Short Block-length Codes for Ultra-Reliable Low-Latency Communications

This paper reviews the state of the art channel coding techniques for ultra-reliable low latency communication (URLLC). The stringent requirements of URLLC services, such as ultra-high reliability and low latency, have made it the most challenging feature of the fifth generation (5G) mobile systems. The problem is even more challenging for the services beyond the 5G promise, such as tele-surgery and factory automation, which require latencies less than 1ms and failure rate as low as $10^{-9}$. The very low latency requirements of URLLC do not allow traditional approaches such as re-transmission to be used to increase the reliability. On the other hand, to guarantee the delay requirements, the block length needs to be small, so conventional channel codes, originally designed and optimised for moderate-to-long block-lengths, show notable deficiencies for short blocks. This paper provides an overview on channel coding techniques for short block lengths and compares them in terms of performance and complexity. Several important research directions are identified and discussed in more detail with several possible solutions.Comment: Accepted for publication in IEEE Communications Magazin

Turbo Decoding and Detection for Wireless Applications

A historical perspective of turbo coding and turbo transceivers inspired by the generic turbo principles is provided, as it evolved from Shannon’s visionary predictions. More specifically, we commence by discussing the turbo principles, which have been shown to be capable of performing close to Shannon’s capacity limit. We continue by reviewing the classic maximum a posteriori probability decoder. These discussions are followed by studying the effect of a range of system parameters in a systematic fashion, in order to gauge their performance ramifications. In the second part of this treatise, we focus our attention on the family of iterative receivers designed for wireless communication systems, which were partly inspired by the invention of turbo codes. More specifically, the family of iteratively detected joint coding and modulation schemes, turbo equalization, concatenated spacetime and channel coding arrangements, as well as multi-user detection and three-stage multimedia systems are highlighted

Application of a design space exploration tool to enhance interleaver generation

This paper presents a methodology to efficiently explore the design space of communication adapters. In most digital signal processing (DSP) applications, the overall performance of the system is significantly affected by communication architectures, as a consequence the designers need specifically optimized adapters. By explicitly modeling these communications within an effective graph-theoretic model and analysis framework, we automatically generate an optimized architecture, named Space-Time AdapteR (STAR). Our design flow inputs a C description of Input/Output data scheduling, and user requirements (throughput, latency, parallelism...), and formalizes communication constraints through a Resource Constraints Graph (RCG). Design space exploration is then performed through associated tools, to synthesize a STAR component under time-to-market constraints. The proposed approach has been tested to design an industrial data mixing block example: an Ultra-Wideband interleaver

Combating channels with long impulse response using combined turbo equalization and turbo decoding.

by Chan Yiu Tong.Thesis (M.Phil.)--Chinese University of Hong Kong, 2000.Includes bibliographical references (leaves 56-[59]).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Communications and Coding Technology --- p.2Chapter 1.2 --- The Emerge of Turbo Codes --- p.3Chapter 1.3 --- The Extension of Turbo Principle --- p.3Chapter 1.4 --- Receiver Structures for Practical Situations --- p.4Chapter 1.5 --- Thesis Overview --- p.5Chapter 2 --- ISI Channel Model and Channel Equalization --- p.6Chapter 2.1 --- A Discrete Time ISI Channel Model --- p.6Chapter 2.1.1 --- Optimum Maximum Likelihood Receiver --- p.8Chapter 2.1.2 --- The Whitened Matched Filter --- p.11Chapter 2.2 --- Equalization Techniques for Combating ISI --- p.13Chapter 2.2.1 --- Linear MMSE Equalizer --- p.13Chapter 2.2.2 --- MLSE Equalizer in Viterbi Algorithm --- p.15Chapter 3 --- An Overview of Turbo Codes --- p.18Chapter 3.1 --- The Turbo Encoder --- p.19Chapter 3.2 --- The Turbo Interleaver --- p.21Chapter 3.3 --- The Iterative Decoder --- p.22Chapter 3.3.1 --- The MAP Algorithm --- p.23Chapter 3.3.2 --- The Max-Log MAP Algorithm --- p.25Chapter 3.3.3 --- The Log-MAP Algorithm --- p.28Chapter 4 --- Receivers for Channels with Long Impulse Responses --- p.29Chapter 4.1 --- Shortcomings for the Existing Models --- p.30Chapter 4.2 --- Proposed System Architecture --- p.30Chapter 4.2.1 --- Optimized Model for Channel Shortening Filter --- p.31Chapter 4.2.2 --- Method One - Separate Trellises for EQ and DEC --- p.35Chapter 4.2.3 --- Method Two - Combined Trellises for EQ and DEC --- p.37Chapter 5 --- Performance Analysis --- p.40Chapter 5.1 --- Simulation Model and Settings --- p.40Chapter 5.2 --- Performance Expectations --- p.43Chapter 5.3 --- Simulation Results and Discussions --- p.49Chapter 6 --- Concluding Remarks --- p.55Bibliography --- p.5