Joint Design of Fronthauling and Hybrid Beamforming for Downlink C-RAN Systems

Jaein Kim, Seok Hwan Park, Osvaldo Simeone, Inkyu Lee, Shlomo Shamai Shitz

Research output: Contribution to journalArticle

Abstract

Hybrid beamforming is known to be a cost-effective and wide-spread solution for a system with large-scale antenna arrays. This paper studies the optimization of the analog and digital components of the hybrid beamforming solution for remote radio heads (RRHs) in a downlink cloud radio access network architecture. Digital processing is carried out at a baseband processing unit (BBU) in the 'cloud,' and the precoded baseband signals are quantized prior to transmission to the RRHs via finite-capacity fronthaul links. In this system, we consider two different channel state information (CSI) scenarios: 1) ideal CSI at the BBU and 2) imperfect effective CSI. The optimization of digital beamforming and fronthaul quantization strategies at the BBU as well as analog radio-frequency (RF) beamforming at the RRHs is a coupled problem since the effect of the quantization noise at the receiver depends on the precoding matrices. The resulting joint optimization problem is examined with the goal of maximizing the weighted downlink sum-rate and the network energy efficiency. Fronthaul capacity and per-RRH power constraints are enforced along with constant modulus constraint on the RF beamforming matrices. For the case of perfect CSI, a block coordinate descent scheme is proposed based on the weighted minimum-mean-square-error approach by relaxing the constant modulus constraint of the analog beamformer. Also, we present the impact of imperfect CSI on the weighted sum-rate and network energy efficiency performance, and the algorithm is extended by applying the sample average approximation. The numerical results confirm the effectiveness of the proposed scheme and show that the proposed algorithm is robust to estimation errors.

Original languageEnglish
Article number8660693
Pages (from-to)4423-4434
Number of pages12
JournalIEEE Transactions on Communications
Volume67
Issue number6
DOIs
Publication statusPublished - 2019 Jun 1

Fingerprint

Beamforming
Channel state information
Energy efficiency
Processing
Quantization (signal)
Digital signal processing
Network architecture
Antenna arrays
Mean square error
Error analysis
Telecommunication links
Costs

Keywords

  • Cloud-RAN
  • fronthaul compression
  • hybrid beamforming
  • imperfect CSI
  • massive MIMO

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

Cite this

Joint Design of Fronthauling and Hybrid Beamforming for Downlink C-RAN Systems. / Kim, Jaein; Park, Seok Hwan; Simeone, Osvaldo; Lee, Inkyu; Shitz, Shlomo Shamai.

In: IEEE Transactions on Communications, Vol. 67, No. 6, 8660693, 01.06.2019, p. 4423-4434.

Research output: Contribution to journalArticle

Kim, Jaein ; Park, Seok Hwan ; Simeone, Osvaldo ; Lee, Inkyu ; Shitz, Shlomo Shamai. / Joint Design of Fronthauling and Hybrid Beamforming for Downlink C-RAN Systems. In: IEEE Transactions on Communications. 2019 ; Vol. 67, No. 6. pp. 4423-4434.
@article{43920f4c5e9d4eecae3baf4d6b01dfca,
title = "Joint Design of Fronthauling and Hybrid Beamforming for Downlink C-RAN Systems",
abstract = "Hybrid beamforming is known to be a cost-effective and wide-spread solution for a system with large-scale antenna arrays. This paper studies the optimization of the analog and digital components of the hybrid beamforming solution for remote radio heads (RRHs) in a downlink cloud radio access network architecture. Digital processing is carried out at a baseband processing unit (BBU) in the 'cloud,' and the precoded baseband signals are quantized prior to transmission to the RRHs via finite-capacity fronthaul links. In this system, we consider two different channel state information (CSI) scenarios: 1) ideal CSI at the BBU and 2) imperfect effective CSI. The optimization of digital beamforming and fronthaul quantization strategies at the BBU as well as analog radio-frequency (RF) beamforming at the RRHs is a coupled problem since the effect of the quantization noise at the receiver depends on the precoding matrices. The resulting joint optimization problem is examined with the goal of maximizing the weighted downlink sum-rate and the network energy efficiency. Fronthaul capacity and per-RRH power constraints are enforced along with constant modulus constraint on the RF beamforming matrices. For the case of perfect CSI, a block coordinate descent scheme is proposed based on the weighted minimum-mean-square-error approach by relaxing the constant modulus constraint of the analog beamformer. Also, we present the impact of imperfect CSI on the weighted sum-rate and network energy efficiency performance, and the algorithm is extended by applying the sample average approximation. The numerical results confirm the effectiveness of the proposed scheme and show that the proposed algorithm is robust to estimation errors.",
keywords = "Cloud-RAN, fronthaul compression, hybrid beamforming, imperfect CSI, massive MIMO",
author = "Jaein Kim and Park, {Seok Hwan} and Osvaldo Simeone and Inkyu Lee and Shitz, {Shlomo Shamai}",
year = "2019",
month = "6",
day = "1",
doi = "10.1109/TCOMM.2019.2903142",
language = "English",
volume = "67",
pages = "4423--4434",
journal = "IEEE Transactions on Communications",
issn = "0090-6778",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "6",

