Channel estimation in wideband millimeter-wave (mmWave) systems is very challenging due to the beam squint effect. To solve the problem, we propose a learnable iterative shrinkage thresholding algorithm-based channel estimator (LISTA-CE) based on deep learning. The proposed channel estimator can learn to transform the beam-frequency mmWave channel into the domain with sparse features through training data. The transform domain enables us to adopt a simple denoiser with few trainable parameters. We further enhance the adaptivity of the estimator by introducing hypernetwork to automatically generate learnable parameters for LISTA-CE online. Simulation results show that the proposed approach can significantly outperform the state-of-the-art deep learning-based algorithms with lower complexity and fewer parameters and adapt to new scenarios rapidly.
Spatial wideband effects are known to affect channel estimation and localization performance in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems. Based on perturbation analysis, we show that the spatial wideband effect is in fact more pronounced than previously thought and significantly degrades performance, even at moderate bandwidths, if it is not properly considered in the algorithm design. We propose a novel channel estimation method based on multidimensional ESPRIT per subcarrier, combined with unsupervised learning for pairing across subcarriers, which shows…
We consider a wideband integrated access and backhaul system operating in full-duplex mode between the New Radio gNB donor and single user equipment. Due to high power consumption in millimeter wave systems, we use low-resolution analog-to-digital converters (ADCs) in the receivers. Our contributions include (1) hybrid beamformer to maximize sum spectral efficiency of the access and backhaul links by canceling self-interference and maximizing received power; (2) all-digital beamformer and upper bound on sum spectral efficiency; and (3) simulations to compare full vs. half duplex, finite vs. in…
Of the wide palette of 5G features, ultra-wide bandwidth and large-scale antenna configuration are regarded as the essential enabling technology components at millimeter wave (mmWave) communication. Accurate knowledge of delay and angle information of multipath components is essential for many applications in mmWave systems. There is a strong need for a low computation-cost channel estimation algorithm for such systems, where typically adopted far-field and narrowband assumptions might be violated. In this work, a generic yet novel beamspace uniform circular array (UCA) beamforming algorithm w…
Reconfigurable Intelligent Surfaces (RIS) are passive or semi-passive heterogeneous metasurfaces and consist of many tunable elements. RIS is gaining momentum as a promising new technology to enable transforming the propagation environment into controllable parameters. In this paper, we investigate the co-design of per-subcarrier power allocation matrices and multielement RIS phase shifts in downlink wideband MIMO transmission using 28 GHz frequency bands. Our contributions in improving RIS-aided links include (1) enhanced system modeling with pathloss and blockage modeling, and uniform rectan…
Recently, full duplex (FD) has been studied in 5G LTE millimeter wave (mmWave) cellular communications for New Radio in 3GPP releases 15-17. FD allows bidirectional transmission over the same resources and has the potential to reduce latency and double spectral efficiency. Self-interference (SI) is the primary drawback. SI can be several orders of magnitude greater than the received signal power, saturate the analog-to-digital converters (ADCs) and degrade communication performance severely. Massive mmWave antenna arrays may provide enough degrees of freedom for spatial multiplexing and SI sup…
Beamspace multi-input multi-output (MIMO) relying on lens antenna arrays can significantly reduce the number of radio-frequency chains in millimeter-wave (mmWave) communication systems through beam selection. However, the beamforming gain is actually frequency-dependent in wideband mmWave MIMO systems. This phenomenon is called beam squint, which will deteriorate the system's performance when traditional beam selection methods are used. To solve this problem, we propose a wideband beam selection method for mmWave MIMO systems relying on lens antenna arrays. Firstly, we select one beam with the…
In this letter, we investigate time-domain channel estimation for wideband millimeter wave (mmWave) MIMO OFDM system. By transmitting frequency-domain pilot symbols as well as different beamforming vectors, we observe that the time-domain mmWave MIMO channels exhibit channel delay sparsity and especially block sparsity among different spatial directions. Then we propose a time-domain channel estimation exploiting block sparsity (TDCEBS) scheme, which always aims at finding the best nonzero block achieving the largest projection of the residue at each iterations. In particular, we evaluate the …
Channel estimation is challenging for hybrid millimeter wave (mmWave) large-scale antenna arrays which are promising in 5G/B5G applications. The challenges are associated with angular resolution losses resulting from hybrid front-ends, beam squinting, and susceptibility to the receiver noises. Based on tensor signal processing, this paper presents a novel multi-dimensional approach to channel parameter estimation with large-scale mmWave hybrid uniform circular cylindrical arrays (UCyAs) which are compact in size and immune to mutual coupling but known to suffer from infinite-dimensional array …
