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

Abstract

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. Index TermsChannel coding, algorithmic complexity, energy efficiency, design space exploration, design methodology. I. MOTIVATIONToday, high-end smart phones have to support multiple radio standards, advanced graphic-and media applications and many other applications resulting in a workload of about 100 giga operations per second in a power budget of 1 Watt [1]. The baseband processing in the radio part (mainly front-end processing, demodulation and decoding) requires more than 50% of the overall workload in a state-of-the-art 3.5G smart phone. To achieve higher spectral efficiency new transmission techniques like MIMO will be established. However, this will increase the workload even further. Thus there is a strong need for efficient wireless baseband receivers. The overall efficiency of a baseband receiver depends on • communications efficiency: expressed by the spectral efficiency and signal-to-noise ratio (SNR). The requirements on the communications efficiency have the largest impact on the selected baseband processing algorithms.

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