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

On the feasibility and applications of in-band full-duplex radios for future wireless networks

Due to the continuous increase of the demands for the wireless network’s capacity, in-band full-duplex (IBFD) has recently become a key research topic due to its potential to double spectral efficiency, reduce latency, enhance emerging applications, etc., by transmitting and receiving simultaneously over the same channel. Meanwhile, many studies in the literature experimentally demonstrated the feasibility of IBFD radios, which leads to the belief that it is possible to introduce IBFD in the standard of the next-generation networks. Therefore, in this thesis, we timely study the feasibility of IBFD and investigate its advantages for emerging applications in future networks. In the first part, we investigate the interference suppression methods to maximize the IBFD gain by minimizing the effects of self-interference (SI) and co-channel interference (CCI). To this end, we first study a 3-step self-interference cancellation (SIC) scheme. We focus on the time domain-based analog canceller and nonlinear digital canceller, explaining their rationale, demonstrating their effectiveness, and finding the optimal design by minimizing the residual effects. To break the limitation of conventional electrical radio frequency (RF) cancellers, we study the photonic-assisted canceller (PAC) and propose a new design, namely a fiber array-based canceller. We propose a new low-complexity tuning algorithm for the PAC. The effectiveness of the proposed fiber array canceller is demonstrated via simulations. Furthermore, we construct a prototype of the fiber array canceller with two taps and carry out experiments in real-world environments. Results show that the 3-step cancellation scheme can bring the SI close to the receiver's noise floor. Then, we consider the multiple-input multiple-output (MIMO) scenarios, proposing to employ hybrid RF-digital beamforming to reduce the implementation cost and studying its effects on the SIC design. Additionally, we propose a user allocation algorithm to reduce the CCI from the physical layer. A heterogeneous industrial Internet of Things (IIoT) scenario is considered, while the proposed algorithm can be generalized by modifying the parameters to fit any other network. In the second part, we study the beamforming schemes for IBFD multi-cell multi-user (IBFD-MCMU) networks. The transceiver hardware impairments (HWIs) and channel uncertainty are considered for robustness. We first enhance zero-forcing (ZF) and maximum ratio transmission and combining (MRTC) beamforming to be compatible with IBFD-MCMU networks in the presence of multi-antenna users. Then, we study beamforming for SIC, which is challenging for MCMU networks due to the limited antennas but complex interference. We propose a minimum mean-squared error (MMSE)-based scheme to enhance the SIC performance while minimizing its effects on the sum rate. Furthermore, we investigate a robust joint power allocation and beamforming (JPABF) scheme, which approaches the performance of existing optimal designs with reduced complexity. Their performance is evaluated and compared through 3GPP-based simulations. In the third part, we investigate the advantages of applying IBFD radios for physical layer security (PLS). We focus on a channel frequency response (CFR)-based secret key generation (SKG) scheme in MIMO systems. We formulate the intrinsic imperfections of IBFD radios (e.g., SIC overheads and noise due to imperfect SIC) and derive their effects on the probing errors. Then we derive closed-form expressions for the secret key capacity (SKC) of the SKG scheme in the presence of a passive eavesdropper. We analyze the asymptotic behavior of the SKC in the high-SNR regime and reveal the fundamental limits for IBFD and half-duplex (HD) radios. Based on the asymptotic SKC, numerical results illustrate that effective analog self-interference cancellation (ASIC) is the basis for IBFD to gain benefits over HD. Additionally, we investigate essential processing for the CFR-based SKG scheme and verify its effectiveness via simulations and the National Institute of Standards and Technology (NIST) test. In the fourth part, we consider a typical application of IBFD radios: integrated sensing and communication (ISAC). To provide reliable services in high-mobility scenarios, we introduce orthogonal time frequency space (OTFS) modulation and develop a novel framework for OTFS-ISAC. We give the channel representation in different domains and reveal the limitations and disadvantages of existing ISAC frameworks for OTFS waveforms and propose a novel radar sensing method, including a conventional MUSIC algorithm for angle estimation and a delay-time domain-based range and velocity estimator. Additionally, we study the communication design based on the estimated radar sensing parameters. To enable reliable IBFD radios in high-mobility scenarios, a SIC scheme compatible with OTFS and rapidly-changing channels is proposed, which is lacking in the literature. Numerical results demonstrate that the proposed ISAC waveform and associated estimation algorithm can provide both reliable communications and accurate radar sensing with reduced latency, improved spectral efficiency, etc