In this article, we investigate channel estimation for wideband millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) under hybrid architecture with lowprecision analog-to-digital converters (ADCs). To design channel estimation for the hybrid structure, both analog processing components and frequency-selective digital combiners need to be optimized. The proposed channel estimator follows the typical linear-minimum-mean-square-error (LMMSE) structure and applies for an arbitrary channel model. Moreover, for sparsity channels as in mmWave, the proposed estimator performs more ef…
Channel estimation is challenging for the reconfigurable intelligence surface (RIS) assisted millimeter wave (mmWave) communications. Since the number of coefficients of the cascaded channels in such systems is closely dependent on the product of the number of base station antennas and the number of RIS elements, the pilot overhead would be prohibitively high. In this letter, we propose a cascaded channel estimation framework for an RIS assisted mmWave multiple-input multiple-output system, where the wideband effect on transmission model is considered. Then, we transform the wideband channel e…
In this paper, a channel estimator for wideband millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems with hybrid architectures and low-resolution analog-to-digital converters (ADCs) is proposed. To account for the propagation delay across the antenna array, which cannot be neglected in wideband mmWave massive MIMO systems, the discrete time channel that models the spatial wideband effect is developed. Also, the training signal design that addresses inter-frame, inter-user, and inter-symbol interferences is investigated when the spatial wideband effect is not negligibl…
In this paper, the fully corrective forward greedy selection-cross validation-based (FCFGS-CV-based) channel estimator is proposed for wideband millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems with low-resolution analog-to-digital converters (ADCs). The sparse nature of the mmWave virtual channel in the angular and delay domains is exploited to convert the maximum a posteriori (MAP) channel estimation problem to an optimization problem with a concave objective function and sparsity constraint. The FCFGS algorithm, which is the generalized orthogonal matching pursu…
Full-duplex (FD) systems have the capability to transmit and receive at the same time in the same frequency band. FD systems can reduce congestion and latency and improve coverage and spectral efficiency. As a relay, they can increase range and decrease outages. Full-duplex (FD) wireless systems have been emerging as a practical solution to provide high bandwidth, low latency, and big data processing in millimeter wave and Terahertz systems to support cellular networks, autonomous driving, platooning, advanced driving assistance and other systems. However, FD systems suffer from loopback self-…
In wideband millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems, channel estimation is challenging due to the hybrid analog-digital architecture, which compresses the received pilot signal and makes channel estimation a compressive sensing (CS) problem. However, existing high-performance CS algorithms usually suffer from high complexity. On the other hand, the beam squint effect caused by huge bandwidth and massive antennas will deteriorate estimation performance. In this paper, frequency-dependent angular dictionaries are first adopted to compensate for beam squint.…
In this article, we discuss the potential of radio frequency (RF) lens for ultra-wideband millimeter-wave (mmWave) systems. In terms of the beam squint, we compare the proposed RF lens antenna with the phase shifter-based array for hybrid beamforming. To reduce the complexities for fully digital beamforming, researchers have come up with RF lens-based hybrid beamforming. The use of mmWave systems, however, causes an increase in bandwidth, which gives rise to the beam squint phenomenon. We first find the causative factors for beam squint in the dielectric RF lens antenna. Based on the beamformi…
A major source of difficulty when operating with large arrays at mmWave frequencies is to estimate the wideband channel, since the use of hybrid architectures acts as a compression stage for the received signal. Moreover, the channel has to be tracked and the antenna arrays regularly reconfigured to obtain appropriate beamforming gains when a mobile setting is considered. In this paper, we focus on the problem of channel tracking for frequency-selective mmWave channels, and propose two novel channel tracking algorithms that leverage prior statistical information on the angles-of-arrival and an…
6G operators may use millimeter wave (mmWave) and sub-terahertz (sub-THz) bands to meet the ever-increasing demand for wireless access. Sub-THz communication comes with many existing challenges of mmWave communication and adds new challenges associated with the wider bandwidths, more antennas, and harsher propagations. Notably, the frequency- and spatial-wideband (dual-wideband) effects are significant at sub-THz. This paper presents a compressed training framework to estimate the time-varying sub-THz MIMO-OFDM channels. A set of frequency-dependent array response matrices are constructed, ena…
Reconfigurable intelligent surfaces (RISs) can establish favorable wireless environments to combat the severe attenuation and blockages in millimeter-wave (mmWave) bands. However, to achieve the optimal enhancement of performance, the instantaneous channel state information (CSI) needs to be estimated at the cost of a large overhead that scales with the number of RIS elements and the number of users. In this paper, we design a quasi-static broad coverage at the RIS with the reduced overhead based on the statistical CSI. We propose a design framework to synthesize the power pattern reflected by…
