69 research outputs found

    Rapid Industrial Prototyping and SoC Design of 3G/4G Wireless Systems Using an HLS Methodology

    Get PDF
    Many very-high-complexity signal processing algorithms are required in future wireless systems, giving tremendous challenges to real-time implementations. In this paper, we present our industrial rapid prototyping experiences on 3G/4G wireless systems using advanced signal processing algorithms in MIMO-CDMA and MIMO-OFDM systems. Core system design issues are studied and advanced receiver algorithms suitable for implementation are proposed for synchronization, MIMO equalization, and detection. We then present VLSI-oriented complexity reduction schemes and demonstrate how to interact these high-complexity algorithms with an HLS-based methodology for extensive design space exploration. This is achieved by abstracting the main effort from hardware iterations to the algorithmic C/C++ fixed-point design. We also analyze the advantages and limitations of the methodology. Our industrial design experience demonstrates that it is possible to enable an extensive architectural analysis in a short-time frame using HLS methodology, which significantly shortens the time to market for wireless systems.National Science Foundatio

    Energy Efficient VLSI Circuits for MIMO-WLAN

    Get PDF
    Mobile communication - anytime, anywhere access to data and communication services - has been continuously increasing since the operation of the first wireless communication link by Guglielmo Marconi. The demand for higher data rates, despite the limited bandwidth, led to the development of multiple-input multiple-output (MIMO) communication which is often combined with orthogonal frequency division multiplexing (OFDM). Together, these two techniques achieve a high bandwidth efficiency. Unfortunately, techniques such as MIMO-OFDM significantly increase the signal processing complexity of transceivers. While fast improvements in the integrated circuit (IC) technology enabled to implement more signal processing complexity per chip, large efforts had and have to be done for novel algorithms as well as for efficient very large scaled integration (VLSI) architectures in order to meet today's and tomorrow's requirements for mobile wireless communication systems. In this thesis, we will present architectures and VLSI implementations of complete physical (PHY) layer application specific integrated circuits (ASICs) under the constraints imposed by an industrial wireless communication standard. Contrary to many other publications, we do not elaborate individual components of a MIMO-OFDM communication system stand-alone, but in the context of the complete PHY layer ASIC. We will investigate the performance of several MIMO detectors and the corresponding preprocessing circuits, being integrated into the entire PHY layer ASIC, in terms of achievable error-rate, power consumption, and area requirement. Finally, we will assemble the results from the proposed PHY layer implementations in order to enhance the energy efficiency of a transceiver. To this end, we propose a cross-layer optimization of PHY layer and medium access control (MAC) layer

    Systems with Massive Number of Antennas: Distributed Approaches

    Get PDF
    As 5G is entering maturity, the research interest has shifted towards 6G, and specially the new use cases that the future telecommunication infrastructure needs to support. These new use cases encompass much higher requirements, specifically: higher communication data-rates, larger number of users, higher accuracy in localization, possibility to wirelessly charge devices, among others.The radio access network (RAN) has already gone through an evolution on the path towards 5G. One of the main changes was a large increment of the number of antennas in the base-station. Some of them may even reach 100 elements, in what is commonly referred as Massive MIMO. New proposals for 6G RAN point in the direction of continuing this path of increasing the number of antennas, and locate them throughout a certain area of service. Different technologies have been proposed in this direction, such as: cell-free Massive MIMO, distributed MIMO, and large intelligent surface (LIS). In this thesis we focus on LIS, whose conducted theoretical studies promise the fulfillment of the aforementioned requirements.While the theoretical capabilities of LIS have been conveniently analyzed, little has been done in terms of implementing this type of systems. When the number of antennas grow to hundreds or thousands, there are numerous challenges that need to be solved for a successful implementation. The most critical challenges are the interconnection data-rate and the computational complexity.In the present thesis we introduce the implementation challenges, and show that centralized processing architectures are no longer adequate for this type of systems. We also present different distributed processing architectures and show the benefits of this type of schemes. This work aims at giving a system-design guideline that helps the system designer to make the right decisions when designing these type of systems. For that, we provide algorithms, performance analysis and comparisons, including first order evaluation of the interconnection data-rate, processing latency, memory and energy consumption. These numbers are based on models and available data in the literature. Exact values depend on the selected technology, and will be accurately determined after building and testing these type of systems.The thesis concentrates mostly on the topic of communication, with additional exploration of other areas, such as localization. In case of localization, we benefit from the high spatial resolution of a very-large array that provides very rich channel state information (CSI). A CSI-based fingerprinting via neural network technique is selected for this case with promising results. As the communication and localization services are based on the acquisition of CSI, we foresee a common system architecture capable of supporting both cases. Further work in this direction is recommended, with the possibility of including other applications such as sensing.The obtained results indicate that the implementation of these very-large array systems is feasible, but the challenges are numerous. The proposed solutions provide encouraging results that need to be verified with hardware implementations and real measurements

