A Reduced Complexity Ungerboeck Receiver for Quantized Wideband Massive SC-MIMO

Employing low resolution analog-to-digital converters in massive multiple-input multiple-output (MIMO) has many advantages in terms of total power consumption, cost and feasibility of such systems. However, such advantages come together with significant challenges in channel estimation and data detection due to the severe quantization noise present. In this study, we propose a novel iterative receiver for quantized uplink single carrier MIMO (SC-MIMO) utilizing an efficient message passing algorithm based on the Bussgang decomposition and Ungerboeck factorization, which avoids the use of a complex whitening filter. A reduced state sequence estimator with bidirectional decision feedback is also derived, achieving remarkable complexity reduction compared to the existing receivers for quantized SC-MIMO in the literature, without any requirement on the sparsity of the transmission channel. Moreover, the linear minimum mean-square-error (LMMSE) channel estimator for SC-MIMO under frequency-selective channel, which do not require any cyclic-prefix overhead, is also derived. We observe that the proposed receiver has significant performance gains with respect to the existing receivers in the literature under imperfect channel state information.Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Efficient DSP and Circuit Architectures for Massive MIMO: State-of-the-Art and Future Directions

Massive MIMO is a compelling wireless access concept that relies on the use of an excess number of base-station antennas, relative to the number of active terminals. This technology is a main component of 5G New Radio (NR) and addresses all important requirements of future wireless standards: a great capacity increase, the support of many simultaneous users, and improvement in energy efficiency. Massive MIMO requires the simultaneous processing of signals from many antenna chains, and computational operations on large matrices. The complexity of the digital processing has been viewed as a fundamental obstacle to the feasibility of Massive MIMO in the past. Recent advances on system-algorithm-hardware co-design have led to extremely energy-efficient implementations. These exploit opportunities in deeply-scaled silicon technologies and perform partly distributed processing to cope with the bottlenecks encountered in the interconnection of many signals. For example, prototype ASIC implementations have demonstrated zero-forcing precoding in real time at a 55 mW power consumption (20 MHz bandwidth, 128 antennas, multiplexing of 8 terminals). Coarse and even error-prone digital processing in the antenna paths permits a reduction of consumption with a factor of 2 to 5. This article summarizes the fundamental technical contributions to efficient digital signal processing for Massive MIMO. The opportunities and constraints on operating on low-complexity RF and analog hardware chains are clarified. It illustrates how terminals can benefit from improved energy efficiency. The status of technology and real-life prototypes discussed. Open challenges and directions for future research are suggested.Comment: submitted to IEEE transactions on signal processin

Accelerated and Deep Expectation Maximization for One-Bit MIMO-OFDM Detection

In this paper we study the expectation maximization (EM) technique for one-bit MIMO-OFDM detection (OMOD). Arising from the recent interest in massive MIMO with one-bit analog-to-digital converters, OMOD is a massive-scale problem. EM is an iterative method that can exploit the OFDM structure to process the problem in a per-iteration efficient fashion. In this study we analyze the convergence rate of EM for a class of approximate maximum-likelihood OMOD formulations, or, in a broader sense, a class of problems involving regression from quantized data. We show how the SNR and channel conditions can have an impact on the convergence rate. We do so by making a connection between the EM and the proximal gradient methods in the context of OMOD. This connection also gives us insight to build new accelerated and/or inexact EM schemes. The accelerated scheme has faster convergence in theory, and the inexact scheme provides us with the flexibility to implement EM more efficiently, with convergence guarantee. Furthermore we develop a deep EM algorithm, wherein we take the structure of our inexact EM algorithm and apply deep unfolding to train an efficient structured deep net. Simulation results show that our accelerated exact/inexact EM algorithms run much faster than their standard EM counterparts, and that the deep EM algorithm gives promising detection and runtime performances

