A survey on hybrid beamforming techniques in 5G : architecture and system model perspectives

The increasing wireless data traffic demands have driven the need to explore suitable spectrum regions for meeting the projected requirements. In the light of this, millimeter wave (mmWave) communication has received considerable attention from the research community. Typically, in fifth generation (5G) wireless networks, mmWave massive multiple-input multiple-output (MIMO) communications is realized by the hybrid transceivers which combine high dimensional analog phase shifters and power amplifiers with lower-dimensional digital signal processing units. This hybrid beamforming design reduces the cost and power consumption which is aligned with an energy-efficient design vision of 5G. In this paper, we track the progress in hybrid beamforming for massive MIMO communications in the context of system models of the hybrid transceivers' structures, the digital and analog beamforming matrices with the possible antenna configuration scenarios and the hybrid beamforming in heterogeneous wireless networks. We extend the scope of the discussion by including resource management issues in hybrid beamforming. We explore the suitability of hybrid beamforming methods, both, existing and proposed till first quarter of 2017, and identify the exciting future challenges in this domain

Joint Bit Allocation and Hybrid Beamforming Optimization for Energy Efficient Millimeter Wave MIMO Systems

In this paper, we aim to design highly energy efficient end-to-end communication for millimeter wave multiple-input multiple-output systems. This is done by jointly optimizing the digital-to-analog converter (DAC)/analog-to-digital converter (ADC) bit resolutions and hybrid beamforming matrices. The novel decomposition of the hybrid precoder and the hybrid combiner to three parts is introduced at the transmitter (TX) and the receiver (RX), respectively, representing the analog precoder/combiner matrix, the DAC/ADC bit resolution matrix and the baseband precoder/combiner matrix. The unknown matrices are computed as a solution to the matrix factorization problem where the optimal fully digital precoder or combiner is approximated by the product of these matrices. A novel and efficient solution based on the alternating direction method of multipliers is proposed to solve these problems at both the TX and the RX. The simulation results show that the proposed solution, where the DAC/ADC bit allocation is dynamic during operation, achieves higher energy efficiency when compared with existing benchmark techniques that use fixed DAC/ADC bit resolutions.Comment: arXiv admin note: text overlap with arXiv:1909.1217

Energy efficient and low complexity techniques for the next generation millimeter wave hybrid MIMO systems

The fifth generation (and beyond) wireless communication systems require increased capacity, high data rates, improved coverage and reduced energy consumption. This can be potentially provided by unused available spectrum such as the Millimeter Wave (MmWave) frequency spectrum above 30 GHz. The high bandwidths for mmWave communication compared to sub-6 GHz microwave frequency bands must be traded off against increased path loss, which can be compensated using large-scale antenna arrays such as the Multiple-Input Multiple- Output (MIMO) systems. The analog/digital Hybrid Beamforming (HBF) architectures for mmWave MIMO systems reduce the hardware complexity and power consumption using fewer Radio Frequency (RF) chains and support multi-stream communication with high Spectral Efficiency (SE). Such systems can also be optimized to achieve high Energy Efficiency (EE) gains with low complexity but this has not been widely studied in the literature. This PhD project focussed on designing energy efficient and low complexity communication techniques for next generation mmWave hybrid MIMO systems. Firstly, a novel architecture with a framework that dynamically activates the optimal number of RF chains was designed. Fractional programming was used to solve an EE maximization problem and the Dinkelbach Method (DM) based framework was exploited to optimize the number of active RF chains and the data streams. The DM is an iterative and parametric algorithm where a sequence of easier problems converge to the global solution. The HBF matrices were designed using a codebook-based fast approximation solution called gradient pursuit which was introduced as a cost-effective and fast approximation algorithm. This work maximizes EE by exploiting the structure of RF chains with full resolution sampling unlike existing baseline approaches that use fixed RF chains and aim only for high SE. Secondly, an efficient sparse mmWave channel estimation algorithm was developed with low resolution Analog-to-Digital Converters (ADCs) at the receiver. The sparsity of the mmWave channel was exploited and the estimation problem was tackled using compressed sensing through the Stein's unbiased risk estimate based parametric denoiser. The Expectation-maximization density estimation was used to avoid the need to specify the channel statistics. Furthermore, an energy efficient mmWave hybrid MIMO system was developed with Digital-to- Analog Converters (DACs) at the transmitter where the best subset of the active RF chains and the DAC resolution were selected. A novel technique based on the DM and subset selection optimization was implemented for EE maximization. This work exploits the low resolution sampling at the converting units and provides more efficient solutions in terms of EE and channel estimation than existing baselines in the literature. Thirdly, the DAC and ADC bit resolutions and the HBF matrices were jointly optimized for EE maximization. The flexibility in choosing the bit resolution for each DAC and ADC was considered and they were optimized on a frame-by-frame basis unlike the existing approaches, based on the fixed resolution sampling. A novel decomposition of the HBF matrices to three parts was introduced to represent the analog beamformer matrix, the DAC/ADC bit resolution matrix and the baseband beamformer matrix. The alternating direction method of multipliers was used to solve this matrix factorization problem as it has been successfully applied to other non-convex matrix factorization problems in the literature. This work considers EE maximization with low resolution sampling at both the DACs and the ADCs simultaneously, and jointly optimizes the HBF and DAC/ADC bit resolution matrices, unlike the existing baselines that use fixed bit resolution or otherwise optimize either DAC/ADC bit resolution or HBF matrices

