Intelligent reflecting surface (IRS) is an emerging technology for future wireless communications including 5G and especially 6 G. It consists of a large 2D array of (semi-)passive scattering elements that control the electromagnetic properties of radio-frequency waves so that the reflected signals add coherently at the intended receiver or destructively to reduce co-channel interference. The promised gains of IRS-assisted communications depend on the accuracy of the channel state information. In this paper, we address the receiver design for an IRS-assisted multiple-input multiple-output (MIMO) communication system via a tensor modeling approach aiming at the channel estimation problem using supervised (pilot-assisted) methods. Considering a structured time-domain pattern of pilots and IRS phase shifts, we present two channel estimation methods that rely on a parallel factor (PARAFAC) tensor modeling of the received signals. The first one has a closed-form solution based on a Khatri-Rao factorization of the cascaded MIMO channel, by solving rank-1 matrix approximation problems, while the second on is an iterative alternating estimation scheme. The common feature of both methods is the decoupling of the estimates of the involved MIMO channel matrices (base station-IRS and IRS-user terminal), which provides performance enhancements in comparison to competing methods that are based on unstructured LS estimates of the cascaded channel. Design recommendations for both methods that guide the choice of the system parameters are discussed. Numerical results show the effectiveness of the proposed receivers, highlight the involved trade-offs, and corroborate their superior performance compared to competing LS-based solutions.

Channel Estimation for Intelligent Reflecting Surface Assisted MIMO Systems: A Tensor Modeling Approach

The demanding objectives for the future sixth generation (6G) of wireless communication networks have spurred recent research efforts on novel materials and radio-frequency front-end architectures for wireless connectivity, as well as revolutionary communication and computing paradigms. Among the pioneering candidate technologies for 6G belong the reconfigurable intelligent surfaces (RISs), which are artificial planar structures with integrated electronic circuits that can be programmed to manipulate the incoming electromagnetic field in a wide variety of functionalities. Incorporating RISs in wireless networks has been recently advocated as a revolutionary means to transform any wireless signal propagation environment to a dynamically programmable one, intended for various networking objectives, such as coverage extension and capacity boosting, spatiotemporal focusing with benefits in energy efficiency and secrecy, and low electromagnetic field exposure. Motivated by the recent increasing interests in the field of RISs and the consequent pioneering concept of the RIS-enabled smart wireless environments, in this paper, we overview and taxonomize the latest advances in RIS hardware architectures as well as the most recent developments in the modeling of RIS unit elements and RIS-empowered wireless signal propagation. We also present a thorough overview of the channel estimation approaches for RIS-empowered communications systems, which constitute a prerequisite step for the optimized incorporation of RISs in future wireless networks. Finally, we discuss the relevance of the RIS technology in the latest wireless communication standards, and highlight the current and future standardization activities for the RIS technology and the consequent RIS-empowered wireless networking approaches.

Reconfigurable Intelligent Surfaces for Wireless Communications: Overview of Hardware Designs, Channel Models, and Estimation Techniques

The demanding objectives for the future sixth generation (6G) of wireless communication networks have spurred recent research efforts on novel materials and radio-frequency front-end architectures for wireless connectivity, as well as revolutionary communication and computing paradigms. Among the pioneering candidate technologies for 6G belong the reconfigurable intelligent surfaces (RISs), which are artificial planar structures with integrated electronic circuits that can be programmed to manipulate the incoming electromagnetic field in a wide variety of functionalities. Incorporating RISs in wireless networks have been recently advocated as a revolutionary means to transform any wireless signal propagation environment to a dynamically programmable one, intended for various networking objectives, such as coverage extension and capacity boosting, spatiotemporal focusing with benefits in energy efficiency and secrecy, and low electromagnetic field exposure. Motivated by the recent increasing interests in the field of RISs and the consequent pioneering concept of the RIS-enabled smart wireless environments, in this paper, we overview and taxonomize the latest advances in RIS hardware architectures as well as the most recent developments in the modeling of RIS unit elements and RIS-empowered wireless signal propagation. We also present a thorough overview of the channel estimation approaches for RIS-empowered communications systems, which constitute a prerequisite step for the optimized incorporation of RISs in future wireless networks. Finally, we discuss the relevance of the RIS technology in the latest wireless communication standards, and highlight the current and future standardization activities for the RIS technology and the consequent RIS-empowered wireless networking approaches. 

