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2019 | Book

Introduction Read chapter Read first chapter

Hybrid Massive MIMO Precoding in Cloud-RAN

Authors: Tho Le-Ngoc, Ruikai Mai

Publisher: Springer International Publishing

Book Series : Wireless Networks

Part of: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik"

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About this book

This book covers the design and optimization of hybrid RF-baseband precoding for massive multiple-input multiple-output (MIMO)-enabled cloud radio access networks (RANs), where use cases such as millimeter-wave wireless backhauling, fully-loaded cellular networks are of interest. The suitability and practical implementation of the proposed precoding solutions for the Cloud RAN architecture are also discussed.

Novel techniques are examined for RF precoding optimization in combination with nonlinear precoding at baseband, and the superiority of joint RF-baseband design is verified. Moreover, the efficacy of hybrid RF-baseband precoding to combat intercell interference in a multi-cell environment with universal frequency reuse is investigated, which is concluded to be a promising enabler for the dense deployment of base stations.

This book mainly targets researchers and engineers interested in the challenges, optimization, and implementation of massive MIMO precoding in 5G Cloud RAN. Graduate students in electrical engineering and computer science interested in the application of mathematical optimization to model and solve precoding problems in massive MIMO cellular systems will also be interested in this book.

Table of Contents

Frontmatter
Chapter 1. Introduction
Abstract
According to the Cisco visual networking index (Cisco, Cisco visual networking index: Global mobile data traffic forecast update, 2016–2021. Technical report, Feb 2017), mobile data traffic has grown 18-fold over the past 5 years to reach 7.2 exabytes per month at the end of 2016, of which 4G Long-Term Evolution (LTE) traffic accounted for 69%. This trend has largely been driven by the increased use of smart phones and tablets as well as by the emergence of services such as internet of things and machine-to-machine communications. As the mobile connections continue the rapid growth, which is accompanied by the demand of high-definition video streaming, augmented reality, and virtual reality, a rethink of the current architecture of wireless communications systems has become more important than ever.
Tho Le-Ngoc, Ruikai Mai
Chapter 2. Background
Abstract
From a signal processing point of view, the novel aspect of hybrid precoding/combining in comparison with the conventional fully digital precoding/combining lies in the introduction of the precoding/combining stage in the RF domain as a result of driving a large-scale antenna array by a limited number of RF chains. By treating the cascade of the RF stage and multiple-input multiple-output (MIMO) channel as the effective channel, the system model of massive MIMO is analogous to the conventional counterpart, where various solution techniques have been proposed for the single-user and multi-user scenarios. On the other hand, problem formulation and optimization of the RF component depend on the choice of the baseband component in a joint RF-baseband design. Therefore, before we embark on the study of hybrid precoding/combining design, we give a brief review of the related background and recent developments in this chapter, which serve as the basis for our proposed research in the subsequent chapters.
Tho Le-Ngoc, Ruikai Mai
Chapter 3. Hybrid Precoding and Combining for Massive MIMO Wireless Backhauling
Abstract
In this chapter, we explore a joint design of two-timescale hybrid precoding and combining for massive multiple-input multiple-output (MIMO) wireless backhaul communications. With the objective of effective capacity maximization, the statistical channel state information (CSI)-based RF and the instantaneous effective CSI-based baseband solutions are jointly derived for the transmitter and receiver. Previous work such as El Ayach et al. (IEEE Trans Wireless Commun 13(3):1499–1513, 2014), Yu et al. (IEEE J Sel Topics Signal Process 10(3):485–500, 2016), where perfect CSI-based RF and baseband designs were simultaneously obtained as a reconstruction of the optimal counterpart, is no longer applicable. Under the assumption of jointly correlated channels (Weichselberger et al. IEEE Trans Wireless Commun 5(1):90–100, 2006, Tulino et al. IEEE Trans Wireless Commun 5(3):662–671, 2006, Gao et al. IEEE Trans Inf Theory 55(8):3735–3750, 2009), the objective function does not have a closed form. Considering traditional MIMO processing at baseband, we address the RF design with nonuniform- and constant-modulus elements.