Low Power Analog Processing for Ultra-High-Speed Receivers with RF Correlation

Ultra-high-speed data communication receivers (Rxs) conventionally require analog digital converters (ADC)s with high sampling rates which have design challenges in terms of adequate resolution and power. This leads to ultra-high-speed Rxs utilising expensive and bulky high-speed oscilloscopes which are extremely inefficient for demodulation, in terms of power and size. Designing energy-efficient mixed-signal and baseband units for ultra-high-speed Rxs requires a paradigm approach detailed in this paper that circumvents the use of power-hungry ADCs by employing low-power analog processing. The low-power analog Rx employs direct-demodulation with RF correlation using low-power comparators. The Rx is able to support multiple modulations with highest modulation of 16-QAM reported so far for direct-demodulation with RF correlation. Simulations using Matlab, Simulink R2020a® indicate sufficient symbol-error rate (SER) performance at a symbol rate of 8 GS/s for the 71 GHz Urban Micro Cell and 140 GHz indoor channels. Power analysis undertaken with current analog, hybrid and digital beamforming approaches requiring ADCs indicates considerable power savings. This novel approach can be adopted for ultra-high-speed Rxs envisaged for beyond fifth generation (B5G)/sixth generation (6G)/ terahertz (THz) communication without the power-hungry ADCs, leading to low-power integrated design solutions

Energy Efficiency in 5G Communications – Conventional to Machine Learning Approaches, Journal of Telecommunications and Information Technology, 2020, nr 4

Demand for wireless and mobile data is increasing along with development of virtual reality (VR), augmented reality (AR), mixed reality (MR), and extended reality (ER) applications. In order to handle ultra-high data exchange rates while offering low latency levels, fifth generation (5G) networks have been proposed. Energy efficiency is one of the key objectives of 5G networks. The notion is defined as the ratio of throughput and total power consumption, and is measured using the number of transmission bits per Joule. In this paper, we review state-of-the-art techniques ensuring good energy efficiency in 5G wireless networks. We cover the base-station on/off technique, simultaneous wireless information and power transfer, small cells, coexistence of long term evolution (LTE) and 5G, signal processing algorithms, and the latest machine learning techniques. Finally, a comparison of a few recent research papers focusing on energy-efficient hybrid beamforming designs in massive multiple-input multiple-output (MIMO) systems is presented. Results show that machine learningbased designs may replace best performing conventional techniques thanks to a reduced complexity machine learning encode

Array Architectures and Physical Layer Design for Millimeter-Wave Communications Beyond 5G

