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-

Double binary turbo codes analysis and decoder implementation

Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 2008.Thesis (Master's) -- Bilkent University, 2008.Includes bibliographical references leaves 60-61.Classical Turbo Code presented in 1993 by Berrau et al. received great attention due to its near Shannon Limit decoding performance. Double Binary Circular Turbo Code is an improvement on Classical Turbo Code and widely used in today’s communication standards, such as IEEE 802.16 (WIMAX) and DVBRSC. Compared to Classical Turbo Codes, DB-CTC has better error-correcting capability but more computational complexity for the decoder scheme. In this work, various methods, offered to decrease the computational complexity and memory requirements of DB-CTC decoder in the literature, are analyzed to find the optimum solution for the FPGA implementation of the decoder. IEEE 802.16 standard is taken into account for all simulations presented in this work and different simulations are performed according to the specifications given in the standard. An efficient DB-CTC decoder is implemented on an FPGA board and compared with other implementations in the literature.Yılmaz, ÖzlemM.S

Turbo NOC: a framework for the design of Network-on-Chip-basedturbo decoder architectures

This paper proposes a general framework for the design and simulation of network-on-chip-based turbo decoder architectures. Several parameters in the design space are investigated, namely, network topology, parallelism degree, the rate at which messages are sent by processing nodes over the network, and routing strategy. The main results of this analysis are as follows: 1) the most suited topologies to achieve high throughput with a limited complexity overhead are generalized de Bruijn and generalized Kautz topologies and 2) depending on the throughput requirements, different parallelism degrees, message injection rates, and routing algorithms can be used to minimize the network area overhead

VLSI decoding architectures: flexibility, robustness and performance

Stemming from previous studies on flexible LDPC decoders, this thesis work has been mainly focused on the development of flexible turbo and LDPC decoder designs, and on the narrowing of the power, area and speed gap they might present with respect to dedicated solutions. Additional studies have been carried out within the field of increased code performance and of decoder resiliency to hardware errors. The first chapter regroups several main contributions in the design and implementation of flexible channel decoders. The first part concerns the design of a Network-on-Chip (NoC) serving as an interconnection network for a partially parallel LDPC decoder. A best-fit NoC architecture is designed and a complete multi-standard turbo/LDPC decoder is designed and implemented. Every time the code is changed, the decoder must be reconfigured. A number of variables influence the duration of the reconfiguration process, starting from the involved codes down to decoder design choices. These are taken in account in the flexible decoder designed, and novel traffic reduction and optimization methods are then implemented. In the second chapter a study on the early stopping of iterations for LDPC decoders is presented. The energy expenditure of any LDPC decoder is directly linked to the iterative nature of the decoding algorithm. We propose an innovative multi-standard early stopping criterion for LDPC decoders that observes the evolution of simple metrics and relies on on-the-fly threshold computation. Its effectiveness is evaluated against existing techniques both in terms of saved iterations and, after implementation, in terms of actual energy saving. The third chapter portrays a study on the resilience of LDPC decoders under the effect of memory errors. Given that the purpose of channel decoders is to correct errors, LDPC decoders are intrinsically characterized by a certain degree of resistance to hardware faults. This characteristic, together with the soft nature of the stored values, results in LDPC decoders being affected differently according to the meaning of the wrong bits: ad-hoc error protection techniques, like the Unequal Error Protection devised in this chapter, can consequently be applied to different bits according to their significance. In the fourth chapter the serial concatenation of LDPC and turbo codes is presented. The concatenated FEC targets very high error correction capabilities, joining the performance of turbo codes at low SNR with that of LDPC codes at high SNR, and outperforming both current deep-space FEC schemes and concatenation-based FECs. A unified decoder for the concatenated scheme is subsequently propose