Hardware Imperfections Research Articles

Spectral efficiency of superimposed pilots in cell-free massive MIMO systems with hardware impairments

In this paper, the spectral efficiency (SE) of an uplink hardware-constrained cell-free massive multi-input multi-output (MIMO) system with maximal ratio combining (MRC) receiver filters in the context of superimposed pilots (SPs) is investigated. Tractable closed-form SE expressions for the considered system are derived, which share us with opportunities to explore the impacts of the hardware quality coefficient, the length of coherence interval, and the power balance factor between pilot and data signals. Numerical results indicate that the achievable SE deteriorates as the hardware quality decreases and is more susceptible to the hardware impairments at the user equipments (UEs). Besides, we observe that SPs outperform regular pilots (RPs) in terms of SE and this performance gain is heavily dependent on the values of power balance factor and coherence interval. However, the superiorities of SPs over RPs have vanished when severe hardware imperfections are considered.

Quantitative platform for accurate and reproducible assessment of transverse (T2) relaxation time

MRI's transverse relaxation time (T2) is sensitive to tissues' composition and pathological state. While variations in T2 values can be used as clinical biomarkers, it is challenging to quantify this parameter in vivo due to the complexity of the MRI signal model, differences in protocol implementations, and hardware imperfections. Herein, we provide a detailed analysis of the echo modulation curve (EMC) platform, offering accurate and reproducible mapping of T2 values, from 2D multi‐slice multi‐echo spin‐echo (MESE) protocols.Computer simulations of the full Bloch equations are used to generate an advanced signal model, which accounts for stimulated echoes and transmit field (B1+) inhomogeneities. In addition to quantifying T2 values, the EMC platform also provides proton density (PD) maps, and fat‐water fraction maps. The algorithm's accuracy, reproducibility, and insensitivity to T1 values are validated on a phantom constructed by the National Institute of Standards and Technology and on in vivo human brains.EMC‐derived T2 maps show excellent agreement with ground truth values for both in vitro and in vivo models. Quantitative values are accurate and stable across scan settings and for the physiological range of T2 values, while showing robustness to main field (B0) inhomogeneities, to variations in T1 relaxation time, and to magnetization transfer. Extension of the algorithm to two‐component fitting yields accurate fat and water T2 maps along with their relative fractions, similar to a reference three‐point Dixon technique.Overall, the EMC platform allows to generate accurate and stable T2 maps, with a full brain coverage using a standard MESE protocol and at feasible scan times. The utility of EMC‐based T2 maps was demonstrated on several clinical applications, showing robustness to variations in other magnetic properties. The algorithm is available online as a full stand‐alone package, including an intuitive graphical user interface.

1-Bit Massive MIMO Transmission: Embracing Interference with Symbol-Level Precoding

The deployment of large-scale antenna arrays for cellular base stations (BSs), termed as `Massive MIMO', has been a key enabler for meeting the ever-increasing capacity requirement for 5G communication systems and beyond. Despite their promising performance, fully-digital massive MIMO systems require a vast amount of hardware components including radio frequency chains, power amplifiers, digital-to-analog converters (DACs), etc., resulting in a huge increase in terms of the total power consumption and hardware costs for cellular BSs. Towards both spectrally-efficient and energy-efficient massive MIMO deployment, a number of hardware limited architectures have been proposed, including hybrid analog-digital structures, constant-envelope transmission, and use of low-resolution DACs. In this paper, we overview the recent interest in improving the error-rate performance of massive MIMO systems deployed with 1-bit DACs through precoding at the symbol level. This line of research goes beyond traditional interference suppression or cancellation techniques by managing interference on a symbol-by-symbol basis. This provides unique opportunities for interference-aware precoding tailored for practical massive MIMO systems. Firstly, we characterize constructive interference (CI) and elaborate on how CI can benefit the 1-bit signal design by exploiting the traditionally undesired multi-user interference as well as the interference from imperfect hardware components. Subsequently, we overview several solutions for 1-bit signal design to illustrate the gains achievable by exploiting CI. Finally, we identify some challenges and future research directions for 1-bit massive MIMO systems that are yet to be explored.

