A Flexible LDPC/Turbo Decoder Architecture

Low-density parity-check (LDPC) codes and convolutional Turbo codes are two of the most powerful error correcting codes that are widely used in modern communication systems. In a multi-mode baseband receiver, both LDPC and Turbo decoders may be required. However, the different decoding approaches for LDPC and Turbo codes usually lead to different hardware architectures. In this paper we propose a unified message passing algorithm for LDPC and Turbo codes and introduce a flexible soft-input soft-output (SISO) module to handle LDPC/Turbo decoding. We employ the trellis-based maximum a posteriori (MAP) algorithm as a bridge between LDPC and Turbo codes decoding. We view the LDPC code as a concatenation of n super-codes where each super-code has a simpler trellis structure so that the MAP algorithm can be easily applied to it. We propose a flexible functional unit (FFU) for MAP processing of LDPC and Turbo codes with a low hardware overhead (about 15% area and timing overhead). Based on the FFU, we propose an area-efficient flexible SISO decoder architecture to support LDPC/Turbo codes decoding. Multiple such SISO modules can be embedded into a parallel decoder for higher decoding throughput. As a case study, a flexible LDPC/Turbo decoder has been synthesized on a TSMC 90 nm CMOS technology with a core area of 3.2 mm2. The decoder can support IEEE 802.16e LDPC codes, IEEE 802.11n LDPC codes, and 3GPP LTE Turbo codes. Running at 500 MHz clock frequency, the decoder can sustain up to 600 Mbps LDPC decoding or 450 Mbps Turbo decoding.NokiaNokia Siemens Networks (NSN)XilinxTexas InstrumentsNational Science Foundatio

Advanced Wireless Digital Baseband Signal Processing Beyond 100 Gbit/s

International audienceThe continuing trend towards higher data rates in wireless communication systems will, in addition to a higher spectral efficiency and lowest signal processing latencies, lead to throughput requirements for the digital baseband signal processing beyond 100 Gbit/s, which is at least one order of magnitude higher than the tens of Gbit/s targeted in the 5G standardization. At the same time, advances in silicon technology due to shrinking feature sizes and increased performance parameters alone won't provide the necessary gain, especially in energy efficiency for wireless transceivers, which have tightly constrained power and energy budgets. In this paper, we highlight the challenges for wireless digital baseband signal processing beyond 100 Gbit/s and the limitations of today's architectures. Our focus lies on the channel decoding and MIMO detection, which are major sources of complexity in digital baseband signal processing. We discuss techniques on algorithmic and architectural level, which aim to close this gap. For the first time we show Turbo-Code decoding techniques towards 100 Gbit/s and a complete MIMO receiver beyond 100 Gbit/s in 28 nm technology

A Vision for 5G Channel Coding

Channel coding is a vital but complex component of cellular communication systems, which is used for correcting the communication errors that are caused by noise, interference and poor signal strength. The turbo code was selected as the main channel code in 3G and 4G cellular systems, but the 3GPP standardization group is currently debating whether it should be replaced by the Low Density Parity Check (LDPC) code in 5G. This debate is being driven by the requirements for 5G, which include throughputs of up to 20 Gbps in the downlink to user devices, ultra-low latencies, as well as much greater flexibility to support diverse use-cases, including broadband data, Internet of Things (IoT), vehicular communications and cloud computing. In our previous white paper, we demonstrated that flexible turbo codes can achieve these requirements with superior hardware- and energy-efficiencies than flexible LDPC decoders. However, the proponents of LDPC codes have highlighted that inflexible LDPC decoders can achieve throughputs of 20 Gbps with particularly attractive hardware- and energy- efficiencies. This white paper outlines a vision for 5G, in which channel coding is provided by a flexible turbo code for most use-cases, but which is supported by an inflexible LDPC code for 20 Gbps downlink use-cases, such as fixed wireless broadband. We demonstrate that this approach can meet all of the 5G requirements, while offering hardware- and energy-efficiencies that are significantly better than those of an LDPC-only solution. Furthermore, the proposed approach benefits from synergy with the 3G and 4G turbo code, as well as a significantly faster time-to-market for 5G. These benefits translate to a 5G that is significantly more capable, significantly easier to deploy and significantly lower cost

Turbo codes and turbo algorithms

In the first part of this paper, several basic ideas that prompted the coming of turbo codes are commented on. We then present some personal points of view on the main advances obtained in past years on turbo coding and decoding such as the circular trellis termination of recursive systematic convolutional codes and double-binary turbo codes associated with Max-Log-MAP decoding. A novel evaluation method, called genieinitialised iterative processing (GIIP), is introduced to assess the error performance of iterative processing. We show that using GIIP produces a result that can be viewed as a lower bound of the maximum likelihood iterative decoding and detection performance. Finally, two wireless communication systems are presented to illustrate recent applications of the turbo principle, the first one being multiple-input/multiple-output channel iterative detection and the second one multi-carrier modulation with linear precoding

VLSI Architectures and Rapid Prototyping Testbeds for Wireless Systems

The rapid evolution of wireless access is creating an ever changing variety of standards for indoor and outdoor environments. The real-time processing demands of wireless data rates in excess of 100 Mbps is a challenging problem for architecture design and verification. In this paper, we consider current trends in VLSI architecture and in rapid prototyping testbeds to evaluate these systems. The key phases in multi-standard system design and prototyping include: Algorithm Mapping to Parallel Architectures – based on the real-time data and sampling rate and the resulting area, time and power complexity; Configurable Mappings and Design Exploration – based on heterogeneous architectures consisting of DSP, programmable application-specific instruction (ASIP) processors, and co-processors; and Verification and Testbed Integration – based on prototype implementation on programmable devices and integration with RF units.Nokia Foundation FellowshipNokia CorporationNational InstrumentsNational Science Foundatio

Improving Network-on-Chip-based Turbo Decoder Architectures

In this work novel results concerning Networkon- Chip-based turbo decoder architectures are presented. Stemming from previous publications, this work concentrates first on improving the throughput by exploiting adaptive-bandwidth-reduction techniques. This technique shows in the best case an improvement of more than 60 Mb/s. Moreover, it is known that double-binary turbo decoders require higher area than binary ones. This characteristic has the negative effect of increasing the data width of the network nodes. Thus, the second contribution of this work is to reduce the network complexity to support doublebinary codes, by exploiting bit-level and pseudo-floatingpoint representation of the extrinsic information. These two techniques allow for an area reduction of up to more than the 40 % with a performance degradation of about 0.2 d