Datacenter Design for Future Cloud Radio Access Network.

Cloud radio access network (C-RAN), an emerging cloud service that combines the traditional radio access network (RAN) with cloud computing technology, has been proposed as a solution to handle the growing energy consumption and cost of the traditional RAN. Through aggregating baseband units (BBUs) in a centralized cloud datacenter, C-RAN reduces energy and cost, and improves wireless throughput and quality of service. However, designing a datacenter for C-RAN has not yet been studied. In this dissertation, I investigate how a datacenter for C-RAN BBUs should be built on commodity servers. I first design WiBench, an open-source benchmark suite containing the key signal processing kernels of many mainstream wireless protocols, and study its characteristics. The characterization study shows that there is abundant data level parallelism (DLP) and thread level parallelism (TLP). Based on this result, I then develop high performance software implementations of C-RAN BBU kernels in C++ and CUDA for both CPUs and GPUs. In addition, I generalize the GPU parallelization techniques of the Turbo decoder to the trellis algorithms, an important family of algorithms that are widely used in data compression and channel coding. Then I evaluate the performance of commodity CPU servers and GPU servers. The study shows that the datacenter with GPU servers can meet the LTE standard throughput with 4× to 16× fewer machines than with CPU servers. A further energy and cost analysis show that GPU servers can save on average 13× more energy and 6× more cost. Thus, I propose the C-RAN datacenter be built using GPUs as a server platform. Next I study resource management techniques to handle the temporal and spatial traffic imbalance in a C-RAN datacenter. I propose a “hill-climbing” power management that combines powering-off GPUs and DVFS to match the temporal C-RAN traffic pattern. Under a practical traffic model, this technique saves 40% of the BBU energy in a GPU-based C-RAN datacenter. For spatial traffic imbalance, I propose three workload distribution techniques to improve load balance and throughput. Among all three techniques, pipelining packets has the most throughput improvement at 10% and 16% for balanced and unbalanced loads, respectively.PhDComputer Science and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120825/1/qizheng_1.pd

6G White Paper on Machine Learning in Wireless Communication Networks

The focus of this white paper is on machine learning (ML) in wireless communications. 6G wireless communication networks will be the backbone of the digital transformation of societies by providing ubiquitous, reliable, and near-instant wireless connectivity for humans and machines. Recent advances in ML research has led enable a wide range of novel technologies such as self-driving vehicles and voice assistants. Such innovation is possible as a result of the availability of advanced ML models, large datasets, and high computational power. On the other hand, the ever-increasing demand for connectivity will require a lot of innovation in 6G wireless networks, and ML tools will play a major role in solving problems in the wireless domain. In this paper, we provide an overview of the vision of how ML will impact the wireless communication systems. We first give an overview of the ML methods that have the highest potential to be used in wireless networks. Then, we discuss the problems that can be solved by using ML in various layers of the network such as the physical layer, medium access layer, and application layer. Zero-touch optimization of wireless networks using ML is another interesting aspect that is discussed in this paper. Finally, at the end of each section, important research questions that the section aims to answer are presented

Implementation of New Multiple Access Technique Encoder for 5G Wireless Telecomunication Networks