Optimal Per-Antenna ADC Bit Allocation in Correlated and Cell-Free Massive MIMO

In Massive MIMO base stations (BSs), the hardware design needs to balance high spectral efficiency (SE) with low complexity. The level of hardware impairments (HWIs) indicates how strong the signal distortion introduced by hardware imperfections is. In particular, the analog-to-digital converters (ADCs) have an important impact on signal distortion and power consumption. This article addresses the fundamental problem of selecting the optimal hardware quality in the Massive MIMO space. In particular, we examine the optimal HWI and ADC bit allocation per BS antenna to maximize the SE. The results show that in co-located arrays with low channel gain variations across antennas, equal ADC bit allocation is optimal. In contrast, cell-free Massive MIMO systems benefit the most from optimizing the ADC bit allocation achieving improvements in the order of 2 [bit-per-channel-use] per user equipment when using regularized zero-forcing (RZF). In addition, when including the impact of power consumption in cell-free Massive MIMO with RZF, allocating low values of mixed ADC bit resolutions across the BS antennas can increase the energy efficiency up to 30% compared to equal ADC bit allocation.

Terahertz Wireless Communications With Flexible Index Modulation Aided Pilot Design

Terahertz (THz) wireless communication is envisioned as a promising technology, which is capable of providing ultra-high-rate transmission up to Terabit per second. However, some hardware imperfections, which are generally neglected in the existing literature concerning lower data rates and traditional operating frequencies, cannot be overlooked in the THz systems. Hardware imperfections usually consist of phase noise, in-phase/quadrature imbalance, and nonlinearity of power amplifier. Due to the time-variant characteristic of phase noise, frequent pilot insertion is required, leading to decreased spectral efficiency. In this paper, to address this issue, a novel pilot design strategy is proposed based on index modulation (IM), where the positions of pilots are flexibly changed in the data frame, and additional information bits can be conveyed by indices of pilots. Furthermore, a turbo receiving algorithm is developed, which jointly performs the detection of pilot indices and channel estimation in an iterative manner. It is shown that the proposed turbo receiver works well even under the situation where the prior knowledge of channel state information is outdated. Analytical and simulation results validate that the proposed schemes achieve significant enhancement of bit-error rate performance and channel estimation accuracy, whilst attaining higher spectral efficiency in comparison with its classical counterpart.

Application of morphological processing methods in computer stereo vision

Computer vision algorithms are important for many areas of human activity. In particular, the number of applications related to the need to process images of real-world objects with computerized tools and the subsequent use of descriptive information in a variety of interactive and automated decision-making systems is increased. An important tool for analyzing real-world scenes are approaches to the application of stereo vision algorithms. The important step of many stereo matching algorithms is a disparity map. Depending on the content of the observed scene, part of the values on the disparity map can be immediately attributed to background values on a certain basis, or form a "natural" background, which is characterized by loss of informative data due to unacceptable error of subsequent resultant distance values. The calculated disparity map of any algorithm may contain some shortcomings in the form of discontinuities of continuous information areas caused by the complexity of shooting conditions, the impact of noise of various natures, hardware imperfections, and so on. An approach to mitigating the undesirable influence of negative factors on the resulting disparity is the use of mathematical morphology operations to process disparity maps at the post-processing stage. This paper presents information technology for increasing the content of disparity maps based on the mathematical morphology methods. The technology is based on a combination of morphological operations of erosion and dilation, which eliminates the typical problems of discontinuities of monotone regions and erroneous values on disparity maps. The proposed approach allows reducing the impact of common problems that arise during the operation of stereo matching algorithms, as well as increase the overall informativeness of disparity maps for images of real objects in the absence of partial or complete initial data on the characteristics of the observed scene. The results of testing morphological operations with disparity maps for real objects allow us to conclude about the possibility of partial restoration of areas of disparity maps with gaps in continuous information areas, as well as to reduce the impact of random anomalous values on the overall content of the disparity maps.

Quantum firmware and the quantum computing stack

Integrated quantum-control protocols could bridge the gap between abstract algorithms and the physical manipulation of imperfect hardware.

I-Talk: Reliable and Practical Superimposed Signal Decoding Without Power Control

Internet-of-Things (IoT) is emerging, while the spectrum is at a premium. To enhance spectrum efficiency, a promising solution is Non-Orthogonal Multiple Access (NOMA) that enables users to communicate with the same resource at the same time, while decoding the superimposed signal at the receiver. Existing NOMA technologies, however, rely on strict power control to decode the superimposed signal, infeasible for heterogeneous and low-cost IoT devices. In contrast, we propose I-Talk, a new NOMA scheme that is designed for IoT and can decode the superimposed signals from two transmitters without power control. Importantly, considering the IoT systems in the wild, both the hardware imperfections and mobility are unavoidable, which can cause severe signal variations, resulting in an unreliable decoding performance. To solve this problem, we design a synthesis channel coefficient to track all signal offsets caused by the hardware imperfection. Meanwhile, we propose a diversity transmission and smart combining scheme to achieve high reliable decoding performance. To demonstrate the feasibility of this new NOMA approach in practical systems, we implement I-Talk with USRP devices and the experimental results illustrate that I-Talk achieves a one-order lower bit-error-rate and a 1.47× higher throughput gain than the state-of-the-art superimposed signal decoding scheme.