Ever increasing demands in mobile data rates have resulted in exploration of millimeter-wave (mmW) frequencies for the next generation (5G) wireless networks. Communications at mmW frequencies is presented with two keys challenges. Firstly, high propagation loss requires base stations (BSs) and user equipment (UEs) to use a large number of antennas and narrow beams to close the link with sufficient received signal power. Consequently, communications using narrow beams create a new challenge in channel estimation and link establishment based on fine angular probing. Current mmW system use analog phased arrays that can probe only one angle at the time which results in high latency during link establishment and channel tracking. It is desirable to design low latency beam training by exploring both physical layer designs and array architectures that could replace current 5G approaches and pave the way to the communications for frequency bands in higher mmW band and sub-THz region where larger antenna arrays and communications bandwidth can be exploited. To this end, we propose a novel signal processing techniques exploiting unique properties of mmW channel, and show both theoretically, in simulation and experiments its advantages over conventional approaches. Secondly, we explore different array architecture design and analyze their trade-offs between spectral efficiency and power consumption and area. For comprehensive comparison, we have developed a methodology for optimal design of system parameters for different array architecture candidates based on the spectral efficiency target, and use these parameters to estimate the array area and power consumption based on the circuits reported in the literature. We show that the hybrid analog and digital architectures have severe scalability concerns in radio frequency signal distribution with increased array size and spatial multiplexing levels, while the fully-digital array architectures have the best performance and power/area trade-offs.The developed approaches are based on a cross-disciplinary research that combines innovation in model based signal processing, machine learning, and radio hardware. This work is the first to apply compressive sensing (CS), a signal processing tool that exploits sparsity of mmW channel model, to accelerate beam training of mmW cellular system. The algorithm is designed to address practical issues including the requirement of cell discovery and synchronization that involves estimation of angular channel together with carrier frequency offset and timing offsets. We have analyzed the algorithm performance in the 5G compliant simulation and showed that an order of magnitude saving is achieved in initial access latency for the desired channel estimation accuracy. Moreover, we are the first to develop and implement a neural network assisted compressive beam alignment to deal with hardware impairments in mmW radios. We have used 60GHz mmW testbed to perform experiments and show that neural networks approach enhances alignment rate compared to CS. To further accelerate beam training, we proposed a novel frequency selective probing beams using the true-time-delay (TTD) analog array architecture. Our approach utilizes different subcarriers to scan different directions, and achieves a single-shot beam alignment, the fastest approach reported to date. Our comprehensive analysis of different array architectures and exploration of emerging architectures enabled us to develop an order of magnitude faster and energy efficient approaches for initial access and channel estimation in mmW systems

Spatial modulation schemes and modem architectures for millimeter wave radio systems

