On Complexity, Energy- and Implementation-Efficiency of Channel Decoders

Future wireless communication systems require efficient and flexible baseband receivers. Meaningful efficiency metrics are key for design space exploration to quantify the algorithmic and the implementation complexity of a receiver. Most of the current established efficiency metrics are based on counting operations, thus neglecting important issues like data and storage complexity. In this paper we introduce suitable energy and area efficiency metrics which resolve the afore-mentioned disadvantages. These are decoded information bit per energy and throughput per area unit. Efficiency metrics are assessed by various implementations of turbo decoders, LDPC decoders and convolutional decoders. New exploration methodologies are presented, which permit an appropriate benchmarking of implementation efficiency, communications performance, and flexibility trade-offs. These exploration methodologies are based on efficiency trajectories rather than a single snapshot metric as done in state-of-the-art approaches.Comment: Submitted to IEEE Transactions on Communication

Flexible LDPC Decoder Architectures

Flexible channel decoding is getting significance with the increase in number of wireless standards and modes within a standard. A flexible channel decoder is a solution providing interstandard and intrastandard support without change in hardware. However, the design of efficient implementation of flexible low-density parity-check (LDPC) code decoders satisfying area, speed, and power constraints is a challenging task and still requires considerable research effort. This paper provides an overview of state-of-the-art in the design of flexible LDPC decoders. The published solutions are evaluated at two levels of architectural design: the processing element (PE) and the interconnection structure. A qualitative and quantitative analysis of different design choices is carried out, and comparison is provided in terms of achieved flexibility, throughput, decoding efficiency, and area (power) consumption

Unified turbo/LDPC code decoder architecture for deep-space communications

Deep-space communications are characterized by extremely critical conditions; current standards foresee the usage of both turbo and low-density-parity-check (LDPC) codes to ensure recovery from received errors, but each of them displays consistent drawbacks. Code concatenation is widely used in all kinds of communication to boost the error correction capabilities of single codes; serial concatenation of turbo and LDPC codes has been recently proven effective enough for deep space communications, being able to overcome the shortcomings of both code types. This work extends the performance analysis of this scheme and proposes a novel hardware decoder architecture for concatenated turbo and LDPC codes based on the same decoding algorithm. This choice leads to a high degree of datapath and memory sharing; postlayout implementation results obtained with complementary metal-oxide semiconductor (CMOS) 90 nm technology show small area occupation (0.98 mm 2 ) and very low power consumption (2.1 mW)

Static Address Generation Easing: a Design Methodology for Parallel Interleaver Architectures

4 pagesInternational audienceFor high throughput applications, turbo-like iterative decoders are implemented with parallel architectures. However, to be efficient parallel architectures require to avoid collision accesses i.e. concurrent read/write accesses should not target the same memory block. This consideration applies to the two main classes of turbo-like codes which are Low Density Parity Check (LDPC) and Turbo-Codes. In this paper we propose a methodology which finds a collision-free mapping of the variables in the memory banks and which optimizes the resulting interleaving architecture. Finally, we show through a pedagogical example the interest of our approach compared to state-of-the-art techniques

State of the art baseband DSP platforms for Software Defined Radio: A survey

Software Defined Radio (SDR) is an innovative approach which is becoming a more and more promising technology for future mobile handsets. Several proposals in the field of embedded systems have been introduced by different universities and industries to support SDR applications. This article presents an overview of current platforms and analyzes the related architectural choices, the current issues in SDR, as well as potential future trends.Peer reviewe

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

On the application of graphics processor to wireless receiver design

In many wireless systems, a Turbo decoder is often combined with a soft-output multiple-input and multiple-output (MIMO) detector at the receiver to maximize performance in many 4G and beyond wireless standards. Although custom application specific designs are usually used to meet this challenge, programmable graphics processing units (GPU) has become an alternative to the traditional ASIC and FPGA solution for wireless applications. However, careful architecture-aware algorithm design and mapping are required to maximize performance of a communication block on GPU. For MIMO soft detection, we implemented a new MIMO soft detection algorithm, multi-pass trellis traversal (MTT). For Turbo decoding, we used a parallel window algorithm. We showed that our implementations can achieve high throughput while maintaining good performance. This work will allow us to implement a complete iterative MIMO receiver in software on GPU in the future