针对 IRS 辅助毫米波大规模 MIMO 的高维宽带信道估计难题,提出基于压缩感知的下行导频框架,结合分布式 OMP、公共稀疏性与冗余字典降低导频开销并提升估计性能。
摘要:
本文研究智能反射面(IRS)辅助的毫米波(mmWave)大规模 MIMO 系统的宽带信道估计(CE)。由于基站(BS)端的有源大规模 MIMO 和无源 IRS 均具有很大的维度,此类系统的信道估计是一项具有挑战性的任务。为解决该问题,本文针对 IRS 辅助的毫米波大规模 MIMO 系统提出了一种基于压缩感知(CS)的信道估计方案,利用毫米波频段大规模阵列的角度域信道稀疏性,以较低的导频开销改善信道估计。具体而言,本文首先提出一种下行导频传输框架。在利用视距主导的 BS 到 IRS 信道已知这一先验知识设计导频信号的基础上,可依据 CS 理论联合估计 BS 到用户以及 IRS 到用户的高维信道。此外,为高效估计宽带信道,采用了分布式正交匹配追踪算法,利用不同子载波上信道共享的公共稀疏性。另外,还设计了用于抑制功率泄漏的冗余字典,以增强信道估计性能。仿真结果验证了所提方案的有效性。
英文摘要:
This paper investigates the broadband channel estimation (CE) for intelligent reflecting surface (IRS)-aided millimeter-wave (mmWave) massive MIMO systems. The CE for such systems is a challenging task due to the large dimension of both the active massive MIMO at the base station (BS) and passive IRS. To address this problem, this paper proposes a compressive sensing (CS)-based CE solution for IRS-aided mmWave massive MIMO systems, whereby the angular channel sparsity of large-scale array at mmWave is exploited for improved CE with reduced pilot overhead. Specifically, we first propose a downlink pilot transmission framework. By designing the pilot signals based on the prior knowledge that the line-of-sight dominated BS-to-IRS channel is known, the high-dimensional channels for BS-to-user and IRS-to-user can be jointly estimated based on CS theory. Moreover, to efficiently estimate broadband channels, a distributed orthogonal matching pursuit algorithm is exploited, where the common sparsity shared by the channels at different subcarriers is utilized. Additionally, the redundant dictionary to combat the power leakage is also designed for the enhanced CE performance. Simulation results demonstrate the effectiveness of the proposed scheme.
Vision-aided wireless communication is motivated by the recent advances in deep learning and computer vision as well as the increasing dependence on line-of-sight links in millimeter wave (mmWave) and terahertz systems. By leveraging vision, this new research direction enables an interesting set of new capabilities such as vision-aided mmWave beam and blockage prediction, proactive hand-off, and resource allocation among others. These capabilities have the potential of reliably supporting highly-mobile applications such as vehicular/drone communications and wireless virtual/augmented reality i…
Generalized spatial modulation (GenSM) aided millimeter wave (mmWave) multiple-input multiple-output (MIMO) has recently received substantial academic attention. However, due to the insufficient exploitation of the transmitter's knowledge of the channel state information (CSI), the achievable rates of state-of-the-art GenSM-aided mmWave MIMO systems are far from being optimal. Against this background, a novel analog precoding scheme is proposed in this paper to improve the spectral efficiency (SE) of conventional GenSM-aided mmWave MIMOs. More specifically, we firstly manage to lower-bound the…
Location information offered by external positioning systems, e.g., satellite navigation, can be used as prior information in the process of beam alignment and channel parameter estimation for reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave) multiple-input multiple-output networks. Benefiting from the availability of such prior information, albeit imperfect, the beam alignment and channel parameter estimation processes can be significantly accelerated with less candidate beams explored at all the terminals. We propose a practical channel parameter estimation method via a…
Compressed Sensing (CS) based channel estimation techniques have recently emerged as an effective way to acquire the channel of millimeter-wave (mmWave) systems with a small number of measurements. These techniques, however, are based on prior knowledge of transmit and receive array manifolds, and assume perfect antenna arrays at both the transmitter and the receiver. In the presence of antenna imperfections, the geometry and response of the arrays are modified. This distorts the CS measurement matrix and results in channel estimation errors. This paper studies the effects of both transmit and…
A reconfigurable intelligent surface (RIS) can shape the radio propagation by passively changing the directions of impinging electromagnetic waves. The optimal control of the RIS requires perfect channel state information (CSI) of all the links connecting the base station (BS) and the mobile station (MS) via the RIS. Thereby the channel (parameter) estimation at the BS/MS and the related message feedback mechanism are needed. In this paper, we adopt a two-stage channel estimation scheme for the RIS-aided millimeter wave (mmWave) MIMO channels using an iterative reweighted method to sequentiall…
