including low-orbit satellite communications. Using the Doppler frequency for positioning is a promising research direction on communication and navigation integration. To tackle the high Doppler frequency and low signal-to-noise ratio(SNR) in satellite communication, this paper proposes a Red and Blue Frequency Shift Discriminator(RBFSD) based on the pseudo-noise(PN) sequence.The paper derives that the cross-correlation function on the Doppler domain exhibits the characteristic of a Sinc function. Therefore, it applies modulation onto the Delay-Doppler domain using PN sequence and adjusts Doppler frequency estimation by red-shifting or blue-shifting. Simulation results show that the performance of Doppler frequency estimation is close to the Cramér-Rao Lower Bound when the SNR is greater than -15dB. The proposed algorithm is about 1/D times less complex than the existing PN pilot sequence algorithm, where D is the resolution of the fractional Doppler.
基金National S&T Project 2018YJS036.This study is supported in part by Key Laboratory of Universal Wireless Communications(BUPT),Ministry of Education,P.R.China(No.KFKT-2018104)by the Natural Science Foundation of China(NSFC,No.61571037,61871026,61961130391,and U1834210)+2 种基金NSFC Outstanding Youth(No.61725101)National Key R&D Program of China under Grant 2016YFE0200900the Royal Society Newton Advanced Fellowship under Grant NA191006.
文摘Channel estimation is a well-known challenge for wireless orthogonal frequency division multiplexing(OFDM)communication systems with massive antennas on high speed rails(HSRs).This paper investigates this problem and design two practicable uplink and downlink channel estimators for orthogonal frequency division multiplexing(OFDM)communication systems with massive antenna arrays at base station on HSRs.Specifically,we first use pilots to estimate the initial angle of arrival(AoA)and channel gain information of each uplink path through discrete Fourier transform(DFT),and then refine the estimates via the angle rotation technique and suggested pilot design.Based on the uplink angel estimation,we design a new downlink channel estimator for frequency division duplexing(FDD)systems.Additionally,we derive the Cramér-Rao lower bounds(CRLBs)of the AoA and channel gain estimates.Finally,numerical results are provided to corroborate our proposed studies.
文摘In this paper,we propose a joint channel estimation and symbol detection(JCESD)algorithm relying on message-passing algorithms(MPA)for orthogonal frequency division multiple access(OFDMA)systems.The channel estimation and symbol detection leverage the framework of expectation propagation(EP)and belief propagation(BP)with the aid of Gaussian approximation,respectively.Furthermore,to reduce the computation complexity involved in channel estimation,the matrix inversion is transformed into a series of diagonal matrix inversions through the Sherman-Morrison formula.Simulation experiments show that the proposed algorithm can reduce the pilot overhead by about 50%,compared with the traditional linear minimum mean square error(LMMSE)algorithm,and can approach to the bit error rate(BER)performance bound of perfectly known channel state information within 0.1 dB.
基金supported in part by National Natural Science Foundation of China(Grant Nos.61921003,61925101,61831002 and 61901315)in part by the Beijing Natural Science Foundation under(Grant No.JQ18016)in part by the Fundamental Research Funds for the Central Universities(Grant No.2020RC08).
文摘Reconfigurable intelligent surface(RIS)can manipulate the wireless propagation environment by smartly adjusting the amplitude/phase in a programmable panel,enjoying the improved performance.The accurate acquisition of the instantaneous channel state information(CSI)in the cascaded RIS chain makes an indispensable contribution to the performance gains.However,it is quite challenging to estimate the CSI in a time-variant scenario due to the limited signal processing capability of the passive elements embedded in a RIS pannel.In this work,a channel estimation scheme for the RIS-assisted wireless communication system is proposed,which is demonstrated to perform well in a time-variant scenario.The cascaded RIS channel is modeled as a state-space model based upon the mobility situations.In addition,to fully exploit the time correlation of channel,Kalman filter is employed by taking the prior information of channels into account.Further,the optimal reflection coefficients are derived according to the minimum mean square error(MMSE)criterion.Numerical results show that the proposed methods exhibit superior performance if compared with a conventional channel estimation scheme.
基金supported by the Natural Science Foundation of Chongqing(No.cstc2019jcyj-msxmX0017)。
文摘Since orthogonal time-frequency space(OTFS)can effectively handle the problems caused by Doppler effect in high-mobility environment,it has gradually become a promising candidate for modulation scheme in the next generation of mobile communication.However,the inter-Doppler interference(IDI)problem caused by fractional Doppler poses great challenges to channel estimation.To avoid this problem,this paper proposes a joint time and delayDoppler(DD)domain based on sparse Bayesian learning(SBL)channel estimation algorithm.Firstly,we derive the original channel response(OCR)from the time domain channel impulse response(CIR),which can reflect the channel variation during one OTFS symbol.Compare with the traditional channel model,the OCR can avoid the IDI problem.After that,the dimension of OCR is reduced by using the basis expansion model(BEM)and the relationship between the time and DD domain channel model,so that we have turned the underdetermined problem into an overdetermined problem.Finally,in terms of sparsity of channel in delay domain,SBL algorithm is used to estimate the basis coefficients in the BEM without any priori information of channel.The simulation results show the effectiveness and superiority of the proposed channel estimation algorithm.
