A LOW-POWER 1-Gbps RECONFIGURABLE LDPC DECODER DESIGN FOR MULTIPLE 4G WIRELESS STANDARDS

In this paper we present an efficient system-on-chip implementation of a 1-Gbps LDPC decoder for 4G (or beyond 3G) wireless standards. The decoder has a scalable data path and can be dynamically reconfigured to support multiple 4G standards. We utilize a pipelined version of the layered belief propagation algorithm to achieve partial-parallel decoding of structured LDPC codes. Instead of using the sub-optimal Minsum algorithm, we propose to use the powerful belief propagation (BP) decoding algorithm by designing an area-efficient soft-input soft-output (SISO) decoder. Two power saving schemes are employed to reduce the power consumption up to 65%. The decoder has been synthesized, placed, and routed on a TSMC 90nm 1.0V 8-metal layer CMOS technology with a total area of 3.5 mm2. The maximum clock frequency is 450 MHz and the estimated peak power consumption is 410 mW.NokiaNational Science Foundatio

Scalable and Low Power LDPC Decoder Design Using High Level Algorithmic Synthesis

This paper presents a scalable and low power low-density parity-check (LDPC) decoder design for the next generation wireless handset SoC. The methodology is based on high level synthesis: PICO (program-in chip-out) tool was used to produce efficient RTL directly from a sequential untimed C algorithm. We propose two parallel LDPC decoder architectures: (1) per-layer decoding architecture with scalable parallelism, and (2) multi-layer pipelined decoding architecture to achieve higher throughput. Based on the PICO technology, we have implemented a two-layer pipelined decoder on a TSMC 65nm 0.9V 8-metal layer CMOS technology with a core area of 1.2 mm2. The maximum achievable throughput is 415 Mbps when operating at 400 MHz clock frequency and the estimated peak power consumption is 180 mW.NokiaNokia Siemens Networks (NSN)XilinxNational Science Foundatio

Comparison of Polar Decoders with Existing Low-Density Parity-Check and Turbo Decoders

Polar codes are a recently proposed family of provably capacity-achieving error-correction codes that received a lot of attention. While their theoretical properties render them interesting, their practicality compared to other types of codes has not been thoroughly studied. Towards this end, in this paper, we perform a comparison of polar decoders against LDPC and Turbo decoders that are used in existing communications standards. More specifically, we compare both the error-correction performance and the hardware efficiency of the corresponding hardware implementations. This comparison enables us to identify applications where polar codes are superior to existing error-correction coding solutions as well as to determine the most promising research direction in terms of the hardware implementation of polar decoders.Comment: Fixes small mistakes from the paper to appear in the proceedings of IEEE WCNC 2017. Results were presented in the "Polar Coding in Wireless Communications: Theory and Implementation" Worksho

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