VLSI implementation of a multi-mode turbo/LDPC decoder architecture

Flexible and reconfigurable architectures have gained wide popularity in the communications field. In particular, reconfigurable architectures for the physical layer are an attractive solution not only to switch among different coding modes but also to achieve interoperability. This work concentrates on the design of a reconfigurable architecture for both turbo and LDPC codes decoding. The novel contributions of this paper are: i) tackling the reconfiguration issue introducing a formal and systematic treatment that, to the best of our knowledge, was not previously addressed; ii) proposing a reconfigurable NoCbased turbo/LDPC decoder architecture and showing that wide flexibility can be achieved with a small complexity overhead. Obtained results show that dynamic switching between most of considered communication standards is possible without pausing the decoding activity. Moreover, post-layout results show that tailoring the proposed architecture to the WiMAX standard leads to an area occupation of 2.75 mm2 and a power consumption of 101.5 mW in the worst case

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-

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

20 years of turbo coding and energy-aware design guidelines for energy-constrained wireless applications

During the last two decades, wireless communication has been revolutionized by near-capacity error-correcting codes (ECCs), such as turbo codes (TCs), which offer a lower bit error ratio (BER) than their predecessors, without requiring an increased transmission energy consumption (EC). Hence, TCs have found widespread employment in spectrum-constrained wireless communication applications, such as cellular telephony, wireless local area network, and broadcast systems. Recently, however, TCs have also been considered for energy-constrained wireless communication applications, such as wireless sensor networks and the `Internet of Things.' In these applications, TCs may also be employed for reducing the required transmission EC, instead of improving the BER. However, TCs have relatively high computational complexities, and hence, the associated signal-processing-related ECs are not insignificant. Therefore, when parameterizing TCs for employment in energy-constrained applications, both the processing EC and the transmission EC must be jointly considered. In this tutorial, we investigate holistic design methodologies conceived for this purpose. We commence by introducing turbo coding in detail, highlighting the various parameters of TCs and characterizing their impact on the encoded bit rate, on the radio frequency bandwidth requirement, on the transmission EC and on the BER. Following this, energy-efficient TC decoder application-specific integrated circuit (ASIC) architecture designs are exemplified, and the processing EC is characterized as a function of the TC parameters. Finally, the TC parameters are selected in order to minimize the sum of the processing EC and the transmission EC