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Reconfigurable intelligent surfaces for wireless communications: Overview of hardware designs, channel models, and estimation techniques

Unmanned Aerial Vehicle (UAV)-enabled communication platform is recognized as a promising way for secure transmission in the air-to-air and air-to-ground (A2G) networks. However, the jitter feature of UAV platform due to the absence of fixed infrastructure, the inherent randomness of airflow, and the body vibration introduces non-negligible impact on establishing robust and energy-efficient secure communication links. In this paper, we investigate energy-saving and secure transmission in a downlink A2G wiretap system considering the impact of UAV jitter. Particularly, in order to minimize the total transmission power of UAV-mounted base station, a joint beamforming optimization of confidential signal and artificial noise signal is formulated with the constraints for secrecy performance of the worst scenario. Specifically, considering the impact of UAV jittering on the antenna array response, the worst scenario indicates the A2G wiretap system with the minimum legitimate data rate and the maximum eavesdropping data rate. The non-convex problem is then reformulated with linear approximation for the channel variations and linear matrix inequality alternation for the constraints. Then, semidefinite programming relaxation is adopted to obtain the optimal solutions for the reformulated problem. Furthermore, the problem and solution are extended to the multiuser downlink wiretap system. Finally, numerical results are provided to demonstrate the impact of key system parameters on power saving under the secure transmission constraints and the UAV jitter.

Energy-Efficient and Secure Air-to-Ground Communication With Jittering UAV

Wireless transceivers for mass-market applications must be cost effective. We may achieve this goal by deploying non-ideal low-cost radio frequency (RF) analog components. However, their imperfections may result in RF impairments, including phase noise (PN), carrier frequency offset (CFO), and in-phase (I) and quadrature-phase (Q) imbalance. These impairments introduce in-band and out-of-band interference terms and degrade the performance of wireless systems. In this survey, we present RF-impairment signal models and discuss their impacts. Moreover, we review RF-impairment estimation and compensation in single-carrier (SC) and multicarrier systems, especially orthogonal frequency division multiplexing (OFDM). Furthermore, we discuss the effects of the RF impairments in already-established wireless technologies, e.g., multiple-input multiple-output (MIMO), massive MIMO, full-duplex, and millimeter-wave communications and review existing estimation and compensation algorithms. Finally, future research directions investigate the RF impairments in emerging technologies, including cell-free massive MIMO communications, non-orthogonal multicarrier systems, non-orthogonal multiple access (NOMA), ambient backscatter communications, and intelligent reflecting surface (IRS)-assisted communications. Furthermore, we discuss artificial intelligence (AI) approaches for developing estimation and compensation algorithms for RF impairments.

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RF Impairments in Wireless Transceivers: Phase Noise, CFO, and IQ Imbalance – A Survey

In this paper, two techniques to compensate inphase/quadrature-phase imbalance (IQI) are investigated in the uplink-quantized massive multiple-input and multiple-output (MIMO) systems for different models of randomized IQI parameters. One is referred to as combined-signal-based channel estimation and compensation (CCEC) and the other is denoted by effective channel estimation and compensation (ECEC). First, an independent automatic gain control (AGC) scheme is proposed to calibrate the dynamic range of both the I branch and the Q branch. By doing that, different quantization steps are used for analog-to-digital converters following the AGCs in these two branches at each receive antenna. Second, considering the impacts of both quantization and IQI, we give the details of channel estimation and IQI compensation for both the CCEC and the ECEC using bilinear generalized approximate message passing (Bi-GAMP). Moreover, to exploit the Bi-GAMP for ECEC reasonably, we theoretically derive the probability density function PDF of the elements in the effective channel for the case where only RX IQI is considered. Furthermore, we extend the ECEC to the case where both RX IQI and TX IQI are incorporated into the systems and derive the similar pdf as well. Finally, we use the numerical results to testify the validity of our theoretical analysis and the fact that the analytic PDF can be approximated by a Gaussian distribution when the IQI parameters are relatively small. Compared with other classical methods, the proposed methods can obtain better performance based on the Monte Carlo simulation results.