Intelligent reflecting surface (IRS) has been considered as a promising technology to alleviate the blockage effect and enhance coverage in millimeter wave (mmWave) communication. To explore the impact of IRS on the performance of mmWave communication, we investigate a multi-IRS assisted mmWave communication network and formulate a sum rate maximization problem by jointly optimizing the active and passive beamforming and the set of IRSs for assistance. The optimization problem is intractable due to the lack of convexity of the objective function and the binary nature of the IRS selection varia…
This paper presents an inertial sensor aided technique for beam alignment and tracking in massive multiple-input multiple-output (MIMO) vehicle-to-vehicle (V2V) communications based on millimeter waves (mmWave). Since directional communications in vehicular scenarios are severely hindered by beam pointing issues, a beam alignment procedure has to be periodically carried out to guarantee the communication reliability. When dealing with massive MIMO links, the beam sweeping approach is known to be time consuming and often unfeasible due to latency constraints. To speed up the process, we propose…
As communication systems that employ millimeter wave (mmWave) frequency bands must use large antenna arrays to overcome the severe propagation loss of mmWave signals, hybrid beamforming has been considered as an integral component of mmWave communications. Recently, intelligent reflecting surface (IRS) has been proposed as an innovative technology that can significantly improve the performance of mmWave communication systems through the use of low-cost passive reflecting elements. In this paper, we study IRS-aided mmWave multiple-input multiple-output (MIMO) systems with hybrid beamforming arc…
Relay-aided transmission is envisioned as a key strategy to combat severe path loss and link blockages emerging as unique challenges in millimeter-wave (mmWave) communications. This work considers a relay-aided multiuser mmWave communications scenario aiming at maximizing the sum rate through optimal transmit and relay precoder design. We propose a novel joint precoder design strategy, which exploits weighted minimum mean-square error (WMMSE) using its equivalency to sum-rate maximization. We obtain closed form expressions of transmit and relay precoders, and propose to compute them through al…
Millimeter wave (mmWave) massive multiple-input multiple-output (massive MIMO) is one of the most promising technologies for the fifth generation and beyond wireless communication system. However, a large number of antennas incur high power consumption and hardware costs, and high-frequency communications place a heavy burden on the analog-to-digital converters (ADCs) at the base station (BS). Furthermore, it is too costly to equipping each antenna with a high-precision ADC in a large antenna array system. It is promising to adopt low-resolution ADCs to address this problem. In this paper, we …
This paper proposes a reconfigurable intelligent surface (RIS)-aided and angular-based hybrid beamforming (AB-HBF) technique for the millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems. The proposed RIS-AB-HBF architecture consists of three stages: (i) RF beamformer, (ii) baseband (BB) precoder/combiner, and (iii) RIS phase shift design. First, in order to reduce the number of RF chains and the channel estimation overhead, RF beamformers are designed based on the 3D geometry-based mmWave channel model using slow time-varying angular parameters of the channel. Second,…
A fundamental challenge in millimeter-wave (mmWave) communication is the susceptibility to blocking objects. One way to alleviate this problem is the use of reconfigurable intelligent surfaces (RIS). Nevertheless, due to the large number of passive reflecting elements on RIS, channel estimation turns out to be a challenging task. In this paper, we address the channel estimation for RIS-aided mmWave communication systems based on a localization method. The proposed idea consists of exploiting the sparsity of the mmWave channel and the topology of the RIS. In particular, we first propose the con…
Millimeter-wave (mmWave) communication is one of the key enablers of the fifth-generation cellular networks (5G). However, one of the fundamental challenges of mmWave communication is the susceptibility to blockage effects. One way to alleviate this effect is the use of Intelligent Reflecting Surface (IRS). Nevertheless, due to the large number of the reflecting elements on IRS, the channel estimation turns out to be a challenging problem. This paper proposes a low-complexity channel information acquisition method for IRS-assisted mmWave communication system. Our idea consists in exploiting th…