基金Supported by the National Natural Science Foundation of China under Grant No.60572039
文摘A superimposed training （ST） based channel estimation method is presented that provides accurate estimation of a sparse underwater acoustic orthogonal frequency-division multiplexing （OFDM） channel while improving bandwidth transmission efficiency. A periodic low power training sequence is superimposed on the information sequence at the transmitter. The channel parameters can be estimated without consuming any extra system bandwidth, but an unknown information sequence can interfere with the ST channel estimation method, so in this paper, an iterative method was adopted to improve estimation performance. An underwater acoustic channel＇s properties include large channel dimensions and a sparse structure, so a matching pursuit （MP） algorithm was used to estimate the nonzero taps, allowing the performance loss caused by additive white Gaussian noise （AWGN） to be reduced. The results of computer simulations show that the proposed method has good channel estimation performance and can reduce the peak-to-average ratio of the OFDM channel as well.
基金supported in part by the National High Technology Research and Development Program of China(Grant No.2014AA01A707)the Beijing Natural Science Foundation(Grant No.4131003)+1 种基金the Specialized Research Fund for the Doctoral Program of Higher Education (SRFDP)(Grant No.20120005140002)the Key Program of Science and Technology Development Project of Beijing Municipal Education Commission of China (KZ201511232036)
文摘Relay in full-duplex(FD) mode can achieve higher spectrum efficiency than that in half-duplex mode,while it is crucial to suppress relay self-interference to ensure transmission quality which requires instantaneous channel state information(CSI). In this paper,the channel estimation issue in FD amplify-andforward relay networks is considered,where the training-based estimation technique is adopted. Firstly,the least square(LS) estimation is implemented to obtain composite channel coefficients of source-relay-destination(SRD) channel and relay loop-interference(LI) channel in order to assist destination in performing data detection. Secondly,both LS and maximum likelihood estimation methods are utilized to perform individual channel estimation aiming at supporting successive interference cancelation at destination. Finally,simulation results demonstrate the effectiveness of both composite and individual channel estimation,and the presented ML method can achieve lower MSEs than LS solution.
基金supported by National Natural Science Foundation of China (No. 62101601, No.61971445)。
文摘A joint Doppler shift and channel estimation method for the millimeter-wave communication system of an unmanned aerial vehicle(UAV) equipped with a large-scale uniform linear antenna(ULA) array has been proposed. Since Doppler shift induces intercarrier interference, the parameters of the channel paths have been decomposed into the Doppler shift and the channel information. In order to obtain the Doppler shift, a new estimation algorithm based on a combination of discrete Fourier transform and phase rotation has been proposed, which can determine the appropriate number of antennas. In addition to estimating the channel information, a low-complexity joint Doppler shift and channel estimation method has been designed that can quickly obtain accurate estimates. Furthermore, the achievable sum rate, the theoretical bounds of the mean squared errors, and the Cram?er-Rao lower bounds of the estimation method have been derived. The analysis and simulation results prove that the performance of the proposed approach is close to the theoretical inference.
基金supported by National Natural Science Foundation of China(No.61871452)。
文摘Orthogonal time frequency space(OTFS)modulation has been proven to be superior to traditional orthogonal frequency division multiplexing(OFDM)systems in high-speed communication scenarios.However,the existing channel estimation schemes may results in poor peak to average power ratio(PAPR)performance of OTFS system or low spectrum efficiency.Hence,in this paper,we propose a low PAPR channel estimation scheme with high spectrum efficiency.Specifically,we design a multiple scattered pilot pattern,where multiple low power pilot symbols are superimposed with data symbols in delay-Doppler domain.Furthermore,we propose the placement rules for pilot symbols,which can guarantee the low PAPR.Moreover,the data aided iterative channel estimation was invoked,where joint channel estimation is proposed by exploiting multiple independent received signals instead of only one received signal in the existing scheme,which can mitigate the interference imposed by data symbols for channel estimation.Simulation results shows that the proposed multiple scattered pilot aided channel estimation scheme can significantly reduce the PAPR while keeping the high spectrum efficiency.
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This work is supported in part by the National Natural Science Foundation of China under grants 61901403,61971366 and 61971365in part by the Youth Innovation Fund of Xiamen under grant 3502Z20206039in part by the Natural Science Foundation of Fujian Province of China under grant 2019J05001.
文摘The deep convolutional neural network(CNN)is exploited in this work to conduct the challenging channel estimation for mmWave massive multiple input multiple output(MIMO)systems.The inherent sparse features of the mmWave massive MIMO channels can be extracted and the sparse channel supports can be learnt by the multi-layer CNN-based network through training.Then accurate channel inference can be efficiently implemented using the trained network.The estimation accuracy and spectrum efficiency can be further improved by fully utilizing the spatial correlation among the sparse channel supports of different antennas.It is verified by simulation results that the proposed deep CNN-based scheme significantly outperforms the state-of-the-art benchmarks in both accuracy and spectrum efficiency.