Performance Analysis and Design of MIMO Power NOMA With Estimated Parameters Error Statistics Along With SIC and Hardware Imperfections

In this work, we propose to design and subsequently analyze the performance of a power non-orthogonal multiple access (power-NOMA) system, having multiple input multiple output (MIMO) antennas with the consideration of various imperfection statistics. Three key issues emerge, while NOMA is in place. The first one is the user order mismatch due to estimated channel, which impacts the NOMA performance. The second one is the imperfect successive interference cancellation (SIC) at the receiver, which impacts the interference cancellation at the NOMA receiver. The third issue is the imperfection arising due to hardware circuits, which include fixed-pointed digital logic, analog and radio frequency (RF) circuits. To some extent, these issues have been addressed in bits and pieces in the context of single antenna power NOMA design, however they have not been addressed all together in the context of MIMO power NOMA. There are several key contributory aspects in this work. Key part is the exploitation of these parameter estimation error statistics along with the imperfections in transceiver hardware chains and SIC at the receiver. We propose a MIMO NOMA based on the maximum sum-rate criterion. An analytical framework has been presented in this regard. Numerical results demonstrate that the consideration of these error statistics improves the overall sum-rate performance.

Performance Analysis of TDD Multicell Massive MIMO Systems With Non-Orthogonal Pilots and Hardware Imperfections in Rician Fading Channels

The performance of a time-division duplex (TDD) multicell massive MIMO ( $\mathrm{M}^2$ -MIMO) system with non-orthogonal pilots (Non-OPs) for channel estimation (CE) and hardware imperfections (HWIs), i.e., low-precision ADCs/DACs at the base station (BS) and non-ideally operating user equipment (UE) distorted by RF chain impairments (RF-CIs), is analyzed and evaluated. Assuming that this communication system operates in a Rician fading channel, firstly, the minimum mean square error (MMSE) CE complexity for both Non-OPs and orthogonal pilots (OPs) are derived and compared. It is also shown that the variance of the MMSE CE error with Non-OPs can be approximated as a linear fraction. Based on this CE analysis, the uplink (UL) and downlink (DL) spectral efficiency (SE) performances with ideal and non-ideal channel state information (CSI) are derived. Furthermore, the UL-SE performances for both Non-OPs and OPs are compared to show the advantage of using Non-OPs for applications which have very high connectivity requirements. The power scaling law is also used to obtain additional insights on how these HWIs affect the overall $\mathrm{M}^2$ -MIMO SE performance. In order to balance the total BS circuitry power consumption against UL-SE, the tradeoff between UL energy efficiency (EE) and UL-SE has been investigated by analyzing the performance of several receive detection strategies as a function of the employed ADC quantization bits (Q-bits). Moreover, the optimal ADC/DAC Q-bit region which maximizes the DL-EE is identified. Various performance evaluation results obtained by means of computer simulations have verified the analysis and validated the accuracy of the equivalent theoretical performance evaluation results.

Hardware and Interference Limited Cooperative CR-NOMA Networks Under Imperfect SIC and CSI

The conflation of cognitive radio (CR) and non-orthogonal multiple access (NOMA) concepts is a promising approach to fulfill the massive connectivity goals of future networks given the spectrum scarcity. Accordingly, this paper investigates the performance of a cooperative CR-NOMA network in the presence of system impairments and interference. Our analysis is involved with the derivation of the end-to-end outage probability for primary and secondary networks by accounting for channel state information (CSI), hardware imperfections, and residual interference caused by successive interference cancellation errors as well as coexisting primary/secondary users. Moreover, a mathematically tractable upper bound on spectral efficiency (SE) with its high-SNR approximations are derived. Besides, we propose an optimal power allocation scheme for CR-NOMA users to guarantee their outage and SE fairness. The numerical results validated by Monte Carlo simulations show that the CR-NOMA network provides a superior outage performance over orthogonal multiple access. Furthermore, the higher level of system imperfections leads to the performance degradation of the CR-NOMA networks. As imperfections become more severe, the CR-NOMA is observed to deliver relatively inferior outage and SE performance as compared to the perfect system scenario.

