High-Throughput Contention-Free Concurrent Interleaver Architecture for Multi-Standard Turbo Decoder

To meet the higher data rate requirement of emerging wireless communication technology, numerous parallel turbo decoder architectures have been developed. However, the interleaver has become a major bottleneck that limits the achievable throughput in the parallel decoders due to the massive memory conflicts. In this paper, we propose a flexible Double-Buffer based Contention-Free (DBCF) interleaver architecture that can efficiently solve the memory conflict problem for parallel turbo decoders with very high parallelism. The proposed DBCF architecture enables high throughput concurrent interleaving for multi-standard turbo decoders that support UMTS/HSPA+, LTE and WiMAX, with small datapath delays and low hardware cost. We implemented the DBCF interleaver with a 65nm CMOS technology. The implementation of this highly efficient DBCF interleaver architecture shows significant improvement in terms of the maximum throughput and occupied chip area compared to the previous work.HuaweiNational Science Foundatio

Configurable and Scalable High Throughput Turbo Decoder Architecture for Multiple 4GWireless Standards

In this paper, we propose a novel multi-code turbo decoder architecture for 4G wireless systems. To support various 4G standards, a configurable multi-mode MAP (maximum a posteriori) decoder is designed for both binary and duo-binary turbo codes with small resource overhead (less than 10%) compared to the single-mode architecture. To achieve high data rates in 4G, we present a parallel turbo decoder architecture with scalable parallelism tailored to the given throughput requirements. High-level parallelism is achieved by employing contention-free interleavers. Multi-banked memory structure and routing network among memories and MAP decoders are designed to operate at full speed with parallel interleavers. We designed a very low-complexity recursive on-line address generator supporting multiple interleaving patterns, which avoids the interleaver address memory. Design trade-offs in terms of area and power efficiency are explored to find the optimal architectures. A 711 Mbps data rate is feasible with 32 Radix-4 MAP decoders running at 200 MHz clock rate.Texas Instruments Incorporate

A LOW-POWER 1-Gbps RECONFIGURABLE LDPC DECODER DESIGN FOR MULTIPLE 4G WIRELESS STANDARDS

In this paper we present an efficient system-on-chip implementation of a 1-Gbps LDPC decoder for 4G (or beyond 3G) wireless standards. The decoder has a scalable data path and can be dynamically reconfigured to support multiple 4G standards. We utilize a pipelined version of the layered belief propagation algorithm to achieve partial-parallel decoding of structured LDPC codes. Instead of using the sub-optimal Minsum algorithm, we propose to use the powerful belief propagation (BP) decoding algorithm by designing an area-efficient soft-input soft-output (SISO) decoder. Two power saving schemes are employed to reduce the power consumption up to 65%. The decoder has been synthesized, placed, and routed on a TSMC 90nm 1.0V 8-metal layer CMOS technology with a total area of 3.5 mm2. The maximum clock frequency is 450 MHz and the estimated peak power consumption is 410 mW.NokiaNational Science Foundatio

Link level imuslations for 5G remote area scenario

Abstract. The main object of this thesis is to utilize the Vienna 5G link-level simulator and to introduce modifications which are needed to include new scenarios, such as remote area case. The Vienna 5G link-level simulator is a simulation platform for promoting 5th generation (5G) research and development for the mobile communications system. This work gives a general overview of the link-level simulator platform to evaluate the average performance of the 5G physical layer (PHY) schemes. In many places across the world, there is no reliable internet connectivity in remote areas. Remote area connectivity is a kind of "missing scenario" of standard 5G solution, which focuses on improved data rate, latency, and massive internet of things (IoT). This work addresses views of connectivity in remote areas with 5G solutions, focusing on wireless radio technologies. The study of 5G physical layer performance evaluation is performed for downlink transmission using single-input and single-output (SISO) techniques. This thesis focused on the performance of waveforms, which can be effectively used in remote area communication systems. The analysis of the simulation results signifies that generalized frequency division multiplexing (GFDM) would be the better option for remote area communication than other waveforms investigated in this study. This work also focused on the performance of channel coding schemes in order to determine the appropriate channel coding scheme for the 5G mobile communication system for medium length message transmission in remote area communication. The polar code appears to be the best possible channel code for medium-length message data transmission in remote areas based on the study of channel coding schemes

