This paper investigates the fundamental data detection problem with burst interference in massive multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) systems. In particular, burst inte...This paper investigates the fundamental data detection problem with burst interference in massive multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) systems. In particular, burst interference may occur only on data symbols but not on pilot symbols, which means that interference information cannot be premeasured. To cancel the burst interference, we first revisit the uplink multi-user system and develop a matrixform system model, where the covariance pattern and the low-rank property of the interference matrix is discussed. Then, we propose a turbo message passing based burst interference cancellation(TMP-BIC) algorithm to solve the data detection problem, where the constellation information of target data is fully exploited to refine its estimate. Furthermore, in the TMP-BIC algorithm, we design one module to cope with the interference matrix by exploiting its lowrank property. Numerical results demonstrate that the proposed algorithm can effectively mitigate the adverse effects of burst interference and approach the interference-free bound.展开更多
Enabling high mobility applications in millimeter wave(mmWave)based systems opens up a slew of new possibilities,including vehicle communi-cations in addition to wireless virtual/augmented reality.The narrow beam usag...Enabling high mobility applications in millimeter wave(mmWave)based systems opens up a slew of new possibilities,including vehicle communi-cations in addition to wireless virtual/augmented reality.The narrow beam usage in addition to the millimeter waves sensitivity might block the coverage along with the reliability of the mobile links.In this research work,the improvement in the quality of experience faced by the user for multimedia-related applications over the millimeter-wave band is investigated.The high attenuation loss in high frequencies is compensated with a massive array structure named Multiple Input and Multiple Output(MIMO)which is utilized in a hyperdense environment called heterogeneous networks(HetNet).The optimization problem which arises while maximizing the Mean Opinion Score(MOS)is analyzed along with the QoE(Quality of Experience)metric by considering the Base Station(BS)powers in addition to the needed Quality of Service(QoS).Most of the approaches related to wireless network communication are not suitable for the millimeter-wave band because of its problems due to high complexity and its dynamic nature.Hence a deep reinforcement learning framework is developed for tackling the same opti-mization problem.In this work,a Fuzzy-based Deep Convolutional Neural Net-work(FDCNN)is proposed in addition to a Deep Reinforcing Learning Framework(DRLF)for extracting the features of highly correlated data.The investigational results prove that the proposed method yields the highest satisfac-tion to the user by increasing the number of antennas in addition with the small-scale antennas at the base stations.The proposed work outperforms in terms of MOS with multiple antennas.展开更多
Massive multiple-input multiple-output(MIMO) system is capable of substantially improving the spectral efficiency as well as the capacity of wireless networks relying on equipping a large number of antenna elements at...Massive multiple-input multiple-output(MIMO) system is capable of substantially improving the spectral efficiency as well as the capacity of wireless networks relying on equipping a large number of antenna elements at the base stations. However, the excessively high computational complexity of the signal detection in massive MIMO systems imposes a significant challenge for practical hardware implementations. In this paper, we propose a novel minimum mean square error(MMSE) signal detection using the accelerated overrelaxation(AOR) iterative method without complicated matrix inversion, which is capable of reducing the overall complexity of the classical MMSE algorithm by an order of magnitude. Simulation results show that the proposed AOR-based method can approach the conventional MMSE signal detection with significant complexity reduction.展开更多
This paper presents a co-time co-frequency fullduplex(CCFD)massive multiple-input multiple-output(MIMO)system to meet high spectrum efficiency requirements for beyond the fifth-generation(5G)and the forthcoming the si...This paper presents a co-time co-frequency fullduplex(CCFD)massive multiple-input multiple-output(MIMO)system to meet high spectrum efficiency requirements for beyond the fifth-generation(5G)and the forthcoming the sixth-generation(6G)networks.To achieve equilibrium of energy consumption,system resource utilization,and overall transmission capacity,an energy-efficient resource management strategy concerning power allocation and antenna selection is designed.A continuous quantum-inspired termite colony optimization(CQTCO)algorithm is proposed as a solution to the resource management considering the communication reliability while promoting energy conservation for the CCFD massive MIMO system.The effectiveness of CQTCO compared with other algorithms is evaluated through simulations.The results reveal that the proposed resource management scheme under CQTCO can obtain a superior performance in different communication scenarios,which can be considered as an eco-friendly solution for promoting reliable and efficient communication in future wireless networks.展开更多
Location-based services have become an important part of the daily life.Fingerprint localization has been put forward to overcome the shortcomings of the traditional positioning algorithms in indoor scenario and rich ...Location-based services have become an important part of the daily life.Fingerprint localization has been put forward to overcome the shortcomings of the traditional positioning algorithms in indoor scenario and rich scattering environment.In this paper,a single-site multiple-input multiple-output(MIMO)orthogonal frequency division multiplexing(OFDM)system is modeled,from which an angle delay channel power matrix(ADCPM)is extracted.Considering the changing environment,auto encoders are used to generate new fingerprints based on ADCPM fingerprints to improve the robustness of the fingerprints.When the scattering environment has changed beyond a certain extent,the robustness will not be able to make up for the positioning error.Under this circumstance,an updating of the fingerprint database is imperative.A new fingerprint database updating algorithm which combines a new clustering method and an updating rule based on probability is proposed.Simulation results show the desirable performance of the proposed methods.展开更多
