Optimization and Applications of Modern Wireless Networks and Symmetry

Due to the future demands of wireless communications, this book focuses on channel coding, multi-access, network protocol, and the related techniques for IoT/5G. Channel coding is widely used to enhance reliability and spectral efficiency. In particular, low-density parity check (LDPC) codes and polar codes are optimized for next wireless standard. Moreover, advanced network protocol is developed to improve wireless throughput. This invokes a great deal of attention on modern communications

Forward error correction in 5G heterogeneous network

In this research, the feasibility of developing a complete polar FEC chain of 5th generation cellular mobile communication standard in software. Specifically, on general purpose processors. Paper work attempts to achieve stringent latency requirements through software, algorithmic and platform specific optimizations. Many algorithms in FEC chain are optimized for hardware implementations. Direct implementation of these algorithms in software results in poor performance. To obtain best performance in terms of latency on general purpose processors, these algorithms are modified or reformulated to suit processor architecture and software implementation. Initially both encoding and decoding FEC chains are implemented naively without any optimization. Code profiling is performed on this naive implementation to identify the significant latency contributors. The research split algorithms of significant latency contributing components into primitive operations. These primitive operations are optimized either with software optimizations or mapped to specialized functional units of a general-purpose processor to achieve best performance using CRC calculation in 5G cellular networks. Optimizations reduced the worst-case latency of the encoding FEC chain from 158µs which is more than 10x reduction in latency with communication rate

A Very Brief Introduction to Machine Learning With Applications to Communication Systems

Given the unprecedented availability of data and computing resources, there is widespread renewed interest in applying data-driven machine learning methods to problems for which the development of conventional engineering solutions is challenged by modelling or algorithmic deficiencies. This tutorial-style paper starts by addressing the questions of why and when such techniques can be useful. It then provides a high-level introduction to the basics of supervised and unsupervised learning. For both supervised and unsupervised learning, exemplifying applications to communication networks are discussed by distinguishing tasks carried out at the edge and at the cloud segments of the network at different layers of the protocol stack

On the Road to 6G: Visions, Requirements, Key Technologies and Testbeds

Fifth generation (5G) mobile communication systems have entered the stage of commercial development, providing users with new services and improved user experiences as well as offering a host of novel opportunities to various industries. However, 5G still faces many challenges. To address these challenges, international industrial, academic, and standards organizations have commenced research on sixth generation (6G) wireless communication systems. A series of white papers and survey papers have been published, which aim to define 6G in terms of requirements, application scenarios, key technologies, etc. Although ITU-R has been working on the 6G vision and it is expected to reach a consensus on what 6G will be by mid-2023, the related global discussions are still wide open and the existing literature has identified numerous open issues. This paper first provides a comprehensive portrayal of the 6G vision, technical requirements, and application scenarios, covering the current common understanding of 6G. Then, a critical appraisal of the 6G network architecture and key technologies is presented. Furthermore, existing testbeds and advanced 6G verification platforms are detailed for the first time. In addition, future research directions and open challenges are identified for stimulating the on-going global debate. Finally, lessons learned to date concerning 6G networks are discussed