Literatura científica selecionada sobre o tema "Hybrid Analog-Digital Transceivers"

The necessity to investigate viable spectrum areas for satisfying the anticipated needs has been prompted by the rising cellular data traffic demands. As a result, the scientific community has given (mmWave) communication a lot of attention. In (5G) wireless networks, massive (mmWave MIMO) communications are often accomplished using hybrid transceivers that combine lower and higher as a digital and analog processing units phase shifters and power amplifiers respectfully. This hybrid beamforming (HB) architecture lowers costs and power use, which is consistent with the (5G) network's objective for (EE) of design. In this work, using system models of hybrid transceiver architectures, both digital (DB) and analog (AB) beamforming arrays with possibilities for antenna design, and hybrid beamforming (HB) in heterogeneous wireless networks, they trace the development of (HB) for massive MIMO connections. Authors widen in discussion by focusing on hybrid beamforming to solve resource management issue and examine the applicability of hybrid beamforming (HB) techniques while also highlighting the fascinating difficulties that lie ahead for this field. The main aim of this work is to analyse the many studies and show the advantages and weak points of each single study based on the general and famous parameters as well as explaining the efficiency of all studies. We got an overview of the hybrid beamforming, which covers topics such as application areas; In order to reduce upfront costs and continuing operating costs, the fully-connected architecture can achieve full beamforming gain per RF chain, but at the expense of increased hardware complexity. On the other hand, the low-complexity sub-connected architecture offers reduced beamforming gain.

This paper proposes an effective strongest angles of arrival (AoAs) estimation algorithm for a hybrid millimeter wave (mmWave) communication system with 1-bit analog-to-digital/digital-to-analog converters (A/Ds) equipped at transceivers. The proposed algorithm aims to reduce the required number of estimation overheads, while maintaining the root mean square error (RMSE) of strongest AoA estimates at the base station. We obtain the quantization thresholds of A/Ds for different signal-to-noise ratios (SNRs) and numbers of antennas via numerical simulations, based on which, the strongest AoAs can be estimated with a small amount of overheads. The proposed algorithm is compared with conventional schemes including 1-bit FFT and 1-bit exhaustive search, as well as 1-bit Cramér-Rao lower bound. Simulation results verify the effectiveness of our proposed algorithm in terms of reducing estimation overheads while maintaining reasonable estimation performance in low SNRs.

Efficient management through monitoring of Li-ion batteries is critical to the progress of electro-mobility and energy storage globally, since the technology can be hazardous if pushed beyond its safety boundaries. Battery management systems (BMSs) are being actively improved to reduce size, weight, and cost while increasing their capabilities. Using power line communication, wireless monitoring, or hybrid data links are one of the most advanced research directions today. In this work, we propose the use of radio frequency (RF) transceivers as a communication unit that can deliver both wired and wireless services, through their superior analog and digital signal processing capability compared to PLC technology. To validate our approach computational simulation and empirical evaluation was conducted to examine the possibility of using RF transceivers on a direct current (DC) bus for wired BMS. A key advantage of this study is that it proposes a flexible and tested system for communication across a variety of network scenarios, where wireless data links over disrupted connections may be enabled by using this technology in short-range wired modes. This investigation demonstrates that the IEEE 802.15.4-compliant transceivers with operating frequencies of 868 MHz and 2.4 GHz can establish stable data links on a DC bus via capacitive coupling at high data rates.

In this paper, we present and compare three novel model-cum-data-driven channel estimation procedures in a millimeter-wave Multi-Input Multi-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) wireless communication system. The transceivers employ a hybrid analog-digital architecture. We adapt techniques from a wide range of signal processing methods, such as detection and estimation theories, compressed sensing, and Bayesian inference, to learn the unknown virtual beamspace domain dictionary, as well as the delay-and-beamspace sparse channel. We train the model-based algorithms with a site-specific training dataset generated using a realistic ray tracing-based wireless channel simulation tool. We assess the performance of the proposed channel estimation algorithms with the same site's test data. We benchmark the performance of our novel procedures in terms of normalized mean squared error against an existing fast greedy method and empirically show that model-based approaches combined with data-driven customization unanimously outperform the state-of-the-art techniques by a large margin. The proposed algorithms were selected as the top three solutions in the "ML5G-PHY Channel Estimation Global Challenge 2020" organized by the International Telecommunication Union.

A generic transmitter (TX) I/Q imbalance self-calibration method, which was designed based on a hybrid analog and digital structure, is proposed in this paper. The whole calibration scheme was implemented using low-complexity digital–analog circuits based on a zero-force feedback loop. In order to eliminate the negative effect of local oscillator (LO) harmonics on the calibration, we used a variable-delay line (VDL) in the analog domain instead of the digital phase compensator. The prototype chip was fabricated within a 0.2∼5.0 GHz direct-conversion transmitter in a 65 nm CMOS process, and measurements found an image rejection ratio (IRR) of 65 dBc.

A hybrid analog/digital very large-scale integration (VLSI) implementation of a spiking neural network with programmable synaptic weights was designed. The synaptic weight values are stored in an asynchronous module, which is interfaced to a fast current-mode event-driven DAC for producing synaptic currents with the appropriate amplitude values. It acts as a transceiver, receiving asynchronous events for input, performing neural computations with hybrid analog/digital circuits on the input spikes, and eventually producing digital asynchronous events in output. Input, output, and synaptic weight values are transmitted to/from the chip using a common communication protocol based on the address event representation (AER). Using this representation, it is possible to interface the device to a workstation or a microcontroller and explore the effect of different types of spike-timing dependent plasticity (STDP) learning algorithms for updating the synaptic weights values in the CAM module.