This paper addresses the problem of channel estimation in a multiuser multi-cell wireless communications system in which the base station(BS)is equipped with a very large number of antennas(also referred to as"ma...This paper addresses the problem of channel estimation in a multiuser multi-cell wireless communications system in which the base station(BS)is equipped with a very large number of antennas(also referred to as"massive multiple-input multiple-output(MIMO)").We consider a time-division duplexing(TDD)scheme,in which reciprocity between the uplink and downlink channels can be assumed.Channel estimation is essential for downlink beamforming in massive MIMO,nevertheless,the pilot contamination effect hinders accurate channel estimation,which leads to overall performance degradation.Benefitted from the asymptotic orthogonality between signal and interference subspaces for non-overlapping angle-of arrivals(AOAs)in the large-scale antenna system,we propose a multiple signals classification(MUSIC)based channel estimation algorithm during the uplink transmission.Analytical and numerical results verify complete pilot decontamination and the effectiveness of the proposed channel estimation algorithm in the multiuser multi-cell massive MIMO system.展开更多
Based on massive MIMO(multiple-input multiple-output)multipoint-to-multipoint(M2M) systems,in order to avoid pilot contamination and improve the performance of capacity,a pilot training transmission scheme was designe...Based on massive MIMO(multiple-input multiple-output)multipoint-to-multipoint(M2M) systems,in order to avoid pilot contamination and improve the performance of capacity,a pilot training transmission scheme was designed for pilot decontamination by utilizing orthogonal subcarriers of OFDM(orthogonal frequency division multiplexing) during pilot transmission phase and a joint optimized transceiver design for multi-antenna user pairs was proposed during the data transmission phase.The massive M2 M system included a single relay station,multiple paired source nodes and destination nodes.Source nodes precoding matrices and relay station precoding matrix were jointly optimized by maximizing the weighted sum-rate in OFDM systems.After some mathematical manipulation to sum-rate,the cost function of sum-rate was expressed as quadratic optimizing expressions which could be solved by regular convex optimization softwares.Different from existing algorithms,the proposed precoding design was based on massive MIMO OFDM systems with multi-antenna users pairs together pilot decontamination transmission arrangement.Simulations indicate the effectiveness of the proposed optimal precoding system.The proposed scheme not only can reduce pilot contamination,but also can improve performance of bit-error-rate(BER) as well as sumrate contrast to existing algorithms.In addition,it shows that the proposed M2 M massive MIMO system works steadily when the number of users increases in large scale.展开更多
The mobile data traffic has been exponentially growing during the last several decades.This was enabled by the densification of the network infrastructure in terms of increased cell density(i.e.,Ultra-Dense Network(UD...The mobile data traffic has been exponentially growing during the last several decades.This was enabled by the densification of the network infrastructure in terms of increased cell density(i.e.,Ultra-Dense Network(UDN))and/or the increased number of active antennas per Access Point(AP)(i.e.,massive Multiple-Input Multiple-Output(mMIMO)).However,neither UDN nor mMIMO will meet the increasing demand for the data rate of the Sixth Generation(6G)wireless communications due to the inter-cell interference and large quality-of-service variations.Cell-Free(CF)mMIMO,which combines the best aspects of UDN and mMIMO,is viewed as a key solution to this issue.In such systems,each User Equipment(UE)is served by a preferred set of surrounding APs cooperatively.In this paper,we provide a survey of the state-of-the-art literature on CF mMIMO.As a starting point,the significance and the basic properties of CF mMIMO are highlighted.We then present the canonical framework to discuss the essential details(i.e.,transmission procedure and mathematical system model).Next,we provide a deep look at the resource allocation and signal processing problems related to CF mMIMO and survey the up-to-date schemes and algorithms.After that,we discuss the practical issues in implementing CF mMIMO and point out the potential future directions.Finally,we conclude this paper with a summary of the key lessons learned in this field.展开更多
How to obtain accurate channel state information(CSI)at the transmitter with less pilot overhead for frequency division duplexing(FDD) massive multiple-input multiple-output(MIMO)system is a challenging issue due to t...How to obtain accurate channel state information(CSI)at the transmitter with less pilot overhead for frequency division duplexing(FDD) massive multiple-input multiple-output(MIMO)system is a challenging issue due to the large number of antennas. To reduce the overwhelming pilot overhead, a hybrid orthogonal and non-orthogonal pilot distribution at the base station(BS),which is a generalization of the existing pilot distribution scheme,is proposed by exploiting the common sparsity of channel due to the compact antenna arrangement. Then the block sparsity for antennas with hybrid pilot distribution is derived respectively and can be used to obtain channel impulse response. By employing the theoretical analysis of block sparse recovery, the total coherence criterion is proposed to optimize the sensing matrix composed by orthogonal pilots. Due to the huge complexity of optimal pilot acquisition, a genetic algorithm based pilot allocation(GAPA) algorithm is proposed to acquire optimal pilot distribution locations with fast convergence. Furthermore, the Cramer Rao lower bound is derived for non-orthogonal pilot-based channel estimation and can be asymptotically approached by the prior support set, especially when the optimized pilot is employed.展开更多
