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

Energy Efficient VLSI Circuits for MIMO-WLAN

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