Energy Conservation and Security Enhancement in Wireless End-to-end Secure Connections

Wireless channels are vulnerable to interception. In some applications an end-to-end secure data transfer is required. However the use of cryptographic functions in communication over a wireless channel increases sensitivity to channel errors. As a result, the connection characteristics in terms of delay, throughput, and transmission energy worsen. Transmission energy is a key issue in some secure end-to-end wireless applications especially if they are running on mobile handheld devices with a limited source of energy such as batteries. That is why in most secure end-to-end wireless connections, the connection is dropped in poor channel conditions. In this thesis, models are proposed by which the performance is improved and transmission energy is lowered. A combination of a cross-layer controller, K Best Likelihood (K-BL) channel decoder, and a keyed error detection algorithm in the novel model supports the authorized receivers by a higher throughput, lower delay mean, and less transmission energy in a certain range of the Signal to Noise Ratio (SNR). This is done at the expense of additional computation at the receiving end. Ttradeoffs are examined and the simulation results of the new model are compared with those of conventional wireless communication systems. Another model is devised to mitigate the energy consumption of the Turbo Code channel decoder. The overall decoding energy consumption for each packet can be lowered by reducing the average number of iterations in the Turbo Code channel decoder. The proposed models achieve better energy consumption by reducing the number of iterations in a channel decoder that uses the Turbo decoder and by reducing the number of retransmissions in a trellis channel decoder. Furthermore, the security enhancement of the novel models is assessed in terms of the extent to which the enhancement is fully achieved

Architecture and Analysis for Next Generation Mobile Signal Processing.

Mobile devices have proliferated at a spectacular rate, with more than 3.3 billion active cell phones in the world. With sales totaling hundreds of billions every year, the mobile phone has arguably become the dominant computing platform, replacing the personal computer. Soon, improvements to today’s smart phones, such as high-bandwidth internet access, high-definition video processing, and human-centric interfaces that integrate voice recognition and video-conferencing will be commonplace. Cost effective and power efficient support for these applications will be required. Looking forward to the next generation of mobile computing, computation requirements will increase by one to three orders of magnitude due to higher data rates, increased complexity algorithms, and greater computation diversity but the power requirements will be just as stringent to ensure reasonable battery lifetimes. The design of the next generation of mobile platforms must address three critical challenges: efficiency, programmability, and adaptivity. The computational efficiency of existing solutions is inadequate and straightforward scaling by increasing the number of cores or the amount of data-level parallelism will not suffice. Programmability provides the opportunity for a single platform to support multiple applications and even multiple standards within each application domain. Programmability also provides: faster time to market as hardware and software development can proceed in parallel; the ability to fix bugs and add features after manufacturing; and, higher chip volumes as a single platform can support a family of mobile devices. Lastly, hardware adaptivity is necessary to maintain efficiency as the computational characteristics of the applications change. Current solutions are tailored specifically for wireless signal processing algorithms, but lose their efficiency when other application domains like high definition video are processed. This thesis addresses these challenges by presenting analysis of next generation mobile signal processing applications and proposing an advanced signal processing architecture to deal with the stringent requirements. An application-centric design approach is taken to design our architecture. First, a next generation wireless protocol and high definition video is analyzed and algorithmic characterizations discussed. From these characterizations, key architectural implications are presented, which form the basis for the advanced signal processor architecture, AnySP.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/86344/1/mwoh_1.pd

Low Power Low-Density Parity Check Encoder Using Dynamic Voltage and Frequency Scaling Approach