UAV Based Satellite-Terrestrial Systems With Hardware Impairment and Imperfect SIC: Performance Analysis of User Pairs

We investigated the outage performance of non-orthogonal multiple access (NOMA) in satellite-terrestrial systems which contain hardware impairments. An unmanned aerial vehicle (UAV) was implemented to forward signals from a satellite to users on the ground. A two-user model was applied to achieve spectral efficiency. In practical, real-life scenarios, the UAV and ground users encounter issues with imperfect hardware. We examined the performance gap between two users experiencing practical problems such as hardware impairment and imperfect successive interference cancellation (SIC). To implement a practical scenario, Shadow-Rician fading was adopted in the satellite links, and Rician fading was employed in the terrestrial links for ground users. In the main results, we derived the closed-form expression of the outage probability, and to evaluate the system performance of two NOMA users, we obtained the approximate expressions for high signal-to-noise ratios (SNR). Finally, we produced Monte-Carlo simulations to verify the analytical expressions and demonstrate the effect of the main system parameters, such as the number of transmit antennas on the satellite, transmit SNR, and level of hardware impairment on the system performance metric.

Performance Analysis of Intelligent Reflecting Surface-Assisted Wireless System With Non-Ideal Transceiver

Intelligent Reflecting Surfaces (IRSs) have recently emerged as a promising solution for realizing the smart radio environment concept by leveraging the characteristics of metamaterials and large antenna arrays. However, the existing works on IRS do not account for the transceiver impairments while analyzing the performance of IRS assisted wireless systems. This paper investigates the impact of transceiver hardware imperfections on the performance of IRS-assisted wireless systems. Specifically, we have analyzed the spectral efficiency (SE), the energy efficiency (EE) and the outage probability of IRS-assisted wireless systems by deriving their closed-form expressions and verifying them through simulation results. The results show the importance of modeling and compensating for hardware impairment as they significantly restrict the performance of such systems.

Open Set Wireless Transmitter Authorization: Deep Learning Approaches and Dataset Considerations

Due to imperfections in transmitters' hardware, wireless signals can be used to verify their identity in an authorization system. While deep learning was proposed for transmitter identification, existing work has mainly focused on classification among a closed set of transmitters. Malicious transmitters outside this closed set will be misclassified, jeopardizing the authorization system. In this article, we formulate the problem of recognizing authorized transmitters and rejecting new transmitters as open set recognition and anomaly detection. We consider approaches based on one and several binary classifiers, multiclass classifiers, and signal reconstruction. We study how these approaches scale with the required number of authorized transmitters. We propose using a known set of unauthorized transmitters to assist the training and study its impact. The evaluation procedure takes into consideration that some transmitters might be more similar than others and nuances these effects. The authorization's robustness against temporal changes in fingerprints is also evaluated as a function of the approach and the dataset structure. When using 10 authorized and 50 known unauthorized WiFi transmitters from a publicly accessible testbed, we were able to achieve an outlier detection accuracy of 98% on the same day test set and 80% on the different day test set.

Radio-frequency chain selection for energy and spectral efficiency maximization in hybrid beamforming under hardware imperfections

The next-generation wireless communications require reduced energy consumption, increased data rates and better signal coverage. The millimetre-wave frequency spectrum above 30 GHz can help fulfil the performance requirements of the next-generation mobile broadband systems. Multiple-input multiple-output technology can provide performance gains to help mitigate the increased path loss experienced at millimetre-wave frequencies compared with microwave bands. Emerging hybrid beamforming architectures can reduce the energy consumption and hardware complexity with the use of fewer radio-frequency (RF) chains. Energy efficiency is identified as a key fifth-generation metric and will have a major impact on the hybrid beamforming system design. In terms of transceiver power consumption, deactivating parts of the beamformer structure to reduce power typically leads to significant loss of spectral efficiency. Our aim is to achieve the highest energy efficiency for the millimetre-wave communications system while mitigating the resulting loss in spectral efficiency. To achieve this, we propose an optimal selection framework which activates specific RF chains that amplify the digitally beamformed signals with the analogue beamforming network. Practical precoding is considered by including the effects of user interference, noise and hardware impairments in the system modelling.

Uplink Channel Estimation With Hardware Imperfections, Antenna Position Error and Channel Correlation for Nested and Linear Array Antennas

In this treatise, we have proposed an uplink channel estimation algorithm for nested and linear array antennas with hardware imperfections, antenna position error, and channel correlation in a multi-cell, multi-user wireless system with a one-ring scattering channel model. Hardware impairments and antenna position errors assume special importance in modern wireless system due to their severe impacts on system performance. With the increase of radio frequency (RF) in the modern wireless system and the subsequent usage of a large number of antennas for beamforming and meeting ever-increasing data rates, those errors are much relevant today. We have considered a sparse nested array (NA) and uniform linear array (ULA) for array geometry at the base station (BS). In this work, closed-form expression and bounds on the mean square error (MSE) of the linear minimum mean square error (LMMSE) channel estimate are derived. We have also analyzed the spectral efficiency (SE) of a simplified system with ULA and NA at the BS, given the model with hardware distortion and antenna position error. Two cases for (a) perfect channel side information (CSI) and (b) estimated channel are evaluated and compared in terms of their SEs, while the closed-form expression for SE with ULA at the BS considering perfect CSI is derived and verified. Numerical simulations are conducted to verify the accuracies of our derived results.