RÉSUMÉ Les exigences de la connectivité mobile massive de différents appareils et de diverses applications déterminent les besoins des prochaines générations de technologies mobiles (5G) afin de surmonter les demandes futures. L'expansion significative de la connectivité et de la densité du trafic caractérisent les besoins de la cinquième génération de réseaux mobiles. Par conséquent, pour la 5G, il est nécessaire d'avoir une densité de connectivité beaucoup plus élevée et une plus grande portée de mobilité, un débit beaucoup plus élevé et une latence beaucoup plus faible. En raison de l'exigence d'une connectivité massive, de nombreuses nouvelles technologies doivent être améliorées: le codage des canaux, la technique d'accès multiple, la modulation et la diversité, etc. Par conséquent, compte tenu de l'environnement 5G, surcoût de signalisation et de la latence devrait être pris en compte [1]. En outre, l'application de la virtualisation des accès sans fil (WAV) devrait également être considérée et, par conséquent, il est également nécessaire de concevoir la plate-forme matérielle prenant en charge les nouvelles normes pour la mise en œuvre des émetteurs-récepteurs virtuels. L'une des nouvelles technologies possibles pour la 5G est l'accès multiple pour améliorer le débit. Par conséquent, au lieu d'OFDMA utilisé dans la norme LTE (4G), l'application d'une nouvelle technique d'accès multiple appelée Sparse Code Multiple Access (SCMA) est investiguée dans cette dissertation. SCMA est une nouvelle technique d'accès multiple non orthogonale du domaine fréquentiel proposée pour améliorer l'efficacité spectrale de l'accès radio sans fil [2]. L'encodage SCMA est l'un des algorithmes les plus simples dans les techniques d'accès multiple qui offre l'opportunité d'expérimenter des méthodes génériques de mise en oeuvre. En outre, la nouvelle méthode d'accès multiple est supposée fournir un débit plus élevé. Le choix du codage SCMA avec moins de complexité pourrait être une approche appropriée. La cible fixée pour cette recherche était d'atteindre un débit d’encodage de plus de 1 Gbps pour le codeur SCMA. Les implémentations de codage SCMA ont été effectuées à la fois en logiciel et en matériel pour permettre de les comparer. Les implémentations logicielles ont été développées avec le langage de programmation C. Parmi plusieurs conceptions, la performance a été améliorée en utilisant différentes méthodes pour augmenter le parallélisme, diminuer la complexité de calcul et par conséquent le temps de traitement.----------ABSTRACT The demands of massive mobile connectivity of different devices and diverse applications at the same time set requirments for next generations of mobile technology (5G). The significant expansion of connectivity and traffic density characterize the requirements of fifth generation mobile. Therefore, in 5G, there is a need to have much higher connectivity density, higher mobility ranges, much higher throughput, and much lower latency. In pursuance of the requirement of massive connectivity, numerous technologies must be improved: channel coding, multiple access technique, modulation and diversity, etc. For instance, with 5G, the cost of signaling overhead and latency should be taken into account [1]. Besides, applying wireless access virtualization (WAV) should be considered and there is also a need to have effective implementations supporting novel virtual transceiver. One of the possible new technologies for 5G is exploiting multiple access techniques to improve throughput. Therefore, instead of OFDMA in LTE (4G), applying a new multiple access technique called Sparse Code Multiple Access (SCMA) is an approach considered in this dissertation. SCMA is a new frequency domain non-orthogonal multiple access technique proposed to improve spectral efficiency of wireless radio access [2]. SCMA encoding is one of the simplest multiple access technique that offers an opportunity to experiment generic implementation methods. In addition, the new multiple access method is supposed to provide higher throughput, thus choosing SCMA encoding with less complexity could be an appropriate approach. The target with SCMA was to achieve an encoding throughput of more that 1Gbps. SCMA encoding implementations were done both in software and hardware to allow comparing them. The software implementations were developed with the C programing language. Among several designs, the performance was improved by using different methods to increase parallelism, decrease the computational complexity and consequently the processing time. The best achieved results with software implementations offer a 3.59 Gbps throughput, which is 3.5 times more that the target. For hardware implementation, high level synthesis was experimented. In order to do that, the C based functions and testbenches which were developed for software implementations, were used as inputs to Vivado HLS

Near Deterministic Signal Processing Using GPU, DPDK, and MKL

RÉSUMÉ En radio défnie par logiciel, le traitement numcrique du signal impose le traitement en temps réel des donnés et des signaux. En outre, dans le développement de systèmes de communication sans fil basées sur la norme dite Long Term Evolution (LTE), le temps réel et une faible latence des processus de calcul sont essentiels pour obtenir une bonne experience utilisateur. De plus, la latence des calculs est une clé essentielle dans le traitement LTE, nous voulons explorer si des unités de traitement graphique (GPU) peuvent être utilisées pour accélérer le traitement LTE. Dans ce but, nous explorons la technologie GPU de NVIDIA en utilisant le modéle de programmation Compute Unified Device Architecture (CUDA) pour réduire le temps de calcul associé au traitement LTE. Nous présentons briévement l'architecture CUDA et le traitement paralléle avec GPU sous Matlab, puis nous comparons les temps de calculs avec Matlab et CUDA. Nous concluons que CUDA et Matlab accélérent le temps de calcul des fonctions qui sont basées sur des algorithmes de traitement en paralléle et qui ont le même type de données, mais que cette accélération est fortement variable en fonction de l'algorithme implanté. Intel a proposé une boite à outil pour le développement de plan de données (DPDK) pour faciliter le développement des logiciels de haute performance pour le traitement des fonctionnalités de télécommunication. Dans ce projet, nous explorons son utilisation ainsi que celle de l'isolation du système d'exploitation pour réduire la variabilité des temps de calcul des processus de LTE. Plus précisément, nous utilisons DPDK avec la Math Kernel Library (MKL) pour calculer la transformée de Fourier rapide (FFT) associée avec le processus LTE et nous mesurons leur temps de calcul. Nous évaluons quatre cas: 1) code FFT dans le cœur esclave sans isolation du CPU, 2) code FFT dans le cœur esclave avec l'isolation du CPU, 3) code FFT utilisant MKL sans DPDK et 4) code FFT de base. Nous combinons DPDK et MKL pour les cas 1 et 2 et évaluons quel cas est plus déterministe et réduit le plus la latence des processus LTE. Nous montrons que le temps de calcul moyen pour la FFT de base est environ 100 fois plus grand alors que l'écart-type est environ 20 fois plus élevé. On constate que MKL offre d'excellentes performances, mais comme il n'est pas extensible par lui-même dans le domaine infonuagique, le combiner avec DPDK est une alternative très prometteuse. DPDK permet d'améliorer la performance, la gestion de la mémoire et rend MKL évolutif.----------ABSTRACT In software defined radio, digital signal processing requires strict real time processing of data and signals. Specifically, in the development of the Long Term Evolution (LTE) standard, real time and low latency of computation processes are essential to obtain good user experience. As low latency computation is critical in real time processing of LTE, we explore the possibility of using Graphics Processing Units (GPUs) to accelerate its functions. As the first contribution of this thesis, we adopt NVIDIA GPU technology using the Compute Unified Device Architecture (CUDA) programming model in order to reduce the computation times of LTE. Furthermore, we investigate the efficiency of using MATLAB for parallel computing on GPUs. This allows us to evaluate MATLAB and CUDA programming paradigms and provide a comprehensive comparison between them for parallel computing of LTE processes on GPUs. We conclude that CUDA and Matlab accelerate processing of structured basic algorithms but that acceleration is variable and depends which algorithm is involved. Intel has proposed its Data Plane Development Kit (DPDK) as a tool to develop high performance software for processing of telecommunication data. As the second contribution of this thesis, we explore the possibility of using DPDK and isolation of operating system to reduce the variability of the computation times of LTE processes. Specifically, we use DPDK along with the Math Kernel Library (MKL) provided by Intel to calculate Fast Fourier Transforms (FFT) associated with LTE processes and measure their computation times. We study the computation times in different scenarios where FFT calculation is done with and without the isolation of processing units along the use of DPDK. Our experimental analysis shows that when DPDK and MKL are simultaneously used and the processing units are isolated, the resulting processing times of FFT calculation are reduced and have a near-deterministic characteristic. Explicitly, using DPDK and MKL along with the isolation of processing units reduces the mean and standard deviation of processing times for FFT calculation by 100 times and 20 times, respectively. Moreover, we conclude that although MKL reduces the computation time of FFTs, it does not offer a scalable solution but combining it with DPDK is a promising avenue