    A real-time deep learning OFDM receiver

    Get PDF

    Architectures multi-Asip pour turbo récepteur flexible

    Get PDF
    Rapidly evolving wireless standards use modern techniques such as turbo codes, Bit Interleaved coded Modulation (BICM), high order QAM constellation, Signal Space Diversity (SSD), Multi-Input Multi-Output (MIMO) Spatial Multiplexing (SM) and Space Time Codes (STC) with different parameters for reliable high rate data transmissions. Adoption of such techniques in the transmitter can impact the receiver architecture in three ways: (1) the complex processing related to advanced techniques such as turbo codes, encourage to perform iterative processing in the receiver to improve error rate performance (2) to satisfy high throughput requirement for an iterative receiver, parallel processing is mandatory and finally (3) to allow the support of different techniques and parameters imposed, programmable yet high throughput hardware processing elements are required. In this thesis, to address the high throughput requirement with turbo processing, first of all a study of parallelism on turbo decoding is extended for turbo demodulation and turbo equalization. Based on the results acquired from the parallelism study a flexible high throughput heterogeneous multi-ASIP NoC based unified turbo receiver is proposed. The proposed architecture fulfils the target requirements in a way that: (a) Application Specific Instruction-set Processor (ASIP) exploits metric generation level parallelism and implements the required flexibility, (b) throughputs beyond the capacity of single ASIP in a turbo process are achieved through multiple ASIP elements implementing sub-block parallelism and shuffled processing and finally (c) Network on Chip is used to handle communication conflicts during parallel processing of multiple ASIPs. In pursuit to achieve a hardware model of the proposed architecture two ASIPs are conceived where the first one, namely EquASIP, is dedicated for MMSE-IC equalization and provides a flexible solution for multiple MIMO techniques adopted in multiple wireless standards with a capability to work in turbo equalization context. The second ASIP, named as DemASIP, is a flexible demapper which can be used in MIMO or single antenna environment for any modulation till 256-QAM with or without iterative demodulation. Using available TurbASIP and NoC components, the thesis concludes on an FPGA prototype of heterogeneous multi-ASIP NoC based unified turbo receiver which integrates 9 instances of 3 different ASIPs with 2 NoCs.Les normes de communication sans fil, sans cesse en évolution, imposent l'utilisation de techniques modernes telles que les turbocodes, modulation codée à entrelacement bit (BICM), constellation MAQ d'ordre élevé, diversité de constellation (SSD), multiplexage spatial et codage espace-temps multi-antennes (MIMO) avec des paramètres différents pour des transmissions fiables et de haut débit. L'adoption de ces techniques dans l'émetteur peut influencer l'architecture du récepteur de trois façons: (1) les traitement complexes relatifs aux techniques avancées comme les turbocodes, encourage à effectuer un traitement itératif dans le récepteur pour améliorer la performance en termes de taux d'erreur (2) pour satisfaire l'exigence de haut débit avec un récepteur itératif, le recours au parallélisme est obligatoire et enfin (3) pour assurer le support des différentes techniques et paramètres imposées, des processeurs de traitement matériel flexibles, mais aussi de haute performance, sont nécessaires. Dans cette thèse, pour répondre aux besoins de haut débit dans un contexte de traitement itératif, tout d'abord une étude de parallélisme sur le turbo décodage a été étendue aux applications de turbo démodulation et turbo égalisation. Partant des résultats obtenus à partir de l'étude du parallélisme, un récepteur itératif unifié basé sur un modèle d'architecture multi-ASIP hétérogène intégrant un réseau sur puce (NoC) a été proposé. L'architecture proposée répond aux exigences visées d'une manière où: (a) le concept de processeur à jeu d'instruction dédié à l'application (ASIP) exploite le parallélisme du niveau de génération de métriques et met en oeuvre la flexibilité nécessaire, (b) les débits au-delà de la capacité d'un seul ASIP dans un processus itératif sont obtenus au moyen de multiples ASIP implémentant le parallélisme de sous-blocs et le traitement combiné et enfin (c) le concept de réseau sur puce (NoC) est utilisé pour gérer les conflits de communication au cours du traitement parallèle itératif multi-ASIP. Dans le but de parvenir à un modèle matériel de l'architecture proposée, deux ASIP ont été conçus où le premier, nommé EquASIP, est dédié à l'égalisation MMSE-IC et fournit une solution flexible pour de multiples techniques multi-antennes adoptés dans plusieurs normes sans fil avec la capacité de travailler dans un contexte de turbo égalisation. Le deuxième ASIP, nommé DemASIP, est un démappeur flexible qui peut être utilisé dans un environnement multi-antennes et pour tout type de modulation jusqu'à MAQ-256 avec ou sans démodulation itérative. En intégrant ces ASIP, en plus des NoC et TurbASIP disponibles à Télécom Bretagne, la thèse conclut sur un prototype FPGA d'un récepteur itératif unifié multi-ASIP qui intègre 9 coeurs de 3 différents types d'ASIP avec 2 NoC

