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

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

Design and implementation of an OFDM-based communication system for the GNU Radio platform

Projecte final de carrera fet en col.laboració amb Institut für Kommunikationsnetze und Rechnersysteme. Universität StuttgartCatalà: El processament de senyal en temps real mitjançant software és un camp que s'està expandint molt gràcies a la capacitat de processament dels ordinadors actuals. L'objectiu d'aquest treball ha estat el disseny i la implementació d'una Ràdio Definida en Software (SDR) que funcioni amb tecnologia OFDM, similar a la utilitzada en les comunicacions mòvils de 4a generació, per a la plataforma GNU Radio.Castellano: El procesado de señal en tiempo real mediante software es un campo en expansión gracias a la capacidad de computación de los ordenadores actuales. El objetivo de este trabajo ha sido el diseño y la implementación de una Radio Definida en Software (SDR) que funcione con tecnología OFDM, similar a la utilizada en las comunicaciones móviles de 4ª generación, para la plataforma GNU Radio.English: Software based real time signal processing is a field in expansion thanks to the computing capacity of actual personal computers. The objective of this work is the design and the implementation of a Software Defined Radio (SDR) that uses OFDM technology, which is the one used in the 4th generation of wireless communications

EARLY PERFORMANCE PREDICTION METHODOLOGY FOR MANY-CORES ON CHIP BASED APPLICATIONS

Modern high performance computing applications such as personal computing, gaming, numerical simulations require application-specific integrated circuits (ASICs) that comprises of many cores. Performance for these applications depends mainly on latency of interconnects which transfer data between cores that implement applications by distributing tasks. Time-to-market is a critical consideration while designing ASICs for these applications. Therefore, to reduce design cycle time, predicting system performance accurately at an early stage of design is essential. With process technology in nanometer era, physical phenomena such as crosstalk, reflection on the propagating signal have a direct impact on performance. Incorporating these effects provides a better performance estimate at an early stage. This work presents a methodology for better performance prediction at an early stage of design, achieved by mapping system specification to a circuit-level netlist description. At system-level, to simplify description and for efficient simulation, SystemVerilog descriptions are employed. For modeling system performance at this abstraction, queueing theory based bounded queue models are applied. At the circuit level, behavioral Input/Output Buffer Information Specification (IBIS) models can be used for analyzing effects of these physical phenomena on on-chip signal integrity and hence performance. For behavioral circuit-level performance simulation with IBIS models, a netlist must be described consisting of interacting cores and a communication link. Two new netlists, IBIS-ISS and IBIS-AMI-ISS are introduced for this purpose. The cores are represented by a macromodel automatically generated by a developed tool from IBIS models. The generated IBIS models are employed in the new netlists. Early performance prediction methodology maps a system specification to an instance of these netlists to provide a better performance estimate at an early stage of design. The methodology is scalable in nanometer process technology and can be reused in different designs

New Identification and Decoding Techniques for Low-Density Parity-Check Codes

Error-correction coding schemes are indispensable for high-capacity high data-rate communication systems nowadays. Among various channel coding schemes, low-density parity-check (LDPC) codes introduced by pioneer Robert G. Gallager are prominent due to the capacity-approaching and superior error-correcting properties. There is no hard constraint on the code rate of LDPC codes. Consequently, it is ideal to incorporate LDPC codes with various code rate and codeword length in the adaptive modulation and coding (AMC) systems which change the encoder and the modulator adaptively to improve the system throughput. In conventional AMC systems, a dedicated control channel is assigned to coordinate the encoder/decoder changes. A questions then rises: if the AMC system still works when such a control channel is absent. This work gives positive answer to this question by investigating various scenarios consisting of different modulation schemes, such as quadrature-amplitude modulation (QAM), frequency-shift keying (FSK), and different channels, such as additive white Gaussian noise (AWGN) channels and fading channels. On the other hand, LDPC decoding is usually carried out by iterative belief-propagation (BP) algorithms. As LDPC codes become prevalent in advanced communication and storage systems, low-complexity LDPC decoding algorithms are favored in practical applications. In the conventional BP decoding algorithm, the stopping criterion is to check if all the parities are satisfied. This single rule may not be able to identify the undecodable blocks, as a result, the decoding time and power consumption are wasted for executing unnecessary iterations. In this work, we propose a new stopping criterion to identify the undecodable blocks in the early stage of the iterative decoding process. Furthermore, in the conventional BP decoding algorithm, the variable (check) nodes are updated in parallel. It is known that the number of iterations can be reduced by the serial scheduling algorithm. The informed dynamic scheduling (IDS) algorithms were proposed in the existing literatures to further reduce the number of iterations. However, the computational complexity involved in finding the update node in the existing IDS algorithms would not be neglected. In this work, we propose a new efficient IDS scheme which can provide better performance-complexity trade-off compared to the existing IDS ones. In addition, the iterative decoding threshold, which is used for differentiating which LDPC code is better, is investigated in this work. A family of LDPC codes, called LDPC convolutional codes, has drawn a lot of attentions from researchers in recent years due to the threshold saturation phenomenon. The IDT for an LDPC convolutional code may be computationally demanding when the termination length goes to thousand or even approaches infinity, especially for AWGN channels. In this work, we propose a fast IDT estimation algorithm which can greatly reduce the complexity of the IDT calculation for LDPC convolutional codes with arbitrary large termination length (including infinity). By utilizing our new IDT estimation algorithm, the IDTs for LDPC convolutional codes with arbitrary large termination length (including infinity) can be quickly obtained