Development of an orchestrator layer for a wireless cloud

In the last years mobile devices have gained much popularity, that's why the current mobile infrastructure is becoming obsolete. Cloud-RAN arises as an excellent candidat to overcome the strong limitations of the existing infrastructure as it uses a centralized administration of the resources. However, the implementation of such infrastructure presents a significant challenge due to the strict real time requirements of the wireless standards and the implementation of efficient administration algorithms. In order to provide solutions to the problems presented above, in this project we have focused on the implementation of a Cloud-RAN infrastructure. Specifically, we have focused on the study of algorithms that allows a better use of the wireless resources. Later, we have carried out a study to analyse the feasibility of the proposed infrastructure and we have compared it with the current infrastructures. Results obtained show that Cloud-RAN allows a better management of the wireless resources thanks to its flexibility and the fact that it is totally reconfigurable. Furthermore, its implementation reduces the CAPEX/OPEX costs significantly with respect to the current infrastructure

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

Dependable Embedded Systems

This Open Access book introduces readers to many new techniques for enhancing and optimizing reliability in embedded systems, which have emerged particularly within the last five years. This book introduces the most prominent reliability concerns from today’s points of view and roughly recapitulates the progress in the community so far. Unlike other books that focus on a single abstraction level such circuit level or system level alone, the focus of this book is to deal with the different reliability challenges across different levels starting from the physical level all the way to the system level (cross-layer approaches). The book aims at demonstrating how new hardware/software co-design solution can be proposed to ef-fectively mitigate reliability degradation such as transistor aging, processor variation, temperature effects, soft errors, etc. Provides readers with latest insights into novel, cross-layer methods and models with respect to dependability of embedded systems; Describes cross-layer approaches that can leverage reliability through techniques that are pro-actively designed with respect to techniques at other layers; Explains run-time adaptation and concepts/means of self-organization, in order to achieve error resiliency in complex, future many core systems

Satellite Networks: Architectures, Applications, and Technologies

Since global satellite networks are moving to the forefront in enhancing the national and global information infrastructures due to communication satellites' unique networking characteristics, a workshop was organized to assess the progress made to date and chart the future. This workshop provided the forum to assess the current state-of-the-art, identify key issues, and highlight the emerging trends in the next-generation architectures, data protocol development, communication interoperability, and applications. Presentations on overview, state-of-the-art in research, development, deployment and applications and future trends on satellite networks are assembled