SYMBOL LEVEL PRECODING TECHNIQUES FOR HARDWARE AND POWER EFFICIENT WIRELESS TRANSCEIVERS

Large-scale antennas are crucial for next generation wireless communication systems as they improve spectral efficiency, reliability and coverage compared to the traditional ones that are employing antenna arrays of few elements. However, the large number of antenna elements leads to a big increase in power consumption of conventional fully digital transceivers due to the one Radio Frequency (RF) chain / per antenna element requirement. The RF chains include a number of different components among which are the Digital-to-Analog Converters (DACs)/Analog-to-Digital Converters (ADCs) that their power consumption increases exponential with the resolution they support. Motivated by this, in this thesis, a number of different architectures are proposed with the view to reduce the power consumption and the hardware complexity of the transceiver. In order to optimize the transmission of data through them, corresponding symbol level precoding (SLP) techniques were developed for the proposed architectures. SLP is a technique that mitigates multi-user interference (MUI) by designing the transmitted signals using the Channel State Information and the information-bearing symbols. The cases of both frequency flat and frequency selective channels were considered. First, three different power efficient transmitter designs for transmission over frequency flat channels and their respective SLP schemes are considered. The considered systems tackle the high hardware complexity and power consumption of existing SLP techniques by reducing or completely eliminating fully digital RF chains. The precoding design is formulated as a constrained least squares problem and efficient algorithmic solutions are developed via the Coordinate Descent method. Next, the case of frequency selective channels is considered. To this end, Constant Envelope precoding in a Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing system (CE MIMO-OFDM) is considered. In CE MIMO-OFDM the transmitted signals for each antenna are designed to have constant amplitude regardless of the channel realization and the information symbols that must be conveyed to the users. This facilitates the use of power-efficient components, such as phase shifters and non-linear power amplifiers. The precoding problem is firstly formulated as a least-squares problem with a unit-modulus constraint and solved using an algorithm based on the coordinate descent (CCD) optimization framework and then, after reformulating the problem into an unconstrained non-linear least squares problem, a more computationally efficient solution using the Gauss-Newton algorithm is presented. Then, CE MIMO-OFDM is considered for a system with low resolution DACs. The precoding design problem is formulated as a mixed discrete- continuous least-squares optimization one which is NP-hard. An efficient low complexity solution is developed based also on the CCD optimization framework. Finally, a precoding scheme is presented for OFDM transmission in MIMO systems based on one-bit DACs and ADCs at the transmitter’s and the receiver’s end, respectively, as a way to reduce the total power consumption. The objective of the precoding design is to mitigate the effects of one-bit quantization and the problem is formulated and then is split into two NP hard least squares optimization problems. Algorithmic solutions are developed for the solution of the latter problems, based on the CCD framework