Pilot contamination can bring up a grave impairment in the performance of massive multiple-input multiple-output(MIMO)systems.In this paper,an improved time-shifted pilot scheme is proposed to reduce the pilot contami...Pilot contamination can bring up a grave impairment in the performance of massive multiple-input multiple-output(MIMO)systems.In this paper,an improved time-shifted pilot scheme is proposed to reduce the pilot contamination,where orthogonal pilots are employed in the same group to eliminate the residual intragroup interference existing in the original time-shifted pilot scheme.Meanwhile,the rigorous closed-form expressions of both downlink and uplink transmission rates with a finite number of antennas are derived,and it is shown that the intra-group interference can be completely eliminated by the proposed scheme.Simulation results demonstrate that both downlink and uplink transmission rates are significantly improved by employing the proposed scheme.展开更多
The increase in the number of devices with a massive revolution in mobile technology leads to increase the capacity of the wireless communications net-works. Multi-user Multiple-Input Multiple-Output is an advanced pr...The increase in the number of devices with a massive revolution in mobile technology leads to increase the capacity of the wireless communications net-works. Multi-user Multiple-Input Multiple-Output is an advanced procedure of Multiple-Input Multiple-Output, which improves the performance of Wireless Local Area Networks. Moreover, Multi-user Multiple-Input Multiple-Output leads the Wireless Local Area Networks toward covering more areas. Due to the growth of the number of clients and requirements, researchers try to improve the performance of the Medium Access Control protocol of Multi-user Multiple-Input Multiple-Output technology to serve the user better, by supporting different data sizes, and reducing the waiting time to be able to transmit data quickly. In this paper, we propose a Clustering Multi-user Multiple-Input Multiple-Output protocol, which is an improved Medium Access Control protocol for Multi-user Multiple-Input Multiple-Out-put based on MIMOMate clustering technique and Padovan Backoff Algorithm. Utilizing MIMOMMate focuses on the signal power which only serves the user in that cluster, minimizes the energy consumption and increases the capacity. The implementation of Clustering Multi-user Multiple-Input Multiple-Output performs on the Network Simulator (NS2.34) platform. The results show that Clustering Multi-user Multiple-Input Multiple-Output protocol improves the throughput by 89.8%, and reduces the latency of wireless communication by 43.9% in scenarios with contention. As a result, the overall performances of the network are improved.展开更多
Holographic multiple-input multiple-output(HMIMO)has become an emerging technology for achieving ultra-high frequency spectral efficiency and spatial resolution in future wireless systems.The increasing antenna apertu...Holographic multiple-input multiple-output(HMIMO)has become an emerging technology for achieving ultra-high frequency spectral efficiency and spatial resolution in future wireless systems.The increasing antenna aperture leads to a more significant characterization of the spherical wavefront in near-field communications in HMIMO scenarios.Beam training as a key technique for wireless communication is worth exploring in this near-field scenario.Compared with the widely researched far-field beam training,the increased dimensionality of the search space for near-field beam training poses a challenge to the complexity and accuracy of the proposed algorithm.In this paper,we introduce several typical near-field beam training methods:exhaustive beam training,hierarchical beam training,and multi-beam training that includes equal interval multi-beam training and hash multi-beam training.The performances of these methods are compared through simulation analysis,and their effectiveness is verified on the hardware testbed as well.Additionally,we provide application scenarios,research challenges,and potential future research directions for near-field beam training.展开更多
Asymmetric massive multiple-input multiple-output(MIMO)systems have been proposed to reduce the burden of data processing and hardware cost in sixth-generation mobile networks(6G).However,in the asymmetric massive MIM...Asymmetric massive multiple-input multiple-output(MIMO)systems have been proposed to reduce the burden of data processing and hardware cost in sixth-generation mobile networks(6G).However,in the asymmetric massive MIMO system,reciprocity between the uplink(UL)and downlink(DL)wireless channels is not valid.As a result,pilots are required to be sent by both the base station(BS)and user equipment(UE)to predict doubledirectional channels,which consumes more transmission and computational resources.In this paper we propose an ensemble-transfer-learning-based channel parameter prediction method for asymmetric massive MIMO systems.It can predict multiple DL channel parameters including path loss(PL),multipath number,delay spread(DS),and angular spread.Both the UL channel parameters and environment features are chosen to predict the DL parameters.Also,we propose a two-step feature selection algorithm based on the SHapley Additive exPlanations(SHAP)value and the minimum description length(MDL)criterion to reduce the computation complexity and negative impact on model accuracy caused by weakly correlated or uncorrelated features.In addition,the instance transfer method is introduced to support the prediction model in new propagation conditions,where it is difficult to collect enough training data in a short time.Simulation results show that the proposed method is more accurate than the back propagation neural network(BPNN)and the 3GPP TR 38.901 channel model.Additionally,the proposed instancetransfer-based method outperforms the method without transfer learning in predicting DL parameters when the beamwidth or the communication sector changes.展开更多
This paper first describes a binary Low-Density Parity-Check(LDPC)-coded Probabilistic Shaping(PS)scheme for Multiple-Input Multiple-Output(MIMO)systems based on Signal Space Diversity(SSD).Second,a Nonbinary(NB)LDPC-...This paper first describes a binary Low-Density Parity-Check(LDPC)-coded Probabilistic Shaping(PS)scheme for Multiple-Input Multiple-Output(MIMO)systems based on Signal Space Diversity(SSD).Second,a Nonbinary(NB)LDPC-coded PS scheme for MIMO systems based on SSD is proposed.The first scheme can be used to obtain a shaping gain,whereas the second can also realize a coding gain.The theoretical average mutual information of the optimized rotated quadrature amplitude modulation constellations is analyzed and the simulated error per-formance with 22 and 44 MIMO schemes is investigated.The theoretical average mutual information analysis and simulation results show that the proposed NB LDPC-coded PS scheme for MIMO systems based on SSD is reliable and robust,and is therefore suitable for future wireless communication systems.展开更多