Algorithm-Architecture Co-Design for Digital Front-Ends in Mobile Receivers

The methodology behind this work has been to use the concept of algorithm-hardware co-design to achieve efficient solutions related to the digital front-end in mobile receivers. It has been shown that, by looking at algorithms and hardware architectures together, more efficient solutions can be found; i.e., efficient with respect to some design measure. In this thesis the main focus have been placed on two such parameters; first reduced complexity algorithms to lower energy consumptions at limited performance degradation, secondly to handle the increasing number of wireless standards that preferably should run on the same hardware platform. To be able to perform this task it is crucial to understand both sides of the table, i.e., both algorithms and concepts for wireless communication as well as the implications arising on the hardware architecture. It is easier to handle the high complexity by separating those disciplines in a way of layered abstraction. However, this representation is imperfect, since many interconnected "details" belonging to different layers are lost in the attempt of handling the complexity. This results in poor implementations and the design of mobile terminals is no exception. Wireless communication standards are often designed based on mathematical algorithms with theoretical boundaries, with few considerations to actual implementation constraints such as, energy consumption, silicon area, etc. This thesis does not try to remove the layer abstraction model, given its undeniable advantages, but rather uses those cross-layer "details" that went missing during the abstraction. This is done in three manners: In the first part, the cross-layer optimization is carried out from the algorithm perspective. Important circuit design parameters, such as quantization are taken into consideration when designing the algorithm for OFDM symbol timing, CFO, and SNR estimation with a single bit, namely, the Sign-Bit. Proof-of-concept circuits were fabricated and showed high potential for low-end receivers. In the second part, the cross-layer optimization is accomplished from the opposite side, i.e., the hardware-architectural side. A SDR architecture is known for its flexibility and scalability over many applications. In this work a filtering application is mapped into software instructions in the SDR architecture in order to make filtering-specific modules redundant, and thus, save silicon area. In the third and last part, the optimization is done from an intermediate point within the algorithm-architecture spectrum. Here, a heterogeneous architecture with a combination of highly efficient and highly flexible modules is used to accomplish initial synchronization in at least two concurrent OFDM standards. A demonstrator was build capable of performing synchronization in any two standards, including LTE, WiFi, and DVB-H

Software Defined Radio Solutions for Wireless Communications Systems

Wireless technologies have been advancing rapidly, especially in the recent years. Design, implementation, and manufacturing of devices supporting the continuously evolving technologies require great efforts. Thus, building platforms compatible with different generations of standards and technologies has gained a lot of interest. As a result, software defined radios (SDRs) are investigated to offer more flexibility and scalability, and reduce the design efforts, compared to the conventional fixed-function hardware-based solutions.This thesis mainly addresses the challenges related to SDR-based implementation of today’s wireless devices. One of the main targets of most of the wireless standards has been to improve the achievable data rates, which imposes strict requirements on the processing platforms. Realizing real-time processing of high throughput signal processing algorithms using SDR-based platforms while maintaining energy consumption close to conventional approaches is a challenging topic that is addressed in this thesis.Firstly, this thesis concentrates on the challenges of a real-time software-based implementation for the very high throughput (VHT) Institute of Electrical and Electronics Engineers (IEEE) 802.11ac amendment from the wireless local area networks (WLAN) family, where an SDR-based solution is introduced for the frequency-domain baseband processing of a multiple-input multipleoutput (MIMO) transmitter and receiver. The feasibility of the implementation is evaluated with respect to the number of clock cycles and the consumed power. Furthermore, a digital front-end (DFE) concept is developed for the IEEE 802.11ac receiver, where the 80 MHz waveform is divided to two 40 MHz signals. This is carried out through time-domain digital filtering and decimation, which is challenging due to the latency and cyclic prefix (CP) budget of the receiver. Different multi-rate channelization architectures are developed, and the software implementation is presented and evaluated in terms of execution time, number of clock cycles, power, and energy consumption on different multi-core platforms.Secondly, this thesis addresses selected advanced techniques developed to realize inband fullduplex (IBFD) systems, which aim at improving spectral efficiency in today’s congested radio spectrum. IBFD refers to concurrent transmission and reception on the same frequency band, where the main challenge to combat is the strong self-interference (SI). In this thesis, an SDRbased solution is introduced, which is capable of real-time mitigation of the SI signal. The implementation results show possibility of achieving real-time sufficient SI suppression under time-varying environments using low-power, mobile-scale multi-core processing platforms. To investigate the challenges associated with SDR implementations for mobile-scale devices with limited processing and power resources, processing platforms suitable for hand-held devices are selected in this thesis work. On the baseband processing side, a very long instruction word (VLIW) processor, optimized for wireless communication applications, is utilized. Furthermore, in the solutions presented for the DFE processing and the digital SI canceller, commercial off-the-shelf (COTS) multi-core central processing units (CPUs) and graphics processing units (GPUs) are used with the aim of investigating the performance enhancement achieved by utilizing parallel processing.Overall, this thesis provides solutions to the challenges of low-power, and real-time software-based implementation of computationally intensive signal processing algorithms for the current and future communications systems