Real-Time Waveform Prototyping

Mobile Netzwerke der fünften Generation zeichen sich aus durch vielfältigen Anforderungen und Einsatzszenarien. Drei unterschiedliche Anwendungsfälle sind hierbei besonders relevant: 1) Industrie-Applikationen fordern Echtzeitfunkübertragungen mit besonders niedrigen Ausfallraten. 2) Internet-of-things-Anwendungen erfordern die Anbindung einer Vielzahl von verteilten Sensoren. 3) Die Datenraten für Anwendung wie z.B. der Übermittlung von Videoinhalten sind massiv gestiegen. Diese zum Teil gegensätzlichen Erwartungen veranlassen Forscher und Ingenieure dazu, neue Konzepte und Technologien für zukünftige drahtlose Kommunikationssysteme in Betracht zu ziehen. Ziel ist es, aus einer Vielzahl neuer Ideen vielversprechende Kandidatentechnologien zu identifizieren und zu entscheiden, welche für die Umsetzung in zukünftige Produkte geeignet sind. Die Herausforderungen, diese Anforderungen zu erreichen, liegen jedoch jenseits der Möglichkeiten, die eine einzelne Verarbeitungsschicht in einem drahtlosen Netzwerk bieten kann. Daher müssen mehrere Forschungsbereiche Forschungsideen gemeinsam nutzen. Diese Arbeit beschreibt daher eine Plattform als Basis für zukünftige experimentelle Erforschung von drahtlosen Netzwerken unter reellen Bedingungen. Es werden folgende drei Aspekte näher vorgestellt: Zunächst erfolgt ein Überblick über moderne Prototypen und Testbed-Lösungen, die auf großes Interesse, Nachfrage, aber auch Förderungsmöglichkeiten stoßen. Allerdings ist der Entwicklungsaufwand nicht unerheblich und richtet sich stark nach den gewählten Eigenschaften der Plattform. Der Auswahlprozess ist jedoch aufgrund der Menge der verfügbaren Optionen und ihrer jeweiligen (versteckten) Implikationen komplex. Daher wird ein Leitfaden anhand verschiedener Beispiele vorgestellt, mit dem Ziel Erwartungen im Vergleich zu den für den Prototyp erforderlichen Aufwänden zu bewerten. Zweitens wird ein flexibler, aber echtzeitfähiger Signalprozessor eingeführt, der auf einer software-programmierbaren Funkplattform läuft. Der Prozessor ermöglicht die Rekonfiguration wichtiger Parameter der physikalischen Schicht während der Laufzeit, um eine Vielzahl moderner Wellenformen zu erzeugen. Es werden vier Parametereinstellungen 'LLC', 'WiFi', 'eMBB' und 'IoT' vorgestellt, um die Anforderungen der verschiedenen drahtlosen Anwendungen widerzuspiegeln. Diese werden dann zur Evaluierung der die in dieser Arbeit vorgestellte Implementierung herangezogen. Drittens wird durch die Einführung einer generischen Testinfrastruktur die Einbeziehung externer Partner aus der Ferne ermöglicht. Das Testfeld kann hier für verschiedenste Experimente flexibel auf die Anforderungen drahtloser Technologien zugeschnitten werden. Mit Hilfe der Testinfrastruktur wird die Leistung des vorgestellten Transceivers hinsichtlich Latenz, erreichbarem Durchsatz und Paketfehlerraten bewertet. Die öffentliche Demonstration eines taktilen Internet-Prototypen, unter Verwendung von Roboterarmen in einer Mehrbenutzerumgebung, konnte erfolgreich durchgeführt und bei mehreren Gelegenheiten präsentiert werden.:List of figures List of tables Abbreviations Notations 1 Introduction 1.1 Wireless applications 1.2 Motivation 1.3 Software-Defined Radio 1.4 State of the art 1.5 Testbed 1.6 Summary 2 Background 2.1 System Model 2.2 PHY Layer Structure 2.3 Generalized Frequency Division Multiplexing 2.4 Wireless Standards 2.4.1 IEEE 802.15.4 2.4.2 802.11 WLAN 2.4.3 LTE 2.4.4 Low Latency Industrial Wireless Communications 2.4.5 Summary 3 Wireless Prototyping 3.1 Testbed Examples 3.1.1 PHY - focused Testbeds 3.1.2 MAC - focused Testbeds 3.1.3 Network - focused testbeds 3.1.4 Generic testbeds 3.2 Considerations 3.3 Use cases and Scenarios 3.4 Requirements 3.5 Methodology 3.6 Hardware Platform 3.6.1 Host 3.6.2 FPGA 3.6.3 Hybrid 3.6.4 ASIC 3.7 Software Platform 3.7.1 Testbed Management Frameworks 3.7.2 Development Frameworks 3.7.3 Software Implementations 3.8 Deployment 3.9 Discussion 3.10 Conclusion 4 Flexible Transceiver 4.1 Signal Processing Modules 4.1.1 MAC interface 4.1.2 Encoding and Mapping 4.1.3 Modem 4.1.4 Post modem processing 4.1.5 Synchronization 4.1.6 Channel Estimation and Equalization 4.1.7 Demapping 4.1.8 Flexible Configuration 4.2 Analysis 4.2.1 Numerical Precision 4.2.2 Spectral analysis 4.2.3 Latency 4.2.4 Resource Consumption 4.3 Discussion 4.3.1 Extension to MIMO 4.4 Summary 5 Testbed 5.1 Infrastructure 5.2 Automation 5.3 Software Defined Radio Platform 5.4 Radio Frequency Front-end 5.4.1 Sub 6 GHz front-end 5.4.2 26 GHz mmWave front-end 5.5 Performance evaluation 5.6 Summary 6 Experiments 6.1 Single Link 6.1.1 Infrastructure 6.1.2 Single Link Experiments 6.1.3 End-to-End 6.2 Multi-User 6.3 26 GHz mmWave experimentation 6.4 Summary 7 Key lessons 7.1 Limitations Experienced During Development 7.2 Prototyping Future 7.3 Open points 7.4 Workflow 7.5 Summary 8 Conclusions 8.1 Future Work 8.1.1 Prototyping Workflow 8.1.2 Flexible Transceiver Core 8.1.3 Experimental Data-sets 8.1.4 Evolved Access Point Prototype For Industrial Networks 8.1.5 Testbed Standardization A Additional Resources A.1 Fourier Transform Blocks A.2 Resource Consumption A.3 Channel Sounding using Chirp sequences A.3.1 SNR Estimation A.3.2 Channel Estimation A.4 Hardware part listThe demand to achieve higher data rates for the Enhanced Mobile Broadband scenario and novel fifth generation use cases like Ultra-Reliable Low-Latency and Massive Machine-type Communications drive researchers and engineers to consider new concepts and technologies for future wireless communication systems. The goal is to identify promising candidate technologies among a vast number of new ideas and to decide, which are suitable for implementation in future products. However, the challenges to achieve those demands are beyond the capabilities a single processing layer in a wireless network can offer. Therefore, several research domains have to collaboratively exploit research ideas. This thesis presents a platform to provide a base for future applied research on wireless networks. Firstly, by giving an overview of state-of-the-art prototypes and testbed solutions. Secondly by introducing a flexible, yet real-time physical layer signal processor running on a software defined radio platform. The processor enables reconfiguring important parameters of the physical layer during run-time in order to create a multitude of modern waveforms. Thirdly, by introducing a generic test infrastructure, which can be tailored to prototype diverse wireless technology and which is remotely accessible in order to invite new ideas by third parties. Using the test infrastructure, the performance of the flexible transceiver is evaluated regarding latency, achievable throughput and packet error rates.:List of figures List of tables Abbreviations Notations 1 Introduction 1.1 Wireless applications 1.2 Motivation 1.3 Software-Defined Radio 1.4 State of the art 1.5 Testbed 1.6 Summary 2 Background 2.1 System Model 2.2 PHY Layer Structure 2.3 Generalized Frequency Division Multiplexing 2.4 Wireless Standards 2.4.1 IEEE 802.15.4 2.4.2 802.11 WLAN 2.4.3 LTE 2.4.4 Low Latency Industrial Wireless Communications 2.4.5 Summary 3 Wireless Prototyping 3.1 Testbed Examples 3.1.1 PHY - focused Testbeds 3.1.2 MAC - focused Testbeds 3.1.3 Network - focused testbeds 3.1.4 Generic testbeds 3.2 Considerations 3.3 Use cases and Scenarios 3.4 Requirements 3.5 Methodology 3.6 Hardware Platform 3.6.1 Host 3.6.2 FPGA 3.6.3 Hybrid 3.6.4 ASIC 3.7 Software Platform 3.7.1 Testbed Management Frameworks 3.7.2 Development Frameworks 3.7.3 Software Implementations 3.8 Deployment 3.9 Discussion 3.10 Conclusion 4 Flexible Transceiver 4.1 Signal Processing Modules 4.1.1 MAC interface 4.1.2 Encoding and Mapping 4.1.3 Modem 4.1.4 Post modem processing 4.1.5 Synchronization 4.1.6 Channel Estimation and Equalization 4.1.7 Demapping 4.1.8 Flexible Configuration 4.2 Analysis 4.2.1 Numerical Precision 4.2.2 Spectral analysis 4.2.3 Latency 4.2.4 Resource Consumption 4.3 Discussion 4.3.1 Extension to MIMO 4.4 Summary 5 Testbed 5.1 Infrastructure 5.2 Automation 5.3 Software Defined Radio Platform 5.4 Radio Frequency Front-end 5.4.1 Sub 6 GHz front-end 5.4.2 26 GHz mmWave front-end 5.5 Performance evaluation 5.6 Summary 6 Experiments 6.1 Single Link 6.1.1 Infrastructure 6.1.2 Single Link Experiments 6.1.3 End-to-End 6.2 Multi-User 6.3 26 GHz mmWave experimentation 6.4 Summary 7 Key lessons 7.1 Limitations Experienced During Development 7.2 Prototyping Future 7.3 Open points 7.4 Workflow 7.5 Summary 8 Conclusions 8.1 Future Work 8.1.1 Prototyping Workflow 8.1.2 Flexible Transceiver Core 8.1.3 Experimental Data-sets 8.1.4 Evolved Access Point Prototype For Industrial Networks 8.1.5 Testbed Standardization A Additional Resources A.1 Fourier Transform Blocks A.2 Resource Consumption A.3 Channel Sounding using Chirp sequences A.3.1 SNR Estimation A.3.2 Channel Estimation A.4 Hardware part lis