多输入多输出(MIMO,Multiple-Input Multiple-Output)雷达用多个发射天线同时发射多个独立信号照射目标,并使用多个接收天线接收目标回波信号.本文研究了MIMO雷达中参数估计的稳健性问题.本文应用幅度相位估计(APES,Amplitude and Phase...多输入多输出(MIMO,Multiple-Input Multiple-Output)雷达用多个发射天线同时发射多个独立信号照射目标,并使用多个接收天线接收目标回波信号.本文研究了MIMO雷达中参数估计的稳健性问题.本文应用幅度相位估计(APES,Amplitude and Phase EStimation)技术,利用目标的方位角最大似然估计值,得到了衰落向量的APES估计算法.考虑到方位角估计的不准确性,借鉴稳健的Capon波束形成器的设计思想,本文推导了衰落向量的稳健的APES估计算法.仿真实验表明,衰落向量的APES算法与稳健的APES算法性能十分接近.因此,衰落向量的APES估计算法是稳健的.展开更多
Millimeter wave(mm Wave) has been claimed as the viable solution for high-bandwidth vehicular communications in 5 G and beyond. To realize applications in future vehicular communications, it is important to take a rob...Millimeter wave(mm Wave) has been claimed as the viable solution for high-bandwidth vehicular communications in 5 G and beyond. To realize applications in future vehicular communications, it is important to take a robust mm Wave vehicular network into consideration. However, one challenge in such a network is that mm Wave should provide an ultra-fast and high-rate data exchange among vehicles or vehicle-to-infrastructure(V2 I). Moreover,traditional real-time channel estimation strategies are unavailable because vehicle mobility leads to a fast variation mm Wave channel. To overcome these issues, a channel estimation approach for mm Wave V2 I communications is proposed in this paper. Specifically, by considering a fast-moving vehicle secnario, a corresponding mathematical model for a fast time-varying channel is first established. Then, the temporal variation rule between the base station and each mobile user and the determined direction-of-arrival are used to predict the time-varying channel prior information(PI). Finally, by exploiting the PI and the characteristics of the channel, the time-varying channel is estimated. The simulation results show that the scheme in this paper outperforms traditional ones in both normalized mean square error and sum-rate performance in the mm Wave time-varying vehicular system.展开更多
In this study,we consider a multi-cell millimeter-wave(mmWave)massive multiple-input multiple-output(MIMO)system with a mixed analog-to-digital converter(mixed-ADC)and hybrid beamforming architecture,in which antenna ...In this study,we consider a multi-cell millimeter-wave(mmWave)massive multiple-input multiple-output(MIMO)system with a mixed analog-to-digital converter(mixed-ADC)and hybrid beamforming architecture,in which antenna selection is applied to achieve intelligent assignment of high-and low-resolution ADCs.Both exact and approximate closed-form expressions for the uplink achievable rate are derived in the case of maximum-ratio combining reception.The impacts on the achievable rate of user transmit power,number of radio frequency chains at a base station,ratio of high-resolution ADCs,number of propagation paths,and number of quantization bits are analyzed.It is shown that the user transmit power can be scaled down inversely proportional to the number of antennas at the base station.We propose an efficient power allocation scheme by solving a complementary geometric programming problem.In addition,the energy efficiency is investigated,and an optimal tradeoff between the achievable rate and power consumption is discussed.Our results will provide a useful reference for the study of mixed-ADC multi-cell mmWave massive MIMO systems with antenna selection.展开更多
We propose a novel method for joint two-dimensional (2D) direction-of-arrival (DOA) and channel estimation with data detection for uniform rectangular arrays (URAs) for the massive multiple-input multiple-output (MIMO...We propose a novel method for joint two-dimensional (2D) direction-of-arrival (DOA) and channel estimation with data detection for uniform rectangular arrays (URAs) for the massive multiple-input multiple-output (MIMO) systems. The conventional DOA estimation algorithms usually assume that the channel impulse responses are known exactly. However, the large number of antennas in a massive MIMO system can lead to a challenge in estimating accurate corresponding channel impulse responses. In contrast, a joint DOA and channel estimation scheme is proposed, which first estimates the channel impulse responses for the links between the transmitters and antenna elements using training sequences. After that, the DOAs of the waves are estimated based on a unitary ESPRIT algorithm using previous channel impulse response estimates instead of accurate channel impulse responses and then, the enhanced channel impulse response estimates can be obtained. The proposed estimator enjoys closedform expressions, and thus it bypasses the search and pairing processes. In addition, a low-complexity approach toward data detection is presented by reducing the dimension of the inversion matrix in massive MIMO systems.Different cases for the proposed method are analyzed by changing the number of antennas. Experimental results demonstrate the validity of the proposed method.展开更多
基金supported by the National Key Laboratory of Wireless Communications Foundation,China (IFN20230204)。
文摘This paper investigates the fundamental data detection problem with burst interference in massive multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) systems. In particular, burst interference may occur only on data symbols but not on pilot symbols, which means that interference information cannot be premeasured. To cancel the burst interference, we first revisit the uplink multi-user system and develop a matrixform system model, where the covariance pattern and the low-rank property of the interference matrix is discussed. Then, we propose a turbo message passing based burst interference cancellation(TMP-BIC) algorithm to solve the data detection problem, where the constellation information of target data is fully exploited to refine its estimate. Furthermore, in the TMP-BIC algorithm, we design one module to cope with the interference matrix by exploiting its lowrank property. Numerical results demonstrate that the proposed algorithm can effectively mitigate the adverse effects of burst interference and approach the interference-free bound.
