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

Contextual Beamforming: Exploiting Location and AI for Enhanced Wireless Telecommunication Performance

The pervasive nature of wireless telecommunication has made it the foundation for mainstream technologies like automation, smart vehicles, virtual reality, and unmanned aerial vehicles. As these technologies experience widespread adoption in our daily lives, ensuring the reliable performance of cellular networks in mobile scenarios has become a paramount challenge. Beamforming, an integral component of modern mobile networks, enables spatial selectivity and improves network quality. However, many beamforming techniques are iterative, introducing unwanted latency to the system. In recent times, there has been a growing interest in leveraging mobile users' location information to expedite beamforming processes. This paper explores the concept of contextual beamforming, discussing its advantages, disadvantages and implications. Notably, the study presents an impressive 53% improvement in signal-to-noise ratio (SNR) by implementing the adaptive beamforming (MRT) algorithm compared to scenarios without beamforming. It further elucidates how MRT contributes to contextual beamforming. The importance of localization in implementing contextual beamforming is also examined. Additionally, the paper delves into the use of artificial intelligence schemes, including machine learning and deep learning, in implementing contextual beamforming techniques that leverage user location information. Based on the comprehensive review, the results suggest that the combination of MRT and Zero forcing (ZF) techniques, alongside deep neural networks (DNN) employing Bayesian Optimization (BO), represents the most promising approach for contextual beamforming. Furthermore, the study discusses the future potential of programmable switches, such as Tofino, in enabling location-aware beamforming

In-band-full-duplex integrated access and backhaul enabled next generation wireless networks

In sixth generation (6G) wireless networks, the severe traffic congestion in the microwave frequencies motivates the exploration of the large available bandwidth in the millimetre-wave (mmWave) frequencies to achieve higher network capacity and data rate. Since large-scale antenna arrays and dense base station deployment are required, the hybrid beamforming architecture and the recently proposed integrated access and backhaul (IAB) networks become potential candidates for providing cost and hardware-friendly techniques for 6G wireless networks. In addition, in-band-full-duplex (IBFD) has been recently paid much more research attention since it can make the transmission and reception occur in the same time and frequency band, which nearly doubles the communication spectral efficiency (SE) compared with state-of-the-art half-duplex (HD) systems. Since 6G will explore sensing as its new capability, future wireless networks can go far beyond communications. Motivated by this, the development of integrated sensing and communications (ISAC) systems, where radar and communication systems share the same spectrum resources and hardware, has become one of the major goals in 6G. This PhD thesis focuses on the design and analysis of IBFD-IAB wireless networks in the frequency range 2 (FR2) band (≥ 24.250 GHz) at mmWave frequencies for the potential use in 6G. Firstly, we develop a novel design for the single-cell FR2-IBFD-IAB networks with subarray-based hybrid beamforming, which can enhance the SE and coverage while reducing the latency. The radio frequency (RF) beamformers are obtained via RF codebooks given by a modified matrix-wise Linde-Buzo-Gray (LBG) algorithm. The self-interference (SI) is cancelled in three stages, where the first stage of antenna isolation is assumed to be successfully deployed. The second stage consists of the optical domain-based RF cancellation, where cancellers are connected with the RF chain pairs. The third stage is comprised of the digital cancellation via successive interference cancellation followed by minimum mean-squared error (MSE) baseband receiver. Multiuser interference in the access link is cancelled by zero-forcing at the IAB-node transmitter. The proposed codebook algorithm avoids undesirable low-rank behaviour, while the proposed staged-SI cancellation (SIC) shows satisfactory cancellation performance in the wideband IBFD scenario. However, the system performance can be affected by the hardware impairments (HWI) and RF effective channel estimation errors. Secondly, we study an FR2-IBFD-ISAC-IAB network for vehicle-to-everything communications, where the IAB-node acts as a roadside unit performing sensing and communication simultaneously (i.e., at the same time and frequency band). The SI due to the IBFD operation will be cancelled in the propagation, analogue, and digital domains; only the residual SI (RSI) is reserved for performance analysis. Considering the subarray-based hybrid beamforming structure, including HWI and RF effective SI channel estimation error, the unscented Kalman filter is used for tracking multiple vehicles in the studied scenario. The proposed system shows an enhanced SE compared with the HD system, and the tracking MSEs averaged across all vehicles of each state parameter are close to their posterior Cramér-Rao lower bounds. Thirdly, we analyse the performance of the multi-cell wideband single-hop backhaul FR2-IBFD-IAB networks by using stochastic geometry analysis. We model the wired-connected next generation NodeBs (gNBs) as the Matérn hard-core point process (MHCPP) to meet the real-world deployment requirement and reduce the cost caused by wired connection in the network. We first derive association probabilities that reflect how likely the typical user-equipment is served by a gNB or an IAB-node based on the maximum long-term averaged biased-received-desired-signal power criteria. Further, by leveraging the composite Gamma-Lognormal distribution, we derive results for the signal to interference plus noise ratio coverage, capacity with outage, and ergodic capacity of the network. In order to assess the impact of noise, we consider the sidelobe gain on inter-cell interference links and the analogue to digital converter quantization noise. Compared with the HD transmission, the designated system shows an enhanced capacity when the SIC operates successfully. We also study how the power bias and density ratio of the IAB-node to gNB, and the hard-core distance can affect system performance. Overall, this thesis aims to contribute to the research efforts of shaping the 6G wireless networks by designing and analysing the FR2-IBFD-IAB inspired networks in the FR2 band at mmWave frequencies that will be potentially used in 6G for both communication only and ISAC scenarios