Low-Density Parity Check (LDPC) codes are viewed as one of the best error correction coding (ECC) methods in terms of correction efficiency. They have been used in several modern data transmission standards, where the codecs are often built inside specialized integrated circuits (ICs). On the other hand, Complementary Metal-Oxide-Semiconductor (CMOS) circuits have evolved as a critical design characteristic that the designer must consider such as power, which has been overlooked by many researchers. For that reason, in this paper, a research work that reduces LDPC encoder power consumption is presented using a well-known power reduction method named Dynamic Voltage and Frequency Scaling (DVFS), which is one of the most powerful power reduction strategies in CMOS circuits. The proposed system includes a fuzzy logic controller with the DVFS technique to control and select the optimum level of voltage that enters the encoder to reduce its total power consumption. This combination of these two techniques showed significant power reduction and control while causing no impact on the LDPC efficiency, flexibility, and performance. Comparisons with other studies covering power reduction in LDPC codes have shown that the purposed system has the best performance over similar systems in the literature

Managing lifetime reliability, performance, and power tradeoffs in multicore microarchitectures

The objective of this research is to characterize and manage lifetime reliability, microarchitectural performance, and power tradeoffs in multicore processors. This dissertation is comprised of three research themes; 1) modeling and simulation method of interacting multicore processor physics, 2) characterization and management of performance and lifetime reliability tradeoff, and 3) extending Amdahl’s Law for understanding lifetime reliability, performance, and energy efficiency of heterogeneous processors. With continued technology scaling, processor operations are increasingly dominated by multiple distinct physical phenomena and their coupled interactions. Understanding these behaviors requires the modeling of complex physical interactions. This dissertation first presents a novel simulation framework that orchestrates interactions between multiple physical models and microarchitecture simulators to enable research explorations at the intersection of application, microarchitecture, energy, power, thermal, and reliability. Using this framework, workload-induced variation of device degradation is characterized, and its impacts on processor lifetime and performance are analyzed. This research introduces a new metric to quantify performance-reliability tradeoff. Lastly, the theoretical models of heterogeneous multicore processors are proposed for understanding performance, energy efficiency, and lifetime reliability consequences. It is shown that these system metrics are governed by Amdahl’s Law and correlated as a function of processor composition, scheduling method, and Amdahl’s scaling factor. This dissertation highlights the importance of multidimensional analysis and extends the scope of microarchitectural studies by incorporating the physical aspects of processor operations and designs.Ph.D

Development of Lifting-based VLSI Architectures for Two-Dimensional Discrete Wavelet Transform

Two-dimensional discrete wavelet transform (2-D DWT) has evolved as an essential part of a modem compression system. It offers superior compression with good image quality and overcomes disadvantage of the discrete cosine transform, which suffers from blocks artifacts that reduces the quality of the inage. The amount of computations involve in 2-D DWT is enormous and cannot be processed by generalpurpose processors when real-time processing is required. Th·"efore, high speed and low power VLSI architecture that computes 2-D DWT effectively is needed. In this research, several VLSI architectures have been developed that meets real-time requirements for 2-D DWT applications. This research iaitially started off by implementing a software simulation program that decorrelates the original image and reconstructs the original image from the decorrelated image. Then, based on the information gained from implementing the simulation program, a new approach for designing lifting-based VLSI architectures for 2-D forward DWT is introduced. As a result, two high performance VLSI architectures that perform 2-D DWT for 5/3 and 9/7 filters are developed based on overlapped and nonoverlapped scan methods. Then, the intermediate architecture is developed, which aim a·: reducing the power consumption of the overlapped areas without using the expensive line buffer. In order to best meet real-time applications of 2-D DWT with demanding requirements in terms of speed and throughput parallelism is explored. The single pipelined intermediate and overlapped architectures are extended to 2-, 3-, and 4-parallel architectures to achieve speed factors of 2, 3, and 4, respectively. To further demonstrate the effectiveness of the approach single and para.llel VLSI architectures for 2-D inverse discrete wavelet transform (2-D IDWT) are developed. Furthermore, 2-D DWT memory architectures, which have been overlooked in the literature, are also developed. Finally, to show the architectural models developed for 2-D DWT are simple to control, the control algorithms for 4-parallel architecture based on the first scan method is developed. To validate architectures develcped in this work five architectures are implemented and simulated on Altera FPGA. In compliance with the terms of the Copyright Act 1987 and the IP Policy of the university, the copyright of this thesis has been reassigned by the author to the legal entity of the university, Institute of Technology PETRONAS Sdn bhd. Due acknowledgement shall always be made of the use of any material contained in, or derived from, this thesis