文摘Enabling high mobility applications in millimeter wave(mmWave)based systems opens up a slew of new possibilities,including vehicle communi-cations in addition to wireless virtual/augmented reality.The narrow beam usage in addition to the millimeter waves sensitivity might block the coverage along with the reliability of the mobile links.In this research work,the improvement in the quality of experience faced by the user for multimedia-related applications over the millimeter-wave band is investigated.The high attenuation loss in high frequencies is compensated with a massive array structure named Multiple Input and Multiple Output(MIMO)which is utilized in a hyperdense environment called heterogeneous networks(HetNet).The optimization problem which arises while maximizing the Mean Opinion Score(MOS)is analyzed along with the QoE(Quality of Experience)metric by considering the Base Station(BS)powers in addition to the needed Quality of Service(QoS).Most of the approaches related to wireless network communication are not suitable for the millimeter-wave band because of its problems due to high complexity and its dynamic nature.Hence a deep reinforcement learning framework is developed for tackling the same opti-mization problem.In this work,a Fuzzy-based Deep Convolutional Neural Net-work(FDCNN)is proposed in addition to a Deep Reinforcing Learning Framework(DRLF)for extracting the features of highly correlated data.The investigational results prove that the proposed method yields the highest satisfac-tion to the user by increasing the number of antennas in addition with the small-scale antennas at the base stations.The proposed work outperforms in terms of MOS with multiple antennas.
基金supported by the key project of the National Natural Science Foundation of China (No. 61431001)Huawei Innovation Research Program, the 5G research program of China Mobile Research Institute (Grant No. [2015] 0615)+2 种基金the open research fund of National Mobile Communications Research Laboratory Southeast University (No.2017D02)Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education (Guilin University of Electronic Technology)the Foundation of Beijing Engineering and Technology Center for Convergence Networks and Ubiquitous Services, and Keysight
文摘Massive multiple-input multiple-output(MIMO) system is capable of substantially improving the spectral efficiency as well as the capacity of wireless networks relying on equipping a large number of antenna elements at the base stations. However, the excessively high computational complexity of the signal detection in massive MIMO systems imposes a significant challenge for practical hardware implementations. In this paper, we propose a novel minimum mean square error(MMSE) signal detection using the accelerated overrelaxation(AOR) iterative method without complicated matrix inversion, which is capable of reducing the overall complexity of the classical MMSE algorithm by an order of magnitude. Simulation results show that the proposed AOR-based method can approach the conventional MMSE signal detection with significant complexity reduction.
基金supported by the Ph.D.Student Research and Innovation Fund of the Fundamental Research Funds for the Central Universities(3072020GIP0803)Heilongjiang Province Key Laboratory Fund of High Accuracy Satellite Navigation and Marine Application Laboratory(HKL-2020-Y01)+2 种基金the National Natural Science Foundation of China(61571149)the Initiation Fund for Postdoctoral Research in Heilongjiang Province(LBH-Q19098)the Key Laboratory of Advanced Marine Communication and Information Technology,Ministry of Industry and Information Technology。
文摘This paper presents a co-time co-frequency fullduplex(CCFD)massive multiple-input multiple-output(MIMO)system to meet high spectrum efficiency requirements for beyond the fifth-generation(5G)and the forthcoming the sixth-generation(6G)networks.To achieve equilibrium of energy consumption,system resource utilization,and overall transmission capacity,an energy-efficient resource management strategy concerning power allocation and antenna selection is designed.A continuous quantum-inspired termite colony optimization(CQTCO)algorithm is proposed as a solution to the resource management considering the communication reliability while promoting energy conservation for the CCFD massive MIMO system.The effectiveness of CQTCO compared with other algorithms is evaluated through simulations.The results reveal that the proposed resource management scheme under CQTCO can obtain a superior performance in different communication scenarios,which can be considered as an eco-friendly solution for promoting reliable and efficient communication in future wireless networks.
基金supported by Jiangsu Province Key Research and Development Program(BE2018704)Technical Innovation Project of The Ministry of Public Security(20170001)+1 种基金Fundamental Research Funds for the Central Universities(2242022k30001)National Science Foundation of China(CN)(Grant No.61871111).
文摘Location-based services have become an important part of the daily life.Fingerprint localization has been put forward to overcome the shortcomings of the traditional positioning algorithms in indoor scenario and rich scattering environment.In this paper,a single-site multiple-input multiple-output(MIMO)orthogonal frequency division multiplexing(OFDM)system is modeled,from which an angle delay channel power matrix(ADCPM)is extracted.Considering the changing environment,auto encoders are used to generate new fingerprints based on ADCPM fingerprints to improve the robustness of the fingerprints.When the scattering environment has changed beyond a certain extent,the robustness will not be able to make up for the positioning error.Under this circumstance,an updating of the fingerprint database is imperative.A new fingerprint database updating algorithm which combines a new clustering method and an updating rule based on probability is proposed.Simulation results show the desirable performance of the proposed methods.