    Turbo Equalization: An Overview

    Full text link

    Modulation, Coding, and Receiver Design for Gigabit mmWave Communication

    Get PDF
    While wireless communication has become an ubiquitous part of our daily life and the world around us, it has not been able yet to deliver the multi-gigabit throughput required for applications like high-definition video transmission or cellular backhaul communication. The throughput limitation of current wireless systems is mainly the result of a shortage of spectrum and the problem of congestion. Recent advancements in circuit design allow the realization of analog frontends for mmWave frequencies between 30GHz and 300GHz, making abundant unused spectrum accessible. However, the transition to mmWave carrier frequencies and GHz bandwidths comes with new challenges for wireless receiver design. Large variations of the channel conditions and high symbol rates require flexible but power-efficient receiver designs. This thesis investigates receiver algorithms and architectures that enable multi-gigabit mmWave communication. Using a system-level approach, the design options between low-power time-domain and power-hungry frequency-domain signal processing are explored. The system discussion is started with an analysis of the problem of parameter synchronization in mmWave systems and its impact on system design. The proposed synchronization architecture extends known synchronization techniques to provide greater flexibility regarding the operating environments and for system efficiency optimization. For frequency-selective environments, versatile single-carrier frequency domain equalization (SC-FDE) offers not only excellent channel equalization, but also the possibility to integrate additional baseband tasks without overhead. Hence, the high initial complexity of SC-FDE needs to be put in perspective to the complexity savings in the other parts of the baseband. Furthermore, an extension to the SC-FDE architecture is proposed that allows an adaptation of the equalization complexity by switching between a cyclic-prefix mode and a reduced block length overlap-save mode based on the delay spread. Approaching the problem of complexity adaptation from time-domain, a high-speed hardware architecture for the delayed decision feedback sequence estimation (DDFSE) algorithm is presented. DDFSE uses decision feedback to reduce the complexity of the sequence estimation and allows to set the system performance between the performance of full maximum-likelihood detection and pure decision feedback equalization. An implementation of the DDFSE architecture is demonstrated as part of an all-digital IEEE802.11ad baseband ASIC manufactured in 40nm CMOS. A flexible architecture for wideband mmWave receivers based on complex sub-sampling is presented. Complex sub-sampling combines the design advantages of sub-sampling receivers with the flexibility of direct-conversion receivers using a single passive component and a digital compensation scheme. Feasibility of the architecture is proven with a 16Gb/s hardware demonstrator. The demonstrator is used to explore the potential gain of non-equidistant constellations for high-throughput mmWave links. Specifically crafted amplitude phase-shift keying (APSK) modulation achieve 1dB average mutual information (AMI) advantage over quadrature amplitude modulation (QAM) in simulation and on the testbed hardware. The AMI advantage of APSK can be leveraged for a practical transmission using Polar codes which are trained specifically for the constellation

    Datacenter Design for Future Cloud Radio Access Network.

    Full text link
    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

    Mapping Framework for Heterogeneous Reconfigurable Architectures:Combining Temporal Partitioning and Multiprocessor Scheduling

    Get PDF
    corecore