The rapid growth of wireless industry opens the door to several use cases such as internet of things and device-to-device communications, which require boosting the reliability and the spectral efficiency of the wireless access network, while reducing the energy consumption at the terminals. The vast spectrum available in millimeter-wave (mmWave) frequency band is one of the most promising candidates to achieve high-speed communications. However, the propagation of the radio signals at high carrier frequencies suffers from severe path-loss which reduces the coverage area. Fortunately, the small wavelengths of the mmWave signals allow packing a large number of antennas not only at the base station (BS) but also at the user terminal (UT). These massive antenna arrays can be exploited to attain high beamforming and combining gains and overcome the path-loss associated with the mmWave propagation. In conventional (fully digital) multiple-input-multiple-output (MIMO) transceivers, each antenna is connected to a specific radio-frequency (RF) chain and high resolution analog-to-digital-converter. Unfortunately, these devices are expensive and power hungry especially at mmWave frequency band and when operating in large bandwidths. Having this in mind, several MIMO transceiver architectures have been proposed with the purpose of reducing the hardware cost and the energy consumption. Fully connected hybrid analog and digital precoding schemes were proposed in with the aim of replacing some of the conventional RF chains by energy efficient analog devices. These fully connected mapping requires many analog devices that leads to non-negligible energy consumption. Partially connected hybrid architectures have been proposed to improve the energy efficiency of the fully connected transceivers by reducing the number of analog devices. Simplifying the transceiver’s architecture to reduce the power consumption results in a degradation of the attained spectral efficiency. In this PhD dissertation, we propose novel modulation schemes and massive MIMO transceiver design to combat the challenges at the mmWave cellular systems. The structure of the doctoral manuscript can be expressed as In Chapter 1, we introduce the transceiver design challenges at mmWave cellular communications. Then, we illustrate several state of the art architectures and highlight their limitations. After that, we propose scheme that attains high-energy efficiency and spectrum efficiency. In chapter 2, first, we mathematically describe the state of the art of the SM and highlight the main challenges with these schemes when applied at mmWave frequency band. In order to combat these challenges (for example, high cost and high power consumption), we propose novel SM schemes specifically designed for mmWave massive MIMO systems. After that, we explain how these schemes can be exploited in attaining energy efficient UT architecture. Finally, we present the channel model, systems assumptions and the transceiver devices power consumption models. In chapter 3, we consider single user SM system. First, we propose downlink (DL) receive SM (RSM) scheme where the UT can be implemented with single or multiple radio-frequency chains and the BS can be fully digital or hybrid architecture. Moreover, we consider different precoders at the BS and propose low complexity and efficient antenna selection schemes for narrowband and wideband transmissions. After that, we propose joint uplink-downlink SM scheme where we consider RSM in the DL and transmit SM (TSM) in the UL based on energy efficient hybrid UT architecture. In chapter 4, we extend the SM system to the multi-user case. Specifically, we develop joint multi-user power allocation, user selection and antenna selection algorithms for the broadcast and the multiple access channels. Chapter 5 is presented for concluding the thesis and proposing future research directions.Considerando los altos requerimientos de los servicios de nueva generación, las infraestructuras de red actual se han visto obligadas a evolucionar en la forma de manejar los diferentes recursos de red y computación. Con este fin, nuevas tecnologías han surgido para soportar las funcionalidades necesarias para esta evolución, significando también un gran cambio de paradigma en el diseño de arquitecturas para la futura implementación de redes.En este sentido, este documento de tesis doctoral presenta un análisis sobre estas tecnologías, enfocado en el caso de redes inter/intra Data Centre. Por consiguiente, la introducción de tecnologías basadas en redes ópticas ha sido estudiada, con el fin de identificar problemas actuales que puedan llegar a ser solucionados mediante el diseño y aplicación de nuevas técnicas, asimismo como a través del desarrollo o la extensión de los componentes de arquitectura de red.Con este propósito, se han definido una serie de propuestas relacionadas con aspectos cruciales, así como el control de dispositivos ópticos por SDN para habilitar el manejo de redes híbridas, la necesidad de definir un mecanismo de descubrimiento de topologías ópticas capaz de exponer información precisa, y el analizar las brechas existentes para la definición de una arquitectura común en fin de soportar las comunicaciones 5G.Para validar estas propuestas, se han presentado una serie de validaciones experimentales por medio de escenarios de prueba específicos, demostrando los avances en control, orquestación, virtualización y manejo de recursos con el fin de optimizar su utilización. Los resultados expuestos, además de corroborar la correcta operación de los métodos y componentes propuestos, abre el camino hacia nuevas formas de adaptar los actuales despliegues de red respecto a los desafíos definidos en el inicio de una nueva era de las telecomunicaciones.Postprint (published version

Holographic MIMO Communications: Theoretical Foundations, Enabling Technologies, and Future Directions

Future wireless systems are envisioned to create an endogenously holography-capable, intelligent, and programmable radio propagation environment, that will offer unprecedented capabilities for high spectral and energy efficiency, low latency, and massive connectivity. A potential and promising technology for supporting the expected extreme requirements of the sixth-generation (6G) communication systems is the concept of the holographic multiple-input multiple-output (HMIMO), which will actualize holographic radios with reasonable power consumption and fabrication cost. The HMIMO is facilitated by ultra-thin, extremely large, and nearly continuous surfaces that incorporate reconfigurable and sub-wavelength-spaced antennas and/or metamaterials. Such surfaces comprising dense electromagnetic (EM) excited elements are capable of recording and manipulating impinging fields with utmost flexibility and precision, as well as with reduced cost and power consumption, thereby shaping arbitrary-intended EM waves with high energy efficiency. The powerful EM processing capability of HMIMO opens up the possibility of wireless communications of holographic imaging level, paving the way for signal processing techniques realized in the EM-domain, possibly in conjunction with their digital-domain counterparts. However, in spite of the significant potential, the studies on HMIMO communications are still at an initial stage, its fundamental limits remain to be unveiled, and a certain number of critical technical challenges need to be addressed. In this survey, we present a comprehensive overview of the latest advances in the HMIMO communications paradigm, with a special focus on their physical aspects, their theoretical foundations, as well as the enabling technologies for HMIMO systems. We also compare the HMIMO with existing multi-antenna technologies, especially the massive MIMO, present various...Comment: double column, 58 page