文摘This paper addresses the problem of channel estimation in a multiuser multi-cell wireless communications system in which the base station(BS)is equipped with a very large number of antennas(also referred to as"massive multiple-input multiple-output(MIMO)").We consider a time-division duplexing(TDD)scheme,in which reciprocity between the uplink and downlink channels can be assumed.Channel estimation is essential for downlink beamforming in massive MIMO,nevertheless,the pilot contamination effect hinders accurate channel estimation,which leads to overall performance degradation.Benefitted from the asymptotic orthogonality between signal and interference subspaces for non-overlapping angle-of arrivals(AOAs)in the large-scale antenna system,we propose a multiple signals classification(MUSIC)based channel estimation algorithm during the uplink transmission.Analytical and numerical results verify complete pilot decontamination and the effectiveness of the proposed channel estimation algorithm in the multiuser multi-cell massive MIMO system.
基金National Natural Science Foundations of China(Nos.61505035,81470661,11604057)Science and Technology Project of Guangdong Province,China(No.2016A010101024)
文摘Based on massive MIMO(multiple-input multiple-output)multipoint-to-multipoint(M2M) systems,in order to avoid pilot contamination and improve the performance of capacity,a pilot training transmission scheme was designed for pilot decontamination by utilizing orthogonal subcarriers of OFDM(orthogonal frequency division multiplexing) during pilot transmission phase and a joint optimized transceiver design for multi-antenna user pairs was proposed during the data transmission phase.The massive M2 M system included a single relay station,multiple paired source nodes and destination nodes.Source nodes precoding matrices and relay station precoding matrix were jointly optimized by maximizing the weighted sum-rate in OFDM systems.After some mathematical manipulation to sum-rate,the cost function of sum-rate was expressed as quadratic optimizing expressions which could be solved by regular convex optimization softwares.Different from existing algorithms,the proposed precoding design was based on massive MIMO OFDM systems with multi-antenna users pairs together pilot decontamination transmission arrangement.Simulations indicate the effectiveness of the proposed optimal precoding system.The proposed scheme not only can reduce pilot contamination,but also can improve performance of bit-error-rate(BER) as well as sumrate contrast to existing algorithms.In addition,it shows that the proposed M2 M massive MIMO system works steadily when the number of users increases in large scale.
基金This work was supported in part by National Key R&D Program of China under Grant 2020YFB1807201in part by National Natural Science Foundation of China under Grants 61971027,U1834210,and 61961130391+2 种基金in part by Beijing Natural Science Foundation under Grant L202013in part by Frontiers Science Center for Smart High-speed Railway System under Grant 2020JBZD005in part by the Royal Society Newton Advanced Fellowship under Grant NA191006.E.Björnson was supported by the Grant 2019-05068 from the Swedish Research Council.
文摘The mobile data traffic has been exponentially growing during the last several decades.This was enabled by the densification of the network infrastructure in terms of increased cell density(i.e.,Ultra-Dense Network(UDN))and/or the increased number of active antennas per Access Point(AP)(i.e.,massive Multiple-Input Multiple-Output(mMIMO)).However,neither UDN nor mMIMO will meet the increasing demand for the data rate of the Sixth Generation(6G)wireless communications due to the inter-cell interference and large quality-of-service variations.Cell-Free(CF)mMIMO,which combines the best aspects of UDN and mMIMO,is viewed as a key solution to this issue.In such systems,each User Equipment(UE)is served by a preferred set of surrounding APs cooperatively.In this paper,we provide a survey of the state-of-the-art literature on CF mMIMO.As a starting point,the significance and the basic properties of CF mMIMO are highlighted.We then present the canonical framework to discuss the essential details(i.e.,transmission procedure and mathematical system model).Next,we provide a deep look at the resource allocation and signal processing problems related to CF mMIMO and survey the up-to-date schemes and algorithms.After that,we discuss the practical issues in implementing CF mMIMO and point out the potential future directions.Finally,we conclude this paper with a summary of the key lessons learned in this field.
基金supported by the National Natural Science Foundation of China(61671176 61671173)the Fundamental Research Funds for the Center Universities(HIT.MKSTISP.2016 13)
文摘How to obtain accurate channel state information(CSI)at the transmitter with less pilot overhead for frequency division duplexing(FDD) massive multiple-input multiple-output(MIMO)system is a challenging issue due to the large number of antennas. To reduce the overwhelming pilot overhead, a hybrid orthogonal and non-orthogonal pilot distribution at the base station(BS),which is a generalization of the existing pilot distribution scheme,is proposed by exploiting the common sparsity of channel due to the compact antenna arrangement. Then the block sparsity for antennas with hybrid pilot distribution is derived respectively and can be used to obtain channel impulse response. By employing the theoretical analysis of block sparse recovery, the total coherence criterion is proposed to optimize the sensing matrix composed by orthogonal pilots. Due to the huge complexity of optimal pilot acquisition, a genetic algorithm based pilot allocation(GAPA) algorithm is proposed to acquire optimal pilot distribution locations with fast convergence. Furthermore, the Cramer Rao lower bound is derived for non-orthogonal pilot-based channel estimation and can be asymptotically approached by the prior support set, especially when the optimized pilot is employed.
