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

Viterbi Accelerator for Embedded Processor Datapaths

We present a novel architecture for a lightweight Viterbi accelerator that can be tightly integrated inside an embedded processor. We investigate the accelerator’s impact on processor performance by using the EEMBC Viterbi benchmark and the in-house Viterbi Branch Metric kernel. Our evaluation based on the EEMBC benchmark shows that an accelerated 65-nm 2.7-ns processor datapath is 20% larger but 90% more cycle efficient than a datapath lacking the Viterbi accelerator, leading to an 87% overall energy reduction and a data throughput of 3.52 Mbit/s

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

Turbo NOC: a framework for the design of Network On Chip based turbo decoder architectures

This work 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 the network topology, the parallelism degree, the rate at which messages are sent by processing nodes over the network and the routing strategy. The main results of this analysis are: i) the most suited topologies to achieve high throughput with a limited complexity overhead are generalized de-Bruijn and generalized Kautz topologies; ii) depending on the throughput requirements different parallelism degrees, message injection rates and routing algorithms can be used to minimize the network area overhead.Comment: submitted to IEEE Trans. on Circuits and Systems I (submission date 27 may 2009

High-Level Design Space and Flexibility Exploration for Adaptive, Energy-Efficient WCDMA Channel Estimation Architectures

Due to the fast changing wireless communication standards coupled with strict performance constraints, the demand for flexible yet high-performance architectures is increasing. To tackle the flexibility requirement, software-defined radio (SDR) is emerging as an obvious solution, where the underlying hardware implementation is tuned via software layers to the varied standards depending on power-performance and quality requirements leading to adaptable, cognitive radio. In this paper, we conduct a case study for representatives of two complexity classes of WCDMA channel estimation algorithms and explore the effect of flexibility on energy efficiency using different implementation options. Furthermore, we propose new design guidelines for both highly specialized architectures and highly flexible architectures using high-level synthesis, to enable the required performance and flexibility to support multiple applications. Our experiments with various design points show that the resulting architectures meet the performance constraints of WCDMA and a wide range of options are offered for tuning such architectures depending on power/performance/area constraints of SDR

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