Design of limited feedback for robust MMSE precoding in multiuser MISO systems

[Resumen] En este trabajo consideramos un sistema multiusuario con múltiples antenas en transmisión y una única antena en cada uno de los usuarios receptores y que se denota por brevedad como MU-MISO, del inglés Multi–User Multiple–Input/Single–Output. Este modelo MU–MISO se ajusta perfectamente al enlace descendente de un sistema de comunicaciones móviles, donde múltiples antenas situadas en la estación base envían información a varios usuarios dentro de su zona de cobertura y cuyos terminales móviles disponen generalmente de una única antena. Este canal descendente se denomina también canal de difusión (BC, del inglés Broadcast Channel). Cuando se considera un canal de difusión, el transmisor centralizado tiene claramente más grados de libertad que cada uno de los receptores descentralizados, por lo que es más apropiado separar las señales aplicando precodificación en transmisión. Para poder realizar el diseño de los parámetros del precodificador, el transmisor necesita conocer la información de canal (CSI, en inglés Channel State Information) correspondiente a los distintos usuarios receptores. En el caso de sistemas FDD (del inglés, Frequency Division Duplex), esta información puede obtenerse (al menos parcialmente) mediante realimentación, siempre tras haber aplicado un proceso de cuantificación de la información enviada con el objetivo de adaptarse a las condiciones de ancho de banda limitado del canal de retorno

Design and optimization for wireless-powered networks

Wireless Power Transfer (WPT) opens an emerging area of Wireless-Powered Networks (WPNs). In narrowband WPNs, beamforming is recognized as a key technique for enhancing information and energy transfer. However, in multi-antenna multi-sine WPT systems, not only the beamforming gain but also the rectifier nonlinearity can be exploited by a waveform design to boost the end-to-end power transfer efficiency. This thesis proposes and optimizes novel transmission strategies for two types of WPNs: narrowband autonomous relay networks and multi-antenna multi-sine WPT systems. The thesis starts by proposing a novel Energy Flow-Assisted (EFA) relaying strategy for a one-way multi-antenna Amplify-and-Forward (AF) autonomous relay network. In contrast to state-of-the-art autonomous relaying strategies, the EFA enables the relay to simultaneously harvest power from source information signals and a dedicated Energy Flow (EF) from the destination for forwarding. As a baseline, a Non-EFA (NEFA) strategy, where the relay splits power from the source signals, is also investigated. We optimize relay strategies for EFA and NEFA, so as to maximize the end-to-end rate and gain insights into the benefit of the EF. To transmit multiple data streams, we extend the EFA and the NEFA to a Multiple-Input Multiple-Output (MIMO) relay network. A novel iterative algorithm is developed to jointly optimize source precoders and relay matrices for the EFA and the NEFA, in order to maximize the end-to-end rate. Based on a channel diagonalization method, we also propose less complex EFA and NEFA algorithms. In the study of waveform designs for multi-antenna multi-sine WPT, large-scale designs with many sinewaves and transmit antennas, computationally tractable algorithms and optimal multiuser waveforms remain open challenges. To tackle these issues, we propose efficient waveform optimization algorithms to maximize the multiuser weighted-sum/minimum rectenna DC output voltage, assuming perfect Channel State Information at the Transmitter (CSIT). An optimization framework is developed to derive these waveform algorithms. Relaxing the assumption on CSIT, we propose waveform strategies for multi-antenna multi-sine WPT based on waveform selection (WS) and waveform refinement (WR), respectively. Applying the strategies, an energy transmitter can generate preferred waveforms for WPT from predesigned codebooks of waveform precoders, according to limited feedback from an energy receiver, which carries information on the harvested energy. Although the WR-based strategy is suboptimal for maximizing the average rectenna output voltage, it causes a lower overhead than the WS-based strategy. We propose novel algorithms to optimize the codebooks for the two strategies.Open Acces

Millimeter wave MIMO communications : high-resolution angle acquisition and low-resolution time-frequency synchronization