VLSI Architectures for WIMAX Channel Decoders

This chapter describes the main architectures proposed in the literature to implement the channel decoders required by the WiMax standard, namely convolutional codes, turbo codes (both block and convolutional) and LDPC. Then it shows a complete design of a convolutional turbo code encoder/decoder system for WiMax.Comment: To appear in the book "WIMAX, New Developments", M. Upena, D. Dalal, Y. Kosta (Ed.), ISBN978-953-7619-53-

Advanced Techniques for Future Multicarrier Systems

Future multicarrier systems face the tough challenge of supporting high data-rate and high-quality services. The main limitation is the frequency-selective nature of the propagation channel that affects the received signal, thus degrading the system performance. OFDM can be envisaged as one of the most promising modulation techniques for future communication systems. It exhibits robustness to ISI even in very dispersive environments and its main characteristic is to take advantage of channel diversity by performing dynamic resource allocation. In a multi-user OFDMA scenario, the challenge is to allocate, on the basis of the channel knowledge, different portions of the available frequency spectrum among the users in the systems. Literature on resource allocation for OFDMA systems mainly focused on single-cell systems, where the objective is to assign subcarriers, power and data-rate for each user according to a predetermined criterion. The problem can be formulated with the goal of either maximizing the system sum-rate subject to a constraint on transmitted power or minimizing the overall power consumption under some predetermined constraints on rate per user. Only recently, literature focuses on resource allocation in multi-cell networks, where the goal is not only to take advantage of frequency and multi-user diversity, but also to mitigate MAI, which represents one of the most limiting factor for such problems. We consider a multi-cell OFDMA system with frequency reuse distance equal to one. Allowing all cells to transmit on the whole bandwidth unveils large potential gains in terms of spectral efficiency in comparison with conventional cellular systems. Such a scenario, however, is often deemed unfeasible because of the strong MAI that negatively affects the system performance. In this dissertation we present a layered architecture that integrates a packet scheduler with an adaptive resource allocator, explicitly designed to take care of the multiple access interference. Each cell performs its resource management in a distributed way without any central controller. Iterative resource allocation assigns radio channels to the users so as to minimize the interference. Packet scheduling guarantees that all users get a fair share of resources regardless of their position in the cell. This scheduler-allocator architecture integrates both goals and is able to self adapt to any traffic and user configuration. An adaptive, distributed load control strategy can reduce the cell load so that the iterative procedure always converges to a stable allocation, regardless of the interference. Numerical results show that the proposed architecture guarantees both high spectral efficiency and throughput fairness among flows. In the second part of this dissertation we deal with FBMC communication systems. FBMC modulation is a valid alternative to conventional OFDM signaling as it presents a set of appealing characteristics, such as robustness to narrowband interferers, more flexibility to allocate groups of subchannels to different users/services, and frequency-domain equalization without any cyclic extension. However, like any other multicarrier modulations, FBMC is strongly affected by residual CFOs that have to be accurately estimated. Unlike previously proposed algorithms, whereby frequency is recovered either relying on known pilot symbols multiplexed with the data stream or exploiting specific properties of the multicarrier signal structure following a blind approach, we present and discuss an algorithm based on the ML principle, which takes advantage both of pilot symbols and also indirectly of data symbols through knowledge and exploitation of their specific modulation format. The algorithm requires the availability of the statistical properties of channel fading up to second-order moments. It is shown that the above approach allows to improve on both frequency acquisition range and estimation accuracy of previously published schemes

Design and implementation of an OFDM-based communication system for the GNU Radio platform

Projecte final de carrera fet en col.laboració amb Institut für Kommunikationsnetze und Rechnersysteme. Universität StuttgartCatalà: El processament de senyal en temps real mitjançant software és un camp que s'està expandint molt gràcies a la capacitat de processament dels ordinadors actuals. L'objectiu d'aquest treball ha estat el disseny i la implementació d'una Ràdio Definida en Software (SDR) que funcioni amb tecnologia OFDM, similar a la utilitzada en les comunicacions mòvils de 4a generació, per a la plataforma GNU Radio.Castellano: El procesado de señal en tiempo real mediante software es un campo en expansión gracias a la capacidad de computación de los ordenadores actuales. El objetivo de este trabajo ha sido el diseño y la implementación de una Radio Definida en Software (SDR) que funcione con tecnología OFDM, similar a la utilizada en las comunicaciones móviles de 4ª generación, para la plataforma GNU Radio.English: Software based real time signal processing is a field in expansion thanks to the computing capacity of actual personal computers. The objective of this work is the design and the implementation of a Software Defined Radio (SDR) that uses OFDM technology, which is the one used in the 4th generation of wireless communications

Methods to Improve Applicability and Efficiency of Distributed Data-Centric Compute Frameworks

The success of modern applications depends on the insights they collect from their data repositories. Data repositories for such applications currently exceed exabytes and are rapidly increasing in size, as they collect data from varied sources - web applications, mobile phones, sensors and other connected devices. Distributed storage and data-centric compute frameworks have been invented to store and analyze these large datasets. This dissertation focuses on extending the applicability and improving the efficiency of distributed data-centric compute frameworks