Stay Connected, Leave no Trace

The intrinsic hardware imperfection of WiFi chipsets manifests itself in the transmitted signal, leading to a unique radiometric fingerprint. This fingerprint can be used as an additional means of authentication to enhance security. In fact, recent works propose practical fingerprinting solutions that can be readily implemented in commercial-off-the-shelf devices. In this paper, we prove analytically and experimentally that these solutions are highly vulnerable to impersonation attacks. We also demonstrate that such a unique device-based signature can be abused to violate privacy by tracking the user device, and, as of today, users do not have any means to prevent such privacy attacks other than turning off the device. We propose RF-Veil, a radiometric fingerprinting solution that not only is robust against impersonation attacks but also protects user privacy by obfuscating the radiometric fingerprint of the transmitter for non-legitimate receivers. Specifically, we introduce a randomized pattern of phase errors to the transmitted signal such that only the intended receiver can extract the original fingerprint of the transmitter. In a series of experiments and analyses, we expose the vulnerability of adopting naive randomization to statistical attacks and introduce countermeasures. Finally, we show the efficacy of RF-Veil experimentally in protecting user privacy and enhancing security. More importantly, our proposed solution allows communicating with other devices, which do not employ RF-Veil.

Performance evaluation of an image-based measurement method used to determine the geometric errors of cone-beam CT instruments

Computed Tomography (CT) has been used in an upward trend to inspect dimensional and geometric characteristics of manufactured parts. The complexity of the measurement chain, however, gives rise to many influence factors that affect the measurement accuracy. Some of these factors are under the control of the user, who needs to properly set some CT instrument parameters for a specific measurement task. Over other influence factors, the user may have some degree of control, such as the interaction of the x-rays with the physical matter, which produces image discrepancies. Finally, there are some influence factors over which the user may have no control at all, such as misalignments resulted from imperfections of the CT instrument hardware. In this regard, this paper describes the experimental evaluation of the geometric errors of a cone-beam CT instrument using an image-based method to map them. The experiments were performed under different test conditions, designed with the main purpose of understanding the behavior of the geometric errors in time and space, as well as assisting the appropriate actions to be taken for e.g. error correction by software. Special attention was given to the evaluation of the effectiveness of the measurement method itself to detect the geometric errors.

Realistic hardware imperfections in communication system under Gaussian approximation model and generalised Gaussian model

Studying hardware imperfections in the communication system is very important. It can cause in-phase/quadrature (I/Q) imbalance and phase noise problems. This study proposed a realistic communication system under hardware imperfections and self-interference. The impact of hardware imperfections at the transmitter, at the relays and the receiver is analysed for two and three transmission hops. A realistic Gaussian approximation model and generalised Gaussian model are proposed to show its impact on system performance. Assuming that the channels are subjected to Nakagami-m fading. A closed-form expression for the outage probability is mathematically derived. The comparison between the proposed system and other systems with distortions and I/Q imbalance is provided. Results demonstrate that the performance of realistic communication system is more degraded, especially at higher transmission hops.

Design of a Robust Radio-Frequency Fingerprint Identification Scheme for Multimode LFM Radar

Radar is an indispensable part of the Internet of Things (IoT). Specific emitter identification is essential to identify the legitimate radars and, more importantly, to reject the malicious radars. Conventional methods rely on pulse parameters that are not capable to identify the specific emitter as two radars may have the same configuration or a malicious radar can perform spoofing attacks. Radio-frequency fingerprint (RFF) is the unique and intrinsic hardware characteristic of devices resulted from hardware imperfection, which can be used as the device identity. This article proposes a robust and reliable radar identification scheme based on the RFF, taking linear frequency modulation (LFM) radar as a case study. This scheme first classifies the operation mode of the pulses, then eliminates the noise effect, and finally identifies the radar emitters based on the transient and modulation-based RFF features. The experimental results verify the effectiveness of our radar identification scheme among three real LFM radars (same model) operating at four modes, each mode with 2000 pulses from each radar. The identification rates of the four modes are all higher than 90% when the signal-to-noise ratio (SNR) is about 5 dB. In addition, mode 3 achieves almost 100% identification accuracy even when the SNR is as low as −10 dB.