This letter focuses on the secure transmission for an intelligent reflecting surface (IRS)-assisted millimeter-wave (mmWave) and terahertz (THz) systems, in which a base station (BS) communicates with its destination via an IRS, in the presence of a passive eavesdropper. To maximize the system secrecy rate, the transmit beamforming at the BS and the reflecting matrix at the IRS are jointly optimized with transmit power and discrete phase-shift constraints. It is first proved that the beamforming design is independent of the phase shift design under the rank-one channel assumption. The formulat…
This paper proposes a novel reconfigurable intelligent surface (RIS) architecture which enables channel estimation of RIS-assisted millimeter wave (mmWave) systems. More specifically, two channel estimation methods, namely, direct calculation (DC) and deep learning (DL) methods, are proposed to skillfully convert the overall channel estimation into two tasks: the channel estimation and the angle parameter estimation of a small number of active elements. In particular, the direct calculation method calculates the angle parameters directly through the channel estimates of adjacent active element…
In millimeter wave (mmWave) systems, it is challenging to ensure the reliable connectivity of communications due to its sensitivity to the presence of blockages. In order to improve the robustness of the mmWave system under the presence of the random blockages, multiple reconfigurable intelligent surfaces (RISs) are deployed to enhance the spatial diversity gain, and robust beamforming is then designed based on a stochastic optimization for minimizing the maximum outage probability among multiple users to ensure the fairness. Under the stochastic optimization framework, we adopt the stochastic…
In this letter, we propose a blockwise phase rotation-aided analog transmit beamforming (BPR-ATB) scheme to improve the spectral efficiency and the bit-error-rate (BER) performance in millimeter wave (mmWave) communication systems. Due to the phase angle optimization issues of the conventional analog beamforming, we design the BPR-ATB for reducing the rotated beamspace of the equivalent channel and improving the minimum Euclidean distance. To verify the effectiveness of the proposed BPR-ATB scheme, we employ an Alamouti coding technique at the transmitter and evaluate the bit-error-rate perfor…
Tsinghua University(清华大学);Beijing National Research Center for Information Science and Technology(北京信息科学与技术国家研究中心)
Hybrid beamforming is widely recognized as an important technique for millimeter wave (mmWave) multiple input multiple output (MIMO) systems. Generalized spatial modulation (GSM) is further introduced to improve the spectrum efficiency. However, most of the existing works on beamforming assume the perfect channel state information (CSI), which is unrealistic in practical systems. In this paper, joint optimization of downlink pilot training, channel estimation, CSI feedback, and hybrid beamforming is considered in GSM aided frequency division duplexing (FDD) mmWave MIMO systems. With the help o…
Millimeter wave (mmWave) full-duplex (FD) is a promising technique for improving capacity by maximizing the utilization of both time and the rich mmWave frequency resources. Still, it has restrictions due to FD self-interference (SI) and mmWave's limited coverage. Therefore, this study dives into FD mmWave MIMO with the assistance of reconfigurable intelligent surfaces (RIS) for capacity improvement. First, we demonstrate the angular-domain reciprocity of FD antenna arrays under the far-field planar wavefront assumption. Accordingly, a strategy for joint downlink-uplink (DL-UL) channel estimat…
In this letter, we investigate the robust and secure beamforming (RSBF) in an intelligent reflecting surface (IRS) aided millimeter wave (mmWave) multiple input single output (MISO) system, where multiple single antenna eavesdroppers (Eves) are arbitrarily distributed nearby the legitimate receiver. Considering the channel state information (CSI) of Eves' channels is imperfectly known at the legitimate transmitter, the RSBF design problems to maximize the worst case of achievable secrecy rate (ASR) are formulated under the total transmission power and unit-modulus constraints. Since the proble…
Due to the high cost and low energy efficiency of the dedicated radio frequency (RF) chains, the number of RF chains in a millimeter wave (mmWave) multiple-input multiple-output (MIMO) system is usually limited from a practical point of view. In this case, the maximum number of independent data streams is also restricted by the number of RF chains, which consequently leads to limiting the potentially attainable spatial multiplexing gain. In order to address this issue, in this paper, a novel generalized spatial modulation (GenSM) aided mmWave MIMO system is proposed, which enables the transmis…