基金Supported by Beijing Natural Science Foundation(4194087)。
文摘Pilot contamination can bring up a grave impairment in the performance of massive multiple-input multiple-output(MIMO)systems.In this paper,an improved time-shifted pilot scheme is proposed to reduce the pilot contamination,where orthogonal pilots are employed in the same group to eliminate the residual intragroup interference existing in the original time-shifted pilot scheme.Meanwhile,the rigorous closed-form expressions of both downlink and uplink transmission rates with a finite number of antennas are derived,and it is shown that the intra-group interference can be completely eliminated by the proposed scheme.Simulation results demonstrate that both downlink and uplink transmission rates are significantly improved by employing the proposed scheme.
文摘The increase in the number of devices with a massive revolution in mobile technology leads to increase the capacity of the wireless communications net-works. Multi-user Multiple-Input Multiple-Output is an advanced procedure of Multiple-Input Multiple-Output, which improves the performance of Wireless Local Area Networks. Moreover, Multi-user Multiple-Input Multiple-Output leads the Wireless Local Area Networks toward covering more areas. Due to the growth of the number of clients and requirements, researchers try to improve the performance of the Medium Access Control protocol of Multi-user Multiple-Input Multiple-Output technology to serve the user better, by supporting different data sizes, and reducing the waiting time to be able to transmit data quickly. In this paper, we propose a Clustering Multi-user Multiple-Input Multiple-Output protocol, which is an improved Medium Access Control protocol for Multi-user Multiple-Input Multiple-Out-put based on MIMOMate clustering technique and Padovan Backoff Algorithm. Utilizing MIMOMMate focuses on the signal power which only serves the user in that cluster, minimizes the energy consumption and increases the capacity. The implementation of Clustering Multi-user Multiple-Input Multiple-Output performs on the Network Simulator (NS2.34) platform. The results show that Clustering Multi-user Multiple-Input Multiple-Output protocol improves the throughput by 89.8%, and reduces the latency of wireless communication by 43.9% in scenarios with contention. As a result, the overall performances of the network are improved.
文摘Holographic multiple-input multiple-output(HMIMO)has become an emerging technology for achieving ultra-high frequency spectral efficiency and spatial resolution in future wireless systems.The increasing antenna aperture leads to a more significant characterization of the spherical wavefront in near-field communications in HMIMO scenarios.Beam training as a key technique for wireless communication is worth exploring in this near-field scenario.Compared with the widely researched far-field beam training,the increased dimensionality of the search space for near-field beam training poses a challenge to the complexity and accuracy of the proposed algorithm.In this paper,we introduce several typical near-field beam training methods:exhaustive beam training,hierarchical beam training,and multi-beam training that includes equal interval multi-beam training and hash multi-beam training.The performances of these methods are compared through simulation analysis,and their effectiveness is verified on the hardware testbed as well.Additionally,we provide application scenarios,research challenges,and potential future research directions for near-field beam training.
基金Project supported by the National Key Research and Development Program of China(No.2020YFB1804901)the National Natural Science Foundation of China(Nos.62271051 and 61871035)。
文摘Asymmetric massive multiple-input multiple-output(MIMO)systems have been proposed to reduce the burden of data processing and hardware cost in sixth-generation mobile networks(6G).However,in the asymmetric massive MIMO system,reciprocity between the uplink(UL)and downlink(DL)wireless channels is not valid.As a result,pilots are required to be sent by both the base station(BS)and user equipment(UE)to predict doubledirectional channels,which consumes more transmission and computational resources.In this paper we propose an ensemble-transfer-learning-based channel parameter prediction method for asymmetric massive MIMO systems.It can predict multiple DL channel parameters including path loss(PL),multipath number,delay spread(DS),and angular spread.Both the UL channel parameters and environment features are chosen to predict the DL parameters.Also,we propose a two-step feature selection algorithm based on the SHapley Additive exPlanations(SHAP)value and the minimum description length(MDL)criterion to reduce the computation complexity and negative impact on model accuracy caused by weakly correlated or uncorrelated features.In addition,the instance transfer method is introduced to support the prediction model in new propagation conditions,where it is difficult to collect enough training data in a short time.Simulation results show that the proposed method is more accurate than the back propagation neural network(BPNN)and the 3GPP TR 38.901 channel model.Additionally,the proposed instancetransfer-based method outperforms the method without transfer learning in predicting DL parameters when the beamwidth or the communication sector changes.
基金supported in part by the Innovation and Technology Support Programme(ITSP)of the Innovation and Technology Commission(ITS/210/19)in part by the Young Scientists Fund of the National Natural Science Foundation of China(62001409)+1 种基金in part by Shenzhen-Hong Kong-Macao Science and Technology Project(Category C)(SGDX20210823104002018)in part by 2022 Guangdong-Hong Kong-Macao Joint Innovation Funding Scheme(2022A0505030021).
基金supported by Fundamental Research Program of Shanxi Province(202203021212159).
