A hardware implementation of a Viterbi decoder for a (3,2/3) TCM code

The report details the design of a dedicated Viterbi decoder chip set for an Ungerboek (3,2/3) Trellis Coded Modulation code. It was the specific intention of the thesis to design a system that could be implemented on standard Field Programmable Gate Arrays (FPGA) yet still be able to cope with high bit rates. The focus of the research was to both evaluate and modify the existing VLSI design techniques and to develop new techniques to make this possible. Trellis Coded Modulation refers to a specific sub-class of convolutional codes that ire an example of coded modulation. In coded modulation there is a direct link between the encoding and modulation processes aimed at improving the performance of the code by introducing redundancy in the signal set used to transmit the code. Ungerboek developed a technique for mapping the encoded words onto points in the signal set, called mapping by set partitioning, that maximises the Euclidian distance between adjacent codewords, and hence maximises the minimum distance between any two output sequences in the code. The Viterbi algorithm is a maximum likelihood decoder for convolutional codes such as TCM. The operation of the Viterbi algorithm is based on using soft decision decoding to produce an estimate of how well the received sequence corresponds with any of the allowed code sequences. The code sequences which most closely matches the received sequence is then decoded to form the output of the decoder. A central problem in implementing systems using TCM with Viterbi decoding is that although the encoder is a relatively simple device, the decoder is not. The complexity of the Viterbi decoder for any given TCM scheme will be the major drawback in implementing the scheme. As such techniques for reducing the complexity of Viterbi decoders are of interest to developers of communication systems. The algorithms describing the implementation and operation of the Viterbi algorithm can be categorised into three main layers. The top layer holds the theoretical algorithm itself, in the second layer are the set of algorithms that describe the broad techniques used to manipulate the theoretical algorithm into a form in which it can be implemented, and the third layer of algorithms describe the implementations themselves. The work contained in this thesis concentrates on the second two layers of algorithms

A novel high-speed trellis-coded modulation encoder/decoder ASIC design

Trellis-coded Modulation (TCM) is used in bandlimited communication systems. TCM efficiency improves coding gain by combining modulation and forward error correction coding in one process. In TCM, the bandwidth expansion is not required because it uses the same symbol rate and power spectrum; the differences are the introduction of a redundancy bit and the use of a constellation with double points. In this thesis, a novel TCM encoder/decoder ASIC chip implementation is presented. This ASIC codec not only increases decoding speed but also reduces hardware complexity. The algorithm and technique are presented for a 16-state convolutional code which is used in standard 256-QAM wireless systems. In the decoder, a Hamming distance is used as a cost function to determine output in the maximum likelihood Viterbi decoder. Using the relationship between the delay states and the path state in the Trellis tree of the code, a pre-calculated Hamming distances are stored in a look-up table. In addition, an output look-up-table is generated to determine the decoder output. This table is established by the two relative delay states in the code. The thesis provides details of the algorithm and the structure of TCM codec chip. Besides using parallel processing, the ASIC implementation also uses pipelining to further increase decoding speed. The codec was implemented in ASIC using standard 0.18ƒÝm CMOS technology; the ASIC core occupied a silicon area of 1.1mm2. All register transfer level code of the codec was simulated and synthesized. The chip layout was generated and the final chip was fabricated by Taiwan Semiconductor Manufacturing Company through the Canadian Microelectronics Corporation. The functional testing of the fabricated codec was performed partially successful; the timing testing has not been fully accomplished because the chip was not always stable

An FPGA Design of High-Speed Adaptive Turbo Decoder for Broadband Wireless Communications