The opening of the millimeter wave (mmWave) spectrum bands for 5G communications has motivated the need for novel spectrum sharing solutions at these high frequencies. In fact, reconfigurable intelligent surfaces (RISs) have recently emerged to enable spectrum sharing while enhancing the incumbents' quality-of-service (QoS). Nonetheless, co-existence over mmWave bands remains persistently challenging due to their unfavorable propagation characteristics. Hence, initiating mmWave spectrum sharing requires the RIS to further assist in improving the QoS over mmWave bands without jeopardizing spect…
A reconfigurable intelligent surface (RIS) can shape the radio propagation environment by virtue of changing the impinging electromagnetic waves towards any desired directions, thus, breaking the general Snell's reflection law. However, the optimal control of the RIS requires perfect channel state information (CSI) of the individual channels that link the base station (BS) and the mobile station (MS) to each other via the RIS. Thereby super-resolution channel (parameter) estimation needs to be efficiently conducted at the BS or MS with CSI feedback to the RIS controller. In this paper, we adop…
This paper presents the first machine learning based real-world demonstration for radar-aided beam prediction in a practical vehicular communication scenario. Leveraging radar sensory data at the communication terminals provides important awareness about the transmitter/receiver locations and the surrounding environment. This awareness could be utilized to reduce or even eliminate the beam training overhead in millimeter wave (mmWave) and sub-terahertz (THz) MIMO communication systems, which enables a wide range of highly-mobile low-latency applications. In this paper, we develop deep learning…
Line-of-sight link blockages represent a key challenge for the reliability and latency of millimeter wave (mmWave) and terahertz (THz) communication networks. This paper proposes to leverage LiDAR sensory data to provide awareness about the communication environment and proactively predict dynamic link blockages before they happen. This allows the network to make proactive decisions for hand-off/beam switching which enhances its reliability and latency. We formulate the LiDAR-aided blockage prediction problem and present the first real-world demonstration for LiDAR-aided blockage prediction in…
Millimeter wave (mmWave) communication is expected to play an important role in next generation cellular networks, aiming to cope with the bandwidth shortage affecting conventional wireless carriers. Using side-information has been proposed as a potential approach to accelerate beam selection in mmWave massive MIMO (m-MIMO) communications. However, in practice, such information is not error-free, leading to performance degradation. In the multi-user case, a wrong beam choice might result in irreducible inter-user interference at the base station (BS) side. In this paper, we consider location-a…
This work investigates the effect of double intelligent reflecting surface (IRS) in improving the spectrum efficient of multi-user multiple-input multiple-output (MIMO) network operating in the millimeter wave (mmWave) band. Specifically, we aim to solve a weighted sum rate maximization problem by jointly optimizing the digital precoding at the transmitter and the analog phase shifters at the IRS, subject to the minimum achievable rate constraint. To facilitate the design of an efficient solution, we first reformulate the original problem into a tractable one by exploiting the majorization-min…
Beijing Institute of Technology(北京理工大学);CNRS(法国国家科学研究中心);CentraleSupélec(中央理工-高等电力学院);Université Paris-Saclay(巴黎-萨克雷大学);King Abdullah University of Science and Technology(阿卜杜拉国王科技大学)
Integrating large intelligent reflecting surfaces (IRS) into millimeter-wave (mmWave) massive multi-input-multi-ouput (MIMO) has been a promising approach for improved coverage and throughput. Most existing work assumes the ideal channel estimation, which can be challenging due to the high-dimensional cascaded MIMO channels and passive reflecting elements. Therefore, this paper proposes a deep denoising neural network assisted compressive channel estimation for mmWave IRS systems to reduce the training overhead. Specifically, we first introduce a hybrid passive/active IRS architecture, where v…
This paper considers a reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave) downlink communication system where hybrid analog-digital beamforming is employed at the base station (BS). We formulate a power minimization problem by jointly optimizing hybrid beamforming at the BS and the response matrix at the RIS, under signal-to-interference-plus-noise ratio (SINR) constraints. The problem is highly challenging due to the non-convex SINR constraints as well as the non-convex unit-modulus constraints for both the phase shifts at the RIS and the analog beamforming at the BS. A p…