Optimizing multiuser MIMO for access point cooperation in dense wireless networks

As the usage of wireless devices continues to grow rapidly in popularity, wireless networks that were once designed to support a few laptops must now host a much wider range of equipments, including smart phones, tablets, and wearable devices, that often run bandwidth-hungry applications. Improvements in wireless local access network (WLAN) technology are expected to help accommodate the huge traffic demands. In particular, advanced multicell Multiple-Input Multiple-Output (MIMO) techniques, involving the cooperation of APs and multiuser MIMO processing techniques, can be used to satisfy the increasing demands from users in high-density environments. The objective of this thesis is to address the fundamental problems for multiuser MIMO with AP cooperation in dense wireless network settings. First, for a very common multiuser MIMO linear precoding technique, block diagonalization, a novel pairing-and-binary-tree based user selection algorithm is proposed. Second, without the zero-forcing constraint on the multiuser MIMO transmission, a general weighted sum rate maximization problem is formulated for coordinated APs. A scalable algorithm that performs a combined optimization procedure is proposed to determine the user selection and MIMO weights. Third, we study the fair and high-throughput scheduling problem by formally specifying an optimization problem. Two algorithms are proposed to solve the problem using either alternating optimization or a two-stage procedure. Fourth, with the coexistence of both stationary and mobile users, different scheduling strategies are suggested for different user types. The provided theoretical analysis and simulation results in this thesis lay out the foundation for the realization of the clustered WLAN networks with AP cooperation.Ph.D

On the energy efficiency of spatial modulation concepts

Spatial Modulation (SM) is a Multiple-Input Multiple-Output (MIMO) transmission technique which realizes low complexity implementations in wireless communication systems. Due the transmission principle of SM, only one Radio Frequency (RF) chain is required in the transmitter. Therefore, the complexity of the transmitter is lower compared to the complexity of traditional MIMO schemes, such as Spatial MultipleXing (SMX). In addition, because of the single RF chain configuration of SM, only one Power Amplifier (PA) is required in the transmitter. Hence, SM has the potential to exhibit significant Energy Efficiency (EE) benefits. At the receiver side, due to the SM transmission mechanism, detection is conducted using a low complexity (single stream) Maximum Likelihood (ML) detector. However, despite the use of a single stream detector, SM achieves a multiplexing gain. A point-to-point closed-loop variant of SM is receive space modulation. In receive space modulation, the concept of SMis extended at the receiver side, using linear precoding with Channel State Information at the Transmitter (CSIT). Even though receive space modulation does not preserve the single RF chain configuration of SM, due to the deployed linear precoding, it can be efficiently incorporated in a Space Division Multiple Access (SDMA) or in a Virtual Multiple-Input Multiple-Output (VMIMO) architecture. Inspired by the potentials of SM, the objectives of this thesis are the evaluation of the EE of SM and its extension in different forms of MIMO communication. In particular, a realistic power model for the power consumption of a Base Station (BS) is deployed in order to assess the EE of SM in terms of Mbps/J. By taking into account the whole power supply of a BS and considering a Time Division Multiple Access (TDMA) multiple access scheme, it is shown that SM is significantly more energy efficient compared to the traditional MIMO techniques. In the considered system setup, it is shown that SM is up to 67% more energy efficient compared to the benchmark systems. In addition, the concept of space modulation is researched at the receiver side. Specifically, based on the union bound technique, a framework for the evaluation of the Average Bit Error Probability (ABEP), diversity order, and coding gain of receive space modulation is developed. Because receive space modulation deploys linear precoding with CSIT, two new precoding methods which utilize imperfect CSIT are proposed. Furthermore, in this thesis, receive space modulation is incorporated in the broadcast channel. The derivation of the theoretical ABEP, diversity order, and coding gain of the new broadcast scheme is provided. It is concluded that receive space modulation is able to outperform the corresponding traditional MIMO scheme. Finally, SM, receive space modulation, and relaying are combined in order to form a novel virtual MIMO architecture. It is shown that the new architecture practically eliminates or reduces the problem of the inefficient relaying of the uncoordinated virtual MIMO space modulation architectures. This is undertaken by using precoding in a novel fashion. The evaluation of the new architecture is conducted using simulation and theoretical results