Hybrid analog-digital (HAD) architecture is widely adopted in practical millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems to reduce hardware cost and energy consumption. However, channel estimation in the context of HAD is challenging due to only limited radio frequency (RF) chains at transceivers. Although various compressive sensing (CS) algorithms have been developed to solve this problem by exploiting inherent channel sparsity and sparsity structures, practical effects, such as power leakage and beam squint, can still make the real channel features deviate from…
Millimeter-wave (mmWave) communications have been one of the promising technologies for future wireless networks that integrate a wide range of data-demanding applications. To compensate for the large channel attenuation in mmWave band and avoid high hardware cost, a lens-based beamspace massive multiple-input multiple-output (MIMO) system is considered. However, the beam squint effect in wideband mmWave systems makes channel estimation very challenging, especially when the receiver is equipped with a limited number of radio-frequency (RF) chains. Furthermore, the real channel data cannot be o…
Beamforming technology is widely used in millimeter wave systems to combat path losses, and beamformers are usually selected from a predefined codebook. Unfortunately, the traditional codebook design neglects the beam squint effect, and this will cause severe performance degradation when the bandwidth is large. In this letter, we consider that a codebook with fixed size is adopted in the wideband beamforming system. First, we analyze how beam squint affects system performance when all beams have the same width. The expression of average spectrum efficiency is derived based on the ideal beam pa…
The large beamforming gain used to operate at millimeter wave (mmWave) frequencies requires obtaining channel information to configure hybrid antenna arrays. Previously proposed wideband channel estimation strategies, however, assume perfect time-frequency synchronization and neglect phase noise, making these approaches impractical. Consequently, achieving time-frequency synchronization between transmitter and receiver and correcting for phase noise (PN) as the channel is estimated, is the greatest challenge yet to be solved in order to configure hybrid precoders and combiners in practical set…
Traditional beam tracking methods have severe performance loss under the high mobility and narrow beam scenario. To alleviate the tracking performance degradation, we propose an adaptive beamwidth control for millimeter wave (mmWave) beam tracking. The particle filter is applied to the beam tracking, and the AoA estimation error is approximated with a posterior density function constructed by the particles. The error approximation leads to the adaptive beamwidth control which is implemented by the partial activation of the antenna array. Simulation results show that the proposed algorithm aids…
Low overhead channel estimation based on compressive sensing (CS) has been widely investigated for hybrid wideband millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems. The channel sparsifying dictionaries used in prior work are built from ideal array response vectors evaluated on discrete angles of arrival/departure. In addition, these dictionaries are assumed to be the same for all subcarriers, without considering the impacts of hardware impairments and beam squint. In this manuscript, we derive a general channel and signal model that explicitly incorporates the impacts of …
Millimeter-wave (mmWave) systems use directional beams to support high-rate data communications. Small misalignment between the transmit and receive beams (e.g., due to the mobility) can result in significant drop of the received signal quality especially in line-of-sight communication channels. In this paper, we propose and evaluate high-resolution angle tracking strategies for wideband mmWave systems with mobility. We custom design pairs of auxiliary beams as the tracking beams, and use them to capture the angle variations, towards which the steering directions of the data beams are adjusted…
Millimeter wave (mmWave) technologies will support the high bandwidth and data rate requirements of V2X services demanded by connected and automated vehicles (CAVs). MmWave V2X technologies will leverage directional antennas that challenge the management of the communications in dynamic scenarios including the identification of available links, beams alignment, and scheduling. Previous studies have shown that these challenges can be reduced when mmWave communications are supported by side information like the one transmitted in sub-6GHz V2X technologies. In this context, this paper proposes a …
The concept of reconfigurable intelligent surface (RIS) has been proposed to change the propagation of electromagnetic waves, e.g., reflection, diffraction, and refraction. To accomplish this goal, the phase values of the discrete RIS units need to be optimized. In this paper, we consider RIS-aided millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems for both accurate positioning and high data-rate transmission. We propose an adaptive phase shifter design based on hierarchical codebooks and feedback from the mobile station (MS). The benefit of the scheme lies in that the RIS …