Tho Le-Ngoc, Ruikai Mai
Chapter 4. Hybrid Precoding/Combining for Massive MIMO with Hybrid ARQ
Abstract
Because of poor channel conditions, correct reception at a certain target data rate can sometimes become impossible. Therefore, packet retransmission protocols are used in modern wireless communications systems to improve the reliability of data transmission. Specifically, when a one-bit feedback link is available from the receiver to the transmitter, the simple scheme of hybrid automatic repeat request (ARQ) with Chase combining (HARQ-CC) can be employed, where the same packet is retransmitted in the event of decoding failure.
Tho Le-Ngoc, Ruikai Mai
Chapter 5. Nonlinear Hybrid Precoding for Massive MIMO with Fractional Frequency Reuse
Abstract
In this chapter, we shift our focus from the point-to-point massive multiple-input multiple-output (MIMO) as considered in Chaps. 3 and 4 to the massive MIMO broadcast channel. Although low-complexity linear precoding schemes such as zero forcing (ZF) and regularized ZF (RZF) work sufficiently well in the presence of user diversity (Yoo and Goldsmith, IEEE J. Sel. Areas Commun. 24(3):528–541, 2006), they nonetheless tend to suffer severe power loss in a homogeneous multi-user environment, where the users experience similar channel conditions and require an equal-rate performance. This is especially the case when the system is almost fully loaded, i.e., the number of users scheduled is near the maximum number of data streams that can be physically supported (Peel et al., IEEE Trans. Commun. 53(1):195–202, 2005). In Chap. 2, it was mentioned that such a phenomenon can be effectively alleviated by vector perturbation (VP), which avoids transmission along the ill-behaving eigen-channel by introducing additional degrees of freedom in the form of an integer perturbation vector (Hochwald et al., IEEE Trans. Commun. 53(3):537–544, 2005).
Tho Le-Ngoc, Ruikai Mai
Chapter 6. Nonlinear Hybrid Precoding for Massive MIMO with Universal Frequency Reuse
Abstract
In an attempt to mitigate the performance degradation caused by inter-cell interference (ICI) in cellular networks with universal frequency reuse, frequency planning techniques, such as fractional frequency reuse, have been proposed (Huawei, R1-050507: soft frequency reuse scheme for UTRAN LTE, 3GPP TSG RAN WG1 Meeting #41, May 2005)
Tho Le-Ngoc, Ruikai Mai
Chapter 7. Conclusions
Abstract
In the previous chapter, the ideas of centralized and distributed baseband precoding in the hybrid RF-baseband architecture were explored for the purpose of suppressing the inter-cell interference (ICI) and improving the system error performance at the cell edge. In the distributed implementation, it is seen that by partitioning the high-dimensional multiple-input multiple-output (MIMO) channel into multiple near-orthogonal, low-dimensional subspaces as dictated by block diagonalization in the RF domain, cell-wise spatial multiplexing can be carried out at baseband without causing severe ICI. Although this obviates the need of channel state information (CSI) and user data exchange between base stations (BSs), the lack of cell coordination unfortunately prevents balancing intra-cell spatial multiplexing and ICI suppression in a resource efficient manner. On the contrary, by allowing inter-BS collaboration as in the centralized approach to baseband spatial multiplexing, the error performance enjoys a significant enhancement.
Tho Le-Ngoc, Ruikai Mai
Metadata
Title
Hybrid Massive MIMO Precoding in Cloud-RAN
Authors
Tho Le-Ngoc
Ruikai Mai
Copyright Year
2019
Electronic ISBN
978-3-030-02158-0
Print ISBN
978-3-030-02157-3
DOI
https://doi.org/10.1007/978-3-030-02158-0