文摘This paper first describes a binary Low-Density Parity-Check(LDPC)-coded Probabilistic Shaping(PS)scheme for Multiple-Input Multiple-Output(MIMO)systems based on Signal Space Diversity(SSD).Second,a Nonbinary(NB)LDPC-coded PS scheme for MIMO systems based on SSD is proposed.The first scheme can be used to obtain a shaping gain,whereas the second can also realize a coding gain.The theoretical average mutual information of the optimized rotated quadrature amplitude modulation constellations is analyzed and the simulated error per-formance with 22 and 44 MIMO schemes is investigated.The theoretical average mutual information analysis and simulation results show that the proposed NB LDPC-coded PS scheme for MIMO systems based on SSD is reliable and robust,and is therefore suitable for future wireless communication systems.
文摘多输入多输出(MIMO,Multiple-Input Multiple-Output)雷达用多个发射天线同时发射多个独立信号照射目标,并使用多个接收天线接收目标回波信号.本文研究了MIMO雷达中参数估计的稳健性问题.本文应用幅度相位估计(APES,Amplitude and Phase EStimation)技术,利用目标的方位角最大似然估计值,得到了衰落向量的APES估计算法.考虑到方位角估计的不准确性,借鉴稳健的Capon波束形成器的设计思想,本文推导了衰落向量的稳健的APES估计算法.仿真实验表明,衰落向量的APES算法与稳健的APES算法性能十分接近.因此,衰落向量的APES估计算法是稳健的.
基金Project supported by the National Natural Science Foundation of China (No. 61971063)。
文摘Millimeter wave(mm Wave) has been claimed as the viable solution for high-bandwidth vehicular communications in 5 G and beyond. To realize applications in future vehicular communications, it is important to take a robust mm Wave vehicular network into consideration. However, one challenge in such a network is that mm Wave should provide an ultra-fast and high-rate data exchange among vehicles or vehicle-to-infrastructure(V2 I). Moreover,traditional real-time channel estimation strategies are unavailable because vehicle mobility leads to a fast variation mm Wave channel. To overcome these issues, a channel estimation approach for mm Wave V2 I communications is proposed in this paper. Specifically, by considering a fast-moving vehicle secnario, a corresponding mathematical model for a fast time-varying channel is first established. Then, the temporal variation rule between the base station and each mobile user and the determined direction-of-arrival are used to predict the time-varying channel prior information(PI). Finally, by exploiting the PI and the characteristics of the channel, the time-varying channel is estimated. The simulation results show that the scheme in this paper outperforms traditional ones in both normalized mean square error and sum-rate performance in the mm Wave time-varying vehicular system.
基金Project supported by the National Key R&D Program of China(No.2018YFB1801101)the National Natural Science Foundation of China(Nos.62071031 and 61960206006)+4 种基金the Beijing Municipal Natural Science Foundation,China(No.4212006)the Center of National Railway Intelligent Transportation System Engineering and Technology,China Academy of Railway Sciences(Nos.RITS2019KF01 and 2019YJ188)the Research Fund of the National Mobile Communications Research Laboratory,Southeast University,China(Nos.2020B01 and 2021D01)the Fundamental Research Funds for the Central Universities,China(No.2242020R30001)the Huawei Cooperation Project,China,and the EU H2020 RISE TESTBED2 Project(No.872172)。
文摘In this study,we consider a multi-cell millimeter-wave(mmWave)massive multiple-input multiple-output(MIMO)system with a mixed analog-to-digital converter(mixed-ADC)and hybrid beamforming architecture,in which antenna selection is applied to achieve intelligent assignment of high-and low-resolution ADCs.Both exact and approximate closed-form expressions for the uplink achievable rate are derived in the case of maximum-ratio combining reception.The impacts on the achievable rate of user transmit power,number of radio frequency chains at a base station,ratio of high-resolution ADCs,number of propagation paths,and number of quantization bits are analyzed.It is shown that the user transmit power can be scaled down inversely proportional to the number of antennas at the base station.We propose an efficient power allocation scheme by solving a complementary geometric programming problem.In addition,the energy efficiency is investigated,and an optimal tradeoff between the achievable rate and power consumption is discussed.Our results will provide a useful reference for the study of mixed-ADC multi-cell mmWave massive MIMO systems with antenna selection.
基金supported by Ericsson and the National Natural Science Foundation of China(No.61371075)
文摘We propose a novel method for joint two-dimensional (2D) direction-of-arrival (DOA) and channel estimation with data detection for uniform rectangular arrays (URAs) for the massive multiple-input multiple-output (MIMO) systems. The conventional DOA estimation algorithms usually assume that the channel impulse responses are known exactly. However, the large number of antennas in a massive MIMO system can lead to a challenge in estimating accurate corresponding channel impulse responses. In contrast, a joint DOA and channel estimation scheme is proposed, which first estimates the channel impulse responses for the links between the transmitters and antenna elements using training sequences. After that, the DOAs of the waves are estimated based on a unitary ESPRIT algorithm using previous channel impulse response estimates instead of accurate channel impulse responses and then, the enhanced channel impulse response estimates can be obtained. The proposed estimator enjoys closedform expressions, and thus it bypasses the search and pairing processes. In addition, a low-complexity approach toward data detection is presented by reducing the dimension of the inversion matrix in massive MIMO systems.Different cases for the proposed method are analyzed by changing the number of antennas. Experimental results demonstrate the validity of the proposed method.
