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-

A hardware spinal decoder

Spinal codes are a recently proposed capacity-achieving rateless code. While hardware encoding of spinal codes is straightforward, the design of an efficient, high-speed hardware decoder poses significant challenges. We present the first such decoder. By relaxing data dependencies inherent in the classic M-algorithm decoder, we obtain area and throughput competitive with 3GPP turbo codes as well as greatly reduced latency and complexity. The enabling architectural feature is a novel alpha-beta incremental approximate selection algorithm. We also present a method for obtaining hints which anticipate successful or failed decoding, permitting early termination and/or feedback-driven adaptation of the decoding parameters. We have validated our implementation in FPGA with on-air testing. Provisional hardware synthesis suggests that a near-capacity implementation of spinal codes can achieve a throughput of 12.5 Mbps in a 65 nm technology while using substantially less area than competitive 3GPP turbo code implementations.Irwin Mark Jacobs and Joan Klein Jacobs Presidential FellowshipIntel Corporation (Fellowship)Claude E. Shannon Research Assistantshi

Reliable Low-Latency and Low-Complexity Viterbi Architectures Benchmarked on ASIC and FPGA

The Viterbi algorithm is commonly applied in a number of sensitive usage models including decoding convolutional codes used in communications such as satellite communication, cellular relay, and wireless local area networks. Moreover, the algorithm has been applied to automatic speech recognition and storage devices. In this thesis, efficient error detection schemes for architectures based on low-latency, low-complexity Viterbi decoders are presented. The merit of the proposed schemes is that reliability requirements, overhead tolerance, and performance degradation limits are embedded in the structures and can be adapted accordingly. We also present three variants of recomputing with encoded operands and its modifications to detect both transient and permanent faults, coupled with signature-based schemes. The instrumented decoder architecture has been subjected to extensive error detection assessments through simulations, and application-specific integrated circuit (ASIC) [32nm library] and field-programmable gate array (FPGA) [Xilinx Virtex-6 family] implementations for benchmark. The proposed fine-grained approaches can be utilized based on reliability objectives and performance/implementation metrics degradation tolerance

VLSI Architecture for Configurable and Low-Complexity Design of Hard-Decision Viterbi Decoding Algorithm

Convolutional encoding and data decoding are fundamental processes in convolutional error correction. One of the most popular error correction methods in decoding is the Viterbi algorithm. It is extensively implemented in many digital communication applications. Its VLSI design challenges are about area, speed, power, complexity and configurability. In this research, we specifically propose a VLSI architecture for a configurable and low-complexity design of a hard-decision Viterbi decoding algorithm. The configurable and low-complexity design is achieved by designing a generic VLSI architecture, optimizing each processing element (PE) at the logical operation level and designing a conditional adapter. The proposed design can be configured for any predefined number of trace-backs, only by changing the trace-back parameter value. Its computational process only needs N + 2 clock cycles latency, with N is the number of trace-backs. Its configurability function has been proven for N = 8, N = 16, N = 32 and N = 64. Furthermore, the proposed design was synthesized and evaluated in Xilinx and Altera FPGA target boards for area consumption and speed performance

On chip interconnects for multiprocessor turbo decoding architectures

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