Joint precoding and antenna selection in massive mimo systems

This thesis presents an overview of massive multiple-input multiple-output (MIMO) systems and proposes new algorithms to jointly precode and select the antennas. Massive MIMO is a new technology, which is candidate for comprising the fifth-generation (5G) of mobile cellular systems. This technology employs a huge amount of antennas at the base station and can reach high data rates under favorable, or asymptotically favorable, propagation conditions, while using simple linear processing. However, massive MIMO systems have some drawbacks, such as the high cost related to the base stations. A way to deal with this issue is to employ antenna selection algorithms at the base stations. These algorithms reduce the number of active antennas, decreasing the deployment and maintenance costs related to the base stations. Moreover, this thesis also describes a class of nonlinear precoders that are rarely addressed in the literature; these techniques are able to generate precoded sparse signals in order to achieve joint precoding and antenna selection. This thesis proposes two precoders belonging to this class, where the number of selected antennas is controlled by a design parameter. Simulation results show that the proposed precoders reach a lower bit-error rate than the classical antenna selection algorithms. Furthermore, simulation results show that the proposed precoders present a linear relation between the aforementioned design parameter that controls the signals’ sparsity and the number of selected antennas. Such relation is invariant to the number of base station’s antennas and the number of terminals served by this base station.Esta dissertação apresenta uma visão geral sobre MIMO (do termo em inglês, multiple-input multiple-output) massivo e propõe novos algoritmos que permitem a pré-codificacão de sinais e a seleção de antenas de forma simultânea. MIMO massivo é uma nova tecnologia candidata para compor a quinta geração (5G) dos sistemas celulares. Essa tecnologia utiliza uma quantidade muito grande de antenas na estação-base e, sob condições de propagação favorável ou assintoticamente favorável, pode alcançar taxas de transmissão elevadas, ainda que utilizando um simples processamento linear. Entretanto, os sistemas MIMO massivo apresentam algumas desvantagens, como por exemplo, o alto custo de implementação das estações-bases. Uma maneira de lidar com esse problema é utilizar algoritmos de seleção de antenas na estação-base. Com esses algoritmos é possível reduzir o número de antenas ativas e consequentemente reduzir o custo nas estações-bases. Essa dissertação também apresenta uma classe pouco estudada de pré-codificadores não-lineares que buscam sinais pré-codificados esparsos para realizar a seleção de antenas conjuntamente com a pré-codificação. Além disso, este trabalho propõem dois novos pré-codificadores pertencentes a essa classe, para os quais o número de antenas selecionadas é controlado por um parâmetro de projeto. Resultados de simulações mostram que os pré-codificadores propostos conseguem uma BER (do termo em inglês, bit-error rate) menor que os algoritmos clássicos usados para selecionar antenas. Além disso, resultados de simulações mostram que os pré-codificadores propostos apresentam uma relação linear com o parâmetro de projeto que controla a quantidade de antenas selecionadas; tal relação independe do número de antenas na estação-base e do número de terminais servidos por essa estação

DR9.3 Final report of the JRRM and ASM activities

Deliverable del projecte europeu NEWCOM++This deliverable provides the final report with the summary of the activities carried out in NEWCOM++ WPR9, with a particular focus on those obtained during the last year. They address on the one hand RRM and JRRM strategies in heterogeneous scenarios and, on the other hand, spectrum management and opportunistic spectrum access to achieve an efficient spectrum usage. Main outcomes of the workpackage as well as integration indicators are also summarised.Postprint (published version