La forte augmentation des applications gourmandes en bande passante ces dernières années et la pénurie mondiale des bandes cellulaire dans le spectre traditionnel des bandes basses ont rendu le spectre vacant dans les bandes de fréquences à ondes millimétriques (mmWave) d'une importance primordiale pour tous les acteurs clés de l'industrie cellulaire. Cela étant dit, communiquer sans fil sur les fréquences mmWave serait néanmoins une tâche difficile, principalement en raison de la faible réflectivité, de l'absorption élevée et des pertes de propagation en espace libre importantes sur des bandes aussi élevées.L'une des solutions très populaires pour surmonter les problèmes de propagation susmentionnés consiste à utiliser des réseaux d'antennes massifs, une technique rendue possible grace a la proportionnalité entre la taille physique du réseau et la longueur d'onde de la porteuse (les fréquences mmWave sont caractérisées par une petite longueur d'onde, ce qui se traduit par réseaux d'antennes compacts avec un grand nombre d'éléments). Cependant, le coût élevé, la consommation d'énergie et la complexité du matériel de signal mixte chez mmWave rendent impossible l'utilisation de grands réseaux d'antennes avec des éléments à commande numérique.Le cloisonnement des traitements de signal liés aux émetteurs-récepteurs mmWave a rendu possible une mise en œuvre économique et énergétiquement efficace de ces derniers. Ces nouvelles architectures sont connues sous le nom d'émetteurs-récepteurs hybrides analogiques/numériques de formation de faisceaux. Ces architectures hybrides divisent le traitement de précodage/combinaison entre les domaines analogique et numérique, ce qui réduit considérablement le nombre requis de chaînes RF.Les structures des réseaux hybrides soulevent néanmoins leurs propres défis, le faible rapport signal sur bruit (SNR) résultant des pertes de propagation élevées, la grande dimensionnalité de la matrice de canaux sans fil Multiple-Input-Multiple-Output (MIMO) et la présence de traitement analogique compliquent l'acquisition des informations d'état du canal (CSI) et le calcul des précodeurs et combineurs MIMO.Relever les défis susmentionnés est essentiel pour activer le cellulaire basé sur mmWave. Avec cette motivation à l'esprit, cette thèse propose de nouvelles solutions algorithmiques qui les abordent. Nous proposons des solutions rapides et de faible complexité qui offrent des performances efficaces tout en respectant les contraintes matérielles. Les principales contributions de la présente thèse consistent à concevoir des algorithmes rapides et de faible complexité qui permettent de construire des précodeurs et des combineurs robustes pendant la phase d'apprentissage du beamformer et sans avoir besoin d'estimer explicitement le CSI puis de l'utiliser pour dériver ces beamformers
The high increase of bandwidth greedy applications in recent years, and the global wireless bandwidth shortage in the traditional low band spectra has made vacant spectrum in millimeter-wave (mmWave) frequency bands of a paramount importance for all key players in the cellular industry. This being said, wireless communications over mmWave frequencies will nevertheless be a challenging task, mainly due to the poor reflectivity, high absorption and large free space propagation losses on such high bands.One of the very popular solutions to overcome the aforementioned propagation issues is to use massive antenna arrays, a technique that is made possible because if the proportionality between the array's physical size and the carrier wavelength (mmWave frequencies are characterized by small wavelength, which translates to compact antenna arrays with high number of elements). However, the high cost, power consumption and complexity of the mixed signal hardware at mmWave make having large antenna arrays with digitally controlled elements infeasible.The partitioning of the signal processing operations related to the mmWave transceivers made having a cost and energy effective implementation of these latter possible. These novel architectures are known as hybrid analog/digital beamforming transceivers. These hybrid architectures divide the precoding/combining processing between the analog and digital domains, which reduces considerably the required number of RF chains.Hybrid array structures entail nevertheless their own challenges, the low signal-to-noise ration (SNR) resulting from high propagation losses, the large dimensionality of the Multiple-Input-Multiple-Output (MIMO) wireless channel matrix and the presence of analog processing complicate the acquisition of the channel state information (CSI) and the computation of the MIMO precoders and combiners.Addressing the aforementioned challenges is key to enabling mmWave based cellular. With this motivation in mind, this dissertation proposes novel algorithmic solutions that tackle them. We propose fast and low complexity solutions that yield efficient performance while respecting the hardware constraints. The main contributions of the present thesis consist of devising fast and low complexity algorithms that enable building robust precoders and combiners during the beam training phase and without the need of explicitly estimating the CSI and then using it to derive these beamformers

碩士
國立中正大學
通訊工程研究所
105
Millimeter-wave (mmWave) has become one of the most promising technologies to deal with the growing demand for data transmission over wireless networks. Due to the propagation characteristics in the mmWave band, there is a higher path loss compared to the microwave frequency band. MmWave communication combined with massive MIMO technique has been proposed. In traditional multi-user fully-digital MIMO system, every antenna connects to one RF chain. Unfortunately, due to the hardware cost and power constraint, fully-digital architecture with a large antenna array in millimeter-wave systems is difficult to implement. Recent works in the literature advocate a hybrid architecture for millimeter-wave systems to solve this problem. In this thesis, after reviewing the recent literature, we proposed new multiuser hybrid transeiver architecture and algorithms in mmWave systems, and then proposed two designs to harvest array gain. Simulation results demonstrate that our proposed algorithms can approach to the total transmission rate of the fully-digital architecture.