Uplink Channel Estimation and Data Transmission in Millimeter-Wave CRAN With Lens Antenna Arrays

Stephen, Reuben George; Zhang, Rui

doi:10.1109/tcomm.2018.2859996

Cited by 10 publications

(13 citation statements)

References 31 publications

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“…To achieve this, an optimized framework for the integration should be designed in such a way that the performance of legacy WiFi users should not be compromised [38]. On the other hand, mmWave band is also proposed as an important ingredient for 5G and beyond wireless networks [39], [40]. It is also suggested that mmWave is more appropriate for the backhaul link part.…”

Section: A Resource Allocation Elementsmentioning

confidence: 99%

“…Also, CRAN can enable the network densification in a cost-efficient manner for enhancing the spectral efficiency and energy efficiency of the next-generation wireless networks. By integrating CRAN architecture with the mmWave communications, both the objectives of huge bandwidth and network densification can be achieved, thus leading to the concept of mmWave CRAN [40]. Furthermore, in contrast to the communications in low-frequency bands, mmWave communications is more susceptible to blockages including shadowing and building walls and is also affected by atmospheric conditions.…”

Section: B Millimeter Wave (Mmwave) Cranmentioning

confidence: 99%

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A comprehensive survey on resource allocation for CRAN in 5G and beyond networks

Ejaz

Sharma

Saadat

et al. 2020

Journal of Network and Computer Applications

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The diverse service requirements coming with the advent of sophisticated applications as well as a large number of connected devices demand for revolutionary changes in the traditional distributed radio access network (RAN). To this end, Cloud-RAN (CRAN) is considered as an important paradigm to enhance the performance of the upcoming fifth generation (5G) and beyond wireless networks in terms of capacity, latency, and connectivity to a large number of devices. Out of several potential enablers, efficient resource allocation can mitigate various challenges related to user assignment, power allocation, and spectrum management in a CRAN, and is the focus of this paper. Herein, we provide a comprehensive review of resource allocation schemes in a CRAN along with a detailed optimization taxonomy on various aspects of resource allocation. More importantly, we identity and discuss the key elements for efficient resource allocation and management in CRAN, namely: user assignment, remote radio heads (RRH) selection, throughput maximization, spectrum management, network utility, and power allocation. Furthermore, we present emerging use-cases including heterogeneous CRAN, millimeter-wave CRAN, virtualized CRAN, Non-Orthogonal Multiple Access (NoMA)-based CRAN and fullduplex enabled CRAN to illustrate how their performance can be enhanced by adopting CRAN technology. We then classify and discuss objectives and constraints involved in CRAN-based 5G and beyond networks. Moreover, a detailed taxonomy of optimization methods and solution approaches with different objectives is presented and discussed. Finally, we conclude the paper with several open research issues and future directions.

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Section: A Resource Allocation Elementsmentioning

confidence: 99%

Section: B Millimeter Wave (Mmwave) Cranmentioning

confidence: 99%

A comprehensive survey on resource allocation for CRAN in 5G and beyond networks

Ejaz

Sharma

Saadat

et al. 2020

Journal of Network and Computer Applications

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“…We study the localization (position and velocity estimation of the moving UE) in mmWave CRAN with N multi-antenna RRHs [5], as shown in Fig. 1, where each RRH is equipped with J = 3 3-D lens antenna arrays, and each lens antenna array covers 120 • and has M antenna elements.…”

Section: System Modelmentioning

confidence: 99%

“…To compensate for the severe penetration loss and the increased path-loss, large antenna arrays and highly directional transmission should be combined [4], which facilitates the acquisition of angle of arrival (AoA) and angle of departure (AoD). Moreover, cloud radio access network (CRAN) can also enhance mmWave communications by improving the network coverage [5]. Therefore, mmWave CRAN can offer accurate localization, in return, the location information can improve the scalability, latency, and robustness of the future networks [6].…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we focus on the joint position and velocity estimation problem of the moving UE. We adopt mmWave CRAN architecture [5], and leverage advanced 3-D lens antenna arrays at the RRHs. Lens can operate at very short pulse length and receive signals with different AoAs simultaneously without beam scanning [4], which can accelerate the uplink localization process.…”

Section: Introductionmentioning

confidence: 99%

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3-D Position and Velocity Estimation in 5G mmWave CRAN with Lens Antenna Arrays

Yang

Jin

Han

et al. 2019

2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall)

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5G millimeter-wave (mmWave) cloud radio access network (CRAN) provides new opportunities for accurate multilateration: large bandwidth, large antenna arrays, and increased densities of base stations allow for unparalleled delay and angle resolution. However, combining localization into communications and designing joint position and velocity estimation algorithms are challenging. This paper considers the joint estimation in three-dimensional (3-D) lens antenna array based mmWave CRAN architecture. We embed multilateration into communications and explain its benefits to the initial access and beam training stages. We propose a closed-form solution for the joint estimation problem by forming the pseudo-linear matrix representation and designing the weighted least squares estimator with hybrid measurements. The proposed method is proven asymptotically unbiased and confirmed by simulations to achieve the Cramer-Rao lower bound and attain the sub-decimeter level accuracy.

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Performance analysis of relay-aided millimeter-wave communications with optimal and suboptimal combining at destination

Hashemi

Haghighat

Eslami

2020

Physical Communication

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Uplink Channel Estimation and Data Transmission in Millimeter-Wave CRAN With Lens Antenna Arrays

Cited by 10 publications

References 31 publications

A comprehensive survey on resource allocation for CRAN in 5G and beyond networks

A comprehensive survey on resource allocation for CRAN in 5G and beyond networks

3-D Position and Velocity Estimation in 5G mmWave CRAN with Lens Antenna Arrays

Performance analysis of relay-aided millimeter-wave communications with optimal and suboptimal combining at destination

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