Communication at high carrier frequencies such as millimeter wave (mmWave) and terahertz (THz) requires channel estimation for very large bandwidths at low SNR. Hence, allocating an orthogonal pilot tone for each coherence bandwidth leads to excessive number of pilots. We leverage generative adversarial networks (GANs) to accurately estimate frequency selective channels with few pilots at low SNR. The proposed estimator first learns to produce channel samples from the true but unknown channel distribution via training the generative network, and then uses this trained network as a prior to est…
This paper investigates the hybrid precoding design in millimeter-wave (mmWave) systems with a fully-adaptive-connected precoding structure, where a switch-controlled connection is deployed between every antenna and every radio frequency (RF) chain. To maximally enhance the energy efficiency (EE) of hybrid precoding under this structure, the joint optimization of switch-controlled connections and the hybrid precoders is formulated as a large-scale mixed-integer non-convex problem with high-dimensional power constraints. To efficiently solve such a challenging problem, we first decouple it into…
In this work, we present a framework analysis of full-duplex (FD) systems for Millimeter Wave (mmWave) analog architecture. Given that FD systems can double the ergodic capacity, such systems experience large losses caused by the loopback self-interference (SI). In addition, systems with analog architecture also suffer from other forms of losses mainly incurred by the constant amplitude (CA) constraint. For this purpose, we propose the projected Gradient Ascent algorithm to maximize the sum rate under the unit-norm and CA constraints. Unlike previous works, our approach achieves the best spect…
Millimeter-wave (mmWave) multiple-input multiple-out (MIMO) systems relying on lens antenna arrays are capable of achieving a high antenna-gain at a considerably reduced number of radio frequency (RF) chains via beam selection. However, the traditional beam selection network suffers from significant performance loss in wideband systems due to the effect of beam squint. In this paper, we propose a phase shifter-aided beam selection network, which enables a single RF chain to support multiple focused-energy beams, for mitigating the beam squint in wideband mmWave MIMO systems. Based on this arch…
We present a beamforming algorithm for multiuser wideband millimeter wave (mmWave) communication systems where one access point uses hybrid analog/digital beamforming while multiple user stations have phased-arrays with a single RF chain. The algorithm operates in a more general mode than others available in literature and has lower computational complexity and training overhead. Throughout the paper, we describe: i) the construction of novel beamformer sets (codebooks) with wide sector beams and narrow beams based on the orthogonality property of beamformer vectors, ii) a beamforming algorith…
This paper presents a spectral attention-driven reinforcement learning based intelligent method for effective and efficient detection of important signals in a wideband spectrum. In the work presented in this paper, it is assumed that the modulation technique used is available as a priori knowledge of the targeted important signal. The proposed spectral attention-driven intelligent method is consists of two main components, a spectral correlation function (SCF) based spectral visualization scheme and a spectral attention-driven reinforcement learning mechanism that adaptively selects the spect…
Wide swaths of bandwidth at millimeter-wave (mmWave) and Terahertz (THz) frequencies stimulate diverse applications in wireless sensing, imaging, position location, cloud computing, and much more. These emerging applications motivate wireless communications hardware to operate with multi Gigahertz (GHz) bandwidth, at nominal costs, minimal size, and power consumption. Channel sounding system implementations currently used to study and measure wireless channels utilize numerous commercially available components from multiple manufacturers that result in a complex and large assembly with many co…
Photonics-assisted analog wideband self-interference cancellation for in-band full-duplex MIMO systems with adaptive digital amplitude and delay pre-matching
We propose sparsity-adaptive beamspace channel estimation algorithms that improve accuracy for 1-bit data converters in all-digital millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) basestations. Our algorithms include a tuning stage based on Stein's unbiased risk estimate (SURE) that automatically selects optimal denoising parameters depending on the instantaneous channel conditions. Simulation results with line-of-sight (LoS) and non-LoS mmWave massive MIMO channel models show that our algorithms improve channel estimation accuracy with 1-bit measurements in a computatio…
Southern Methodist University（南卫理公会大学）；Hunan Normal University（湖南师范大学）
In this paper, we propose a phase shift deep neural network (PhaseDNN) which provides a wideband convergence in approximating a high dimensional function during its training of the network. The PhaseDNN utilizes the fact that many DNN achieves convergence in the low frequency range first, thus, a series of moderately-sized of DNNs are constructed and trained in parallel for ranges of higher frequencies. With the help of phase shifts in the frequency domain, implemented through a simple phase factor multiplication on the training data, each DNN in the series will be trained to approximate the t…
