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Signal Processing for 5G: Algorithms and Implementations
book

Signal Processing for 5G: Algorithms and Implementations

by Fa-Long Luo, Charlie Zhang
October 2016
Intermediate to advanced
610 pages
21h 37m
English
Wiley-IEEE Press
Content preview from Signal Processing for 5G: Algorithms and Implementations

Chapter 18Cloud Radio Access Networks: Uplink Channel Estimation and Downlink Precoding

Osvaldo Simeone, Jinkyu Kang, Joonkhyuk Kang and Shlomo Shamai (Shitz)

  1. 18.1 Introduction
  2. 18.2 Technology Background
    1. 18.2.1 Signal Processing Challenges in C-RAN
    2. 18.2.2 Chapter Overview
  3. 18.3 Uplink: Where to Perform Channel Estimation?
    1. 18.3.1 System Model
    2. 18.3.2 Conventional Approach
    3. 18.3.3 Channel Estimation at the RRHs
    4. 18.3.4 Numerical Results
  4. 18.4 Downlink: Where to Perform Channel Encoding and Precoding?
    1. 18.4.1 System Model
    2. 18.4.2 Conventional Approach
    3. 18.4.3 Channel Encoding and Precoding at the RRHs
    4. 18.4.4 Numerical Results
  5. 18.5 Concluding Remarks
  6. References

18.1 Introduction

The gains afforded by cloud radio access network (C-RAN) in terms of savings in capital and operating expenses, flexibility, interference management and network densification rely on the presence of high-capacity low-latency fronthaul connectivity between remote radio heads (RRHs) and a baseband unit (BBU). In light of the non-uniform and limited availability of fiber-optic cables, the bandwidth constraints on the fronthaul network call, on the one hand, for the development of advanced baseband compression strategies and, on the other hand, for a closer investigation of the optimal functional split between RRHs and BBU. In this chapter, after a brief introduction to the signal-processing challenges in C-RAN, this optimal functional split is studied at the physical (PHY) layer as it pertains to two key baseband ...

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Publisher Resources

ISBN: 9781119116462Purchase book