For unmanned aerial vehicle (UAV) aided millimeter wave (mmWave) networks, we propose a unified three-dimensional (3D) spatial framework in this paper to model a general case that uncovered users send messages to base stations via UAVs. More specifically, the locations of transceivers in downlink and uplink are modeled through the Poisson point processes and Poisson cluster processes (PCPs), respectively. For PCPs, Matern cluster and Thomas cluster processes, are analyzed. Furthermore, both 3D blockage processes and 3D antenna patterns are introduced for appraising the effect of altitudes. Bas…
Intelligent reflecting surfaces (IRSs) are regarded as promising enablers for future millimeter wave (mmWave) wireless communication, due to their ability to create favorable line-of-sight (LoS) propagation environments. In this paper, we investigate channel estimation in downlink IRS-assisted mmWave multiple-input multiple-output (MIMO) systems. By leveraging the sparsity of mmWave channels, we formulate the channel estimation problem as a fixed-rank constrained non-convex optimization problem. To tackle the non-convexity, an efficient algorithm is proposed by capitalizing on alternating mini…
The application of hybrid precoding in millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems has been proved effective for reducing the number of radio frequency (RF) chains. However, the maximum number of independent data streams is conventionally restricted by the number of RF chains, which leads to limiting the spatial multiplexing gain. To further improve the achievable spectral efficiency (SE), in this paper we propose a novel generalized spatial modulation (GenSM) aided mmWave MIMO system to convey an extra data stream via the index of the active antennas group, while no…
In this paper, we focus our attention on the mitigation of beam squint for reconfigurable intelligent surface (RIS) aided wideband millimeter wave (mmWave) communications. Due to the intrinsic passive property, the phase shifts of all elements in RIS should be the same for all frequencies. However, in the wideband scenario, beam squint induced distinct path phases require designing different phase shifts for different frequencies. The above irreconcilable contradiction will dramatically affect the system performance, considering the RIS usually consists of enormous elements and the bandwidth o…
To deal with the explosive growth of mobile traffic, millimeter-wave (mmWave) communications with abundant bandwidth resources have been applied to vehicular networks. As mmWave signal is sensitive to blockage, we introduce the unmanned aerial vehicle (UAV)-aided two-way relaying system for vehicular connection enhancement and coverage expansion. How to improve transmission efficiency and to reduce latency time in such a dynamic scenario is a challenging problem. In this paper, we formulate the joint optimization problem of relay selection and transmission scheduling, aiming to reduce transmis…
Hybrid analog-digital (A/D) transceivers designed for millimeter wave (mmWave) systems have received substantial research attention, as a benefit of their lower cost and modest energy consumption compared to their fully-digital counterparts. We further improve their performance by conceiving a Tomlinson-Harashima precoding (THP) based nonlinear joint design for the downlink of multiuser multiple-input multiple-output (MIMO) mmWave systems. Our optimization criterion is that of minimizing the mean square error (MSE) of the system under channel uncertainties subject both to realistic transmit po…
In this paper, we study the performance of wideband terahertz (THz) communications assisted by an intelligent reflecting surface (IRS). Specifically, we first introduce a generalized channel model that is suitable for electrically large THz IRSs operating in the near-field. Unlike prior works, our channel model takes into account the spherical wavefront of the emitted electromagnetic waves and the spatial-wideband effect. We next show that conventional frequency-flat beamfocusing significantly reduces the power gain due to beam squint, and hence is highly suboptimal. More importantly, we analy…
GPS-Aided Deep Learning for Beam Prediction and Tracking in UAV mmWave Communication
Department of Intelligent Mechatronics Engineering, and Department of Convergence Engineering for Intelligent Drone, Sejong University(智能机电工程系,智能无人机融合工程系,世宗大学)