}

TY - JOUR

T1 - Joint Design of Fronthauling and Hybrid Beamforming for Downlink C-RAN Systems

AU - Kim, Jaein

AU - Park, Seok Hwan

AU - Simeone, Osvaldo

AU - Lee, Inkyu

AU - Shitz, Shlomo Shamai

PY - 2019/6/1

Y1 - 2019/6/1

N2 - Hybrid beamforming is known to be a cost-effective and wide-spread solution for a system with large-scale antenna arrays. This paper studies the optimization of the analog and digital components of the hybrid beamforming solution for remote radio heads (RRHs) in a downlink cloud radio access network architecture. Digital processing is carried out at a baseband processing unit (BBU) in the 'cloud,' and the precoded baseband signals are quantized prior to transmission to the RRHs via finite-capacity fronthaul links. In this system, we consider two different channel state information (CSI) scenarios: 1) ideal CSI at the BBU and 2) imperfect effective CSI. The optimization of digital beamforming and fronthaul quantization strategies at the BBU as well as analog radio-frequency (RF) beamforming at the RRHs is a coupled problem since the effect of the quantization noise at the receiver depends on the precoding matrices. The resulting joint optimization problem is examined with the goal of maximizing the weighted downlink sum-rate and the network energy efficiency. Fronthaul capacity and per-RRH power constraints are enforced along with constant modulus constraint on the RF beamforming matrices. For the case of perfect CSI, a block coordinate descent scheme is proposed based on the weighted minimum-mean-square-error approach by relaxing the constant modulus constraint of the analog beamformer. Also, we present the impact of imperfect CSI on the weighted sum-rate and network energy efficiency performance, and the algorithm is extended by applying the sample average approximation. The numerical results confirm the effectiveness of the proposed scheme and show that the proposed algorithm is robust to estimation errors.

AB - Hybrid beamforming is known to be a cost-effective and wide-spread solution for a system with large-scale antenna arrays. This paper studies the optimization of the analog and digital components of the hybrid beamforming solution for remote radio heads (RRHs) in a downlink cloud radio access network architecture. Digital processing is carried out at a baseband processing unit (BBU) in the 'cloud,' and the precoded baseband signals are quantized prior to transmission to the RRHs via finite-capacity fronthaul links. In this system, we consider two different channel state information (CSI) scenarios: 1) ideal CSI at the BBU and 2) imperfect effective CSI. The optimization of digital beamforming and fronthaul quantization strategies at the BBU as well as analog radio-frequency (RF) beamforming at the RRHs is a coupled problem since the effect of the quantization noise at the receiver depends on the precoding matrices. The resulting joint optimization problem is examined with the goal of maximizing the weighted downlink sum-rate and the network energy efficiency. Fronthaul capacity and per-RRH power constraints are enforced along with constant modulus constraint on the RF beamforming matrices. For the case of perfect CSI, a block coordinate descent scheme is proposed based on the weighted minimum-mean-square-error approach by relaxing the constant modulus constraint of the analog beamformer. Also, we present the impact of imperfect CSI on the weighted sum-rate and network energy efficiency performance, and the algorithm is extended by applying the sample average approximation. The numerical results confirm the effectiveness of the proposed scheme and show that the proposed algorithm is robust to estimation errors.

KW - Cloud-RAN

KW - fronthaul compression

KW - hybrid beamforming

KW - imperfect CSI

KW - massive MIMO

UR - http://www.scopus.com/inward/record.url?scp=85067581649&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85067581649&partnerID=8YFLogxK

U2 - 10.1109/TCOMM.2019.2903142

DO - 10.1109/TCOMM.2019.2903142

M3 - Article

VL - 67

SP - 4423

EP - 4434

JO - IEEE Transactions on Communications

JF - IEEE Transactions on Communications

SN - 0090-6778

IS - 6

M1 - 8660693

ER -