Channel Estimation and IQ Imbalance Compensation for Uplink Massive MIMO Systems With Low-Resolution ADCs

In this paper, we study secure cooperative transmission for the multiple-input-single-output multiple-eavesdropper (MISOME) systems, where a source (Alice) aims to send confidential messages to a legitimate user (Bob) with the aid of an unmanned aerial vehicle (UAV) enabled friendly jammer (Charlie) in the presence of multiple eavesdroppers (Eves). To further guarantee the secrecy performance, artificial noise (AN) beamforming together with cooperative Jamming (CJ) has been utilized in this considered system with only location and statistical channel state information of the Eves. Specifically, taking imperfect channel state information (CSI) between Charlie and Bob into account, we derive the exact closed-form expression of the secrecy outage probability (SOP) and develop an efficient scheme to solve the secrecy rate maximization (SRM) problem which has been verified as a convex one under certain SOP. Moreover, we propose an optimal UAV placement strategy to further enhance secrecy performance. The numerical results are provided to validate that the system security would seriously degenerate with channel uncertainty. Besides, the proposed scheme is verified to outperform the terrestrial CJ scheme in improving the secrecy rate and secure energy efficiency (EE) performance under perfect CSI or tolerable channel estimation errors. Finally, the effectiveness of the proposed UAV placement strategy in enhancing transmission security and the applicability of the proposed scheme has also been demonstrated.

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UAV-Aided Secure Transmission in MISOME Wiretap Channels With Imperfect CSI

In this paper, we analyze the performance of uplink massive multiple‐input–multiple‐output (MIMO) systems with variable‐resolution analog‐to‐digital converters (ADCs), ie, each receive ant...

Performance analysis of uplink massive MIMO systems with variable‐resolution ADCs using MMSE and MRC detection

In this paper, we consider a reconfigurable intelligent surface (RIS) aided millimeter wave (mmWave) multiple-input multiple-output (MIMO) system. The system can obtain the huge gain via joint active beamforming at the base station (BS) and passive beamforming at the RIS. However, due to weather and atmospheric effects, outdoor RIS antenna elements are subject to full or partial blockages from a plethora of particles like dirt, salt, ice, and water droplets. These blockages can cause an approximate squared power/SNR loss for the system. Different from the conventional array diagnosis, the RIS has no signal processing capability. Thus, we propose the joint array diagnosis and channel estimation techniques containing two stages to solve the problem. At the first stage the channel parameters at user equipment (UE) and BS are estimated using an iterative reweighted (IR) method. At the second stage, the array blockage coefficient vector and the effective sparse channel parameters at RIS are jointly estimated via solving a two-timescale non-convex optimization problem. We propose two algorithms, i.e., a batch algorithm (BA) and a two-timescale online joint array diagnosis and channel estimation (TOJADCE) algorithm to solve the problem and compare the performance of these two algorithms. Finally, to speed up the convergence of long-term variable and improve estimation performance, we propose a noise reduction (NR) algorithm. The simulations verify the effectiveness of our proposed algorithms.

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Joint Array Diagnosis and Channel Estimation for RIS-Aided mmWave MIMO System

In this letter, an on- chip integrated terahertz filter with broadband rejection based on spoof surface plasmon polaritions (SSPPs) is demonstrated. The grooves corrugated metallic SSPPs transmission line (TL) with etched complementary split ring resonators (CSRRs) has a pass-reject-pass characteristic in the frequency domain under the fundamental mode and high-order mode. In order to broaden the rejection band and isolation of the filter, SRRs with diverse resonance frequencies are loaded into the grooves of the SSPPs TL. The proposed die prototype is measured via an on- wafer GSG probing with the help of a vector network analyzer. Measured results demonstrate that, from the frequency range of 128 GHz to 158 GHz with a maximum relative bandwidth of up to 21%, the isolation of the filter is larger than 10 dB and the maximum isolation of up to 50 dB, which are in good agreement with the simulated ones. This proposed terahertz filter, with the advantages of compact structure and broad rejection band, has potential application in the terahertz integrated devices.

Yang Chen

Papers

Channel Estimation and IQ Imbalance Compensation for Uplink Massive MIMO Systems With Low-Resolution ADCs

UAV-Aided Secure Transmission in MISOME Wiretap Channels With Imperfect CSI

Performance analysis of uplink massive MIMO systems with variable‐resolution ADCs using MMSE and MRC detection

Joint Array Diagnosis and Channel Estimation for RIS-Aided mmWave MIMO System

Compact Terahertz On-Chip Filter With Broadband Rejection Based on Spoof Surface Plasmon Polaritons