In this paper, a downlink intelligent reflecting surface (IRS) enhanced millimeter-wave (mmWave) non-orthogonal multiple access (NOMA) system is considered. A joint optimization problem over active beamforming, passive beamforming and power allocation is formulated. Due to the highly coupled variables, the formulated optimization problem is non-convex. To solve this problem, an alternative optimization and successive convex approximation based iterative algorithm is proposed. Numerical results illustrate that: 1) the proposed scheme offers significant sum-rate gains, which confirms the effecti…
This paper investigates a novel research direction that leverages vision to help overcome the critical wireless communication challenges. In particular, this paper considers millimeter wave (mmWave) communication systems, which are principal components of 5G and beyond. These systems face two important challenges: (i) the large training overhead associated with selecting the optimal beam and (ii) the reliability challenge due to the high sensitivity to link blockages. Interestingly, most of the devices that employ mmWave arrays will likely also use cameras, such as 5G phones, self-driving vehi…
The problem of beam alignment and tracking in high mobility scenarios such as high-speed railway (HSR) becomes extremely challenging, since large overhead cost and significant time delay are introduced for fast time-varying channel estimation. To tackle this challenge, we propose a learning-aided beam prediction scheme for HSR networks, which predicts the beam directions and the channel amplitudes within a period of future time with fine time granularity, using a group of observations. Concretely, we transform the problem of high-dimensional beam prediction into a two-stage task, i.e., a low-d…
Current scene depth estimation approaches mainly rely on optical sensing, which carries privacy concerns and suffers from estimation ambiguity for distant, shiny, and transparent surfaces/objects. Reconfigurable intelligent surfaces (RISs) provide a path for employing a massive number of antennas using low-cost and energy-efficient architectures. This has the potential for realizing RIS-aided wireless sensing with high spatial resolution. In this paper, we propose to employ RIS-aided wireless sensing systems for scene depth estimation. We develop a comprehensive framework for building accurate…
Reducing computational complexity is crucial in optimizing the phase shifts of Intelligent Reflecting Surface (IRS) systems since IRS-assisted communication systems are generally deployed with a large number of reflecting elements (REs). This letter proposes a low-complexity algorithm, designated as Dimension-wise Sinusoidal Maximization (DSM), to obtain the optimal IRS phase shifts that maximize the sum capacity of a MIMO network. The algorithm exploits the fact that the objective function for the optimization problem is sinusoidal w.r.t. the phase shift of each RE. The numerical results show…
Intelligent reflecting surface (IRS) is a new promising technology that is able to manipulate the wireless propagation channel via smart and controllable signal reflection. In this paper, we investigate the capacity region of a multiple access channel (MAC) with two users sending independent messages to an access point (AP), aided by $M$ IRS reflecting elements. We consider two practical IRS deployment strategies that lead to different user-AP effective channels, namely, the distributed deployment where the $M$ reflecting elements form two IRSs, each deployed in the vicinity of one user, versu…
This paper investigates the achievable rate region of the multiple-input single-output (MISO) interference channel aided by intelligent reflecting surfaces (IRSs). We exploit the the additional design degree of freedom provided by the coordinated IRSs to enhance the desired signal and suppress interference so as to enlarge the achievable rate region of the interference channel. To this end, we jointly optimize the active transmit beamforming at the transmitters and passive reflective beamforming at the IRSs, subject to the constant modulus constraints of reflective beamforming vectors. To addr…
EURECOM(欧洲通信系统研究院);University of Surrey(萨里大学);Imperial College London(帝国理工学院)
Efficient millimeter wave (mmWave) beam selection in vehicle-to-infrastructure (V2I) communication is a crucial yet challenging task due to the narrow mmWave beamwidth and high user mobility. To reduce the search overhead of iterative beam discovery procedures, contextual information from light detection and ranging (LIDAR) sensors mounted on vehicles has been leveraged by data-driven methods to produce useful side information. In this paper, we propose a lightweight neural network (NN) architecture along with the corresponding LIDAR preprocessing, which significantly outperforms previous work…