Knowledge of the propagation channel is critical to exploit the full benefit of multiple-input multiple-output (MIMO) techniques in millimeter wave (mmWave) cellular systems. Obtaining accurate channel state information in mmWave systems, however, is challenging due to high estimation overhead, high computational complexity and on-grid setting. It is also desirable to reduce the analog-to-digital converters (ADCs) resolution at mmWave frequencies to reduce power consumption and implementation costs. The use of low-precision ADCs, though, brings new design challenges to practical cellular networks. In the first part of this dissertation, we develop several new methods to estimate and track the mmWave channel's angle-of-departure and angle-of-arrival with high accuracy and low overhead. The key ingredient of the proposed strategies is custom designed beam pairs, from which there exists an invertible function of the angle to be estimated. We further extend the proposed algorithms to dual-polarized MIMO in wideband channels, and angle tracking design for fast-varying environments. We derive analytical angle estimation error performance of the proposed methods in single-path channels. We also use numerical examples to characterize the robustness of the proposed approaches to various transceiver settings and channel conditions. In the second part of this dissertation, we focus on improving the low-resolution time-frequency synchronization performance for mmWave cellular systems. In our system model, the base station uses analog beams to send the synchronization signal with infinite-resolution digital-to-analog converters (DACs). The user equipment employs a fully digital front end to detect the synchronization signal with low-resolution ADCs. For low-resolution timing synchronization, we propose a new multi-beam probing based strategy, targeting at maximizing the minimum received synchronization signal-to-quantization-plus-noise ratio among all serving users. Regarding low-resolution frequency synchronization, we construct new sequences for carrier frequency offset (CFO) estimation and compensation. We use both analytical and numerical examples to show that the proposed sequences and the corresponding metrics used for retrieving the CFOs are robust to the quantization distortion.Electrical and Computer Engineerin

MIMO Systems

In recent years, it was realized that the MIMO communication systems seems to be inevitable in accelerated evolution of high data rates applications due to their potential to dramatically increase the spectral efficiency and simultaneously sending individual information to the corresponding users in wireless systems. This book, intends to provide highlights of the current research topics in the field of MIMO system, to offer a snapshot of the recent advances and major issues faced today by the researchers in the MIMO related areas. The book is written by specialists working in universities and research centers all over the world to cover the fundamental principles and main advanced topics on high data rates wireless communications systems over MIMO channels. Moreover, the book has the advantage of providing a collection of applications that are completely independent and self-contained; thus, the interested reader can choose any chapter and skip to another without losing continuity

Adaptive and Robust Beam Selection in Millimeter-Wave Massive MIMO Systems

Future 6G wireless communications network will increase the data capacity to unprecedented numbers and thus empower the deployment of new real-time applications. Millimeter-Wave (mmWave) band and Massive MIMO are considered as two of the main pillars of 6G to handle the gigantic influx in data traffic and number of mobile users and IoT devices. The small wavelengths at these frequencies mean that more antenna elements can be placed in the same area. Thereby, high spatial processing gains are achievable that can theoretically compensate for the higher isotropic path loss. The propagation characteristics at mmWave band, create sparse channels in typical scenarios, where only few paths convey significant power. Considering this feature, Hybrid (analog-digital) Beamforming introduces a new signal processing framework which enables energy and cost-efficient implementation of massive MIMO with innovative smart arrays. In this setup, the analog beamalignment via beam selection in link access phase, is the critical performance limiting step. Considering the variable operating condition in mmWave channels, a desirable solution should have the following features: efficiency in training (limited coherence time, delay constraints), adaptivity to channel conditions (large SNR range) and robustness to realized channels (LOS, NLOS, Multipath, non-ideal beam patterns). For the link access task, we present a new energy-detection framework based on variable length channel measurements with (orthogonal) beam codebooks. The proposed beam selection technique denoted as composite M-ary Sequential Competition Test (SCT) solves the beam selection problem when knowledge about the SNR operating point is not available. It adaptively changes the test length when the SNR varies to achieve an essentially constant performance level. In addition, it is robust to non-ideal beam patterns and different types of the realized channel. Compared to the conventional fixed length energy-detection techniques, the SCT can increase the training efficiency up to two times while reducing the delay if the channel condition is good. Having the flexibility to allocate resources for channel measurements through different beams adaptively in time, we improve the SCT to eliminate unpromising beams from the remaining candidate set as soon as possible. In this way, the Sequential Competition and Elimination Test (SCET) significantly further reduces training time by increasing the efficiency. The developed ideas can be applied with different codebook types considered for practical applications. The reliable performance of the beam selection technique is evident through experimental evaluation done using the state-of-the-art test-bed developed at the Vodafone Chair that combines a Universal Software Radio Peripheral (USRP) based platform with mmWave frontends