This thesis proposes an adaptive turbo decoding algorithm for high order modulation scheme combined with original design for a standard rate-1/2 turbo decoder for B/QPSK modulation. A transformation applied to the incoming I-channel and Q-channel symbols allows the use of an off-the-shelf B/QPSK turbo decoder without any modifications. Adaptive turbo decoder processes the received symbols recursively to improve the performance. As the number of iterations increases, the execution time and power consumption also increase as well. To reduce the latency and power consumption, this thesis employs the combination of the radix-4, dual-path processing, parallel decoding, and early-stop algorithms. This thesis implemented the proposed scheme on a field-programmable gate array (FPGA) and compared its decoding speed with that of a conventional decoder. From the result of implementation, it was found that the decoding speed of proposed adaptive decoding is faster than that of conventional scheme by 6.4 times under the following conditions : N=212, iteration=3, 8-states, 3 iterations, and 8PSK modulation scheme.Chapter I. Introduction = 1 Chapter II. Adaptive Turbo Decoding Algorithm = 4 2.1 Mapping of bits to signal = 7 2.2 Coset Symbol Transformer(CST) = 8 2.3 Phase Sector Quantizer(PSQ) = 10 2.4 Simulation Results = 13 Chapter III. High Speed Turbo Decoder Algorithm = 15 3.1 Radix-4 Algorithm = 16 3.2 Dual-Path Processing Algorithm = 18 3.3 Parallel Decoding Algorithm = 21 3.4 Early Stop Algorithm = 22 3.5 Simulation Results = 23 Chapter IV. Design of the Adaptive High-Speed Turbo Decoder = 24 4.1 The Adaptive High-Speed Turbo Decoder Structure = 25 4.2 The Optimum Quantized Bits of the Adaptive Turbo Decoder = 28 4.3 FPGA Implementation = 29 Chapter V. Conclusion = 33 References = 3

VLSI Implementation of Encoder and Decoder for Advanced Communication Systems

Forward Error Correction (FEC) schemes are an essential component of wireless communication systems.Present wireless standards such as Third generation (3G) systems, GSM, 802.11A, 802.16 utilize some configuration of convolutional coding. Convolutional encoding with Viterbi decoding is a powerful method for forward error correction. The Viterbi algorithm is the most extensively employed decoding algorithm for convolutional codes which comprises of minimum path and value calculation and retracing the path. The efficiency of error detection and correction increases with constraint length. In this paper the convolutional encoder and viterbi decoder are implemented on FPGA for constraint length of 9 and bit rate ½

Exploring High Level Synthesis to Improve the Design of Turbo Code Error Correction in a Software Defined Radio Context

With the ever improving progress of technology, Software Defined Radio (SDR) has become a more widely available technique for implementing radio communication. SDRs are sought after for their advantages over traditional radio communication mostly in flexibility, and hardware simplification. The greatest challenges SDRs face are often with their real time performance requirements. Forward error correction is an example of an SDR block that can exemplify these challenges as the error correction can be very computationally intensive. Due to these constraints, SDR implementations are commonly found in or alongside Field Programmable Gate Arrays (FPGAs) to enable performance that general purpose processors alone cannot achieve. The main challenge with FPGAs however, is in Register Transfer Level (RTL) development. High Level Synthesis (HLS) tools are a method of creating hardware descriptions from high level code, in an effort to ease this development process. In this work a turbo code decoder, a form of computationally intensive error correction codes, was accelerated with the help of FPGAs, using HLS tools. This accelerator was implemented on a Xilinx Zynq platform, which integrates a hard core ARM processor alongside programmable logic on a single chip. Important aspects of the design process using HLS were identified and explained. The design process emphasizes the idea that for the best results the high level code should be created with a hardware mindset, and written in an attempt to describe a hardware design. The power of the HLS tools was demonstrated in its flexibility by providing a method of tailoring the hardware parameters through simply changing values in a macro file, and by exploration the design space through different data types and three different designs, each one improving from what was learned in the previous implementation. Ultimately, the best hardware implementation was over 56 times faster than the optimized software implementation. Comparing the HLS to a manually optimized design shows that the HLS implementation was able to achieve over a 19% throughput, with many areas for further improvement identified, demonstrating the competitiveness of the HLS tools