Real-time Digital Signal Processing for Software-defined Optical Transmitters and Receivers

A software-defined optical Tx is designed and demonstrated generating signals with various formats and pulse-shapes in real-time. Special pulse-shapes such as OFDM or Nyquist signaling were utilized resulting in a highly efficient usage of the available fiber channel bandwidth. This was achieved by parallel data processing with high-end FPGAs. Furthermore, highly efficient Rx algorithms for carrier and timing recovery as well as for polarization demultiplexing were developed and investigated

Experimental Investigations of Millimeter Wave Beamforming

The millimeter wave (mmW) band, commonly referred to as the frequency band between 30 GHz and 300 GHz, is seen as a possible candidate to increase achievable rates for mobile applications due to the existence of free spectrum. However, the high path loss necessitates the use of highly directional antennas. Furthermore, impairments and power constraints make it difficult to provide full digital beamforming systems. In this thesis, we approach this problem by proposing effective beam alignment and beam tracking algorithms for low-complex analog beamforming (ABF) systems, showing their applicability by experimental demonstration. After taking a closer look at particular features of the mmW channel properties and introducing the beamforming as a spatial filter, we begin our investigations with the application of detection theory for the non-convex beam alignment problem. Based on an M-ary hypothesis test, we derive algorithms for defining the length of the training signal efficiently. Using the concept of black-box optimization algorithms, which allow optimization of non-convex algorithms, we propose a beam alignment algorithm for codebook-based ABF based systems, which is shown to reduce the training overhead significantly. As a low-complex alternative, we propose a two-staged gradient-based beam alignment algorithm that uses convex optimization strategies after finding a subregion of the beam alignment function in which the function can be regarded convex. This algorithm is implemented in a real-time prototype system and shows its superiority over the exhaustive search approach in simulations and experiments. Finally, we propose a beam tracking algorithm for supporting mobility. Experiments and comparisons with a ray-tracing channel model show that it can be used efficiently in line of sight (LoS) and non line of sight (NLoS) scenarios for walking-speed movements

Real-Time Localization Using Software Defined Radio

Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system