Joint Scheduling and Beamforming Coordination in Cloud Radio Access Networks With QoS Guarantees

Huang, Xiaoyan; Xue, Guoliang; Yu, Ruozhou; Leng, Supeng

doi:10.1109/tvt.2015.2464278

Cited by 71 publications

(55 citation statements)

References 33 publications

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“…The QCQP problem can then be easily solved by some classic methods such as CVX. In [100], [103], the author transformed the nonconvex primal problem into a convex problem and then used the lagrange dual method to transform the convex problem into a more tractable form. Centralized methods to optimize resource allocation in C-RANs are summarized in Table VIII.…”

Section: ) Classic Non-convex Optimizationmentioning

confidence: 99%

Recent Advances in Cloud Radio Access Networks: System Architectures, Key Techniques, and Open Issues

Peng

Sun

et al. 2016

IEEE Commun. Surv. Tutorials

361

205

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Abstract-As a promising paradigm to reduce both capital and operating expenditures, the cloud radio access network (C-RAN) has been shown to provide high spectral efficiency and energy efficiency. Motivated by its significant theoretical performance gains and potential advantages, C-RANs have been advocated by both the industry and research community. This paper comprehensively surveys the recent advances of C-RANs, including system architectures, key techniques, and open issues. The system architectures with different functional splits and the corresponding characteristics are comprehensively summarized and discussed. The state-of-the-art key techniques in C-RANs are classified as: the fronthaul compression, large-scale collaborative processing, and channel estimation in the physical layer; and the radio resource allocation and optimization in the upper layer. Additionally, given the extensiveness of the research area, open issues and challenges are presented to spur future investigations, in which the involvement of edge cache, big data mining, socialaware device-to-device, cognitive radio, software defined network, and physical layer security for C-RANs are discussed, and the progress of testbed development and trial test are introduced as well.

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Section: ) Classic Non-convex Optimizationmentioning

confidence: 99%

Recent Advances in Cloud Radio Access Networks: System Architectures, Key Techniques, and Open Issues

Peng

Sun

et al. 2016

IEEE Commun. Surv. Tutorials

361

205

View full text Add to dashboard Cite

show abstract

“…The authors in [10] study the joint decompression and decoding for an uplink CRAN and propose an iterative algorithm to maximize the achievable uplink sum rate. In [11], the system utility is first defined and then the authors focus on joint optimization of device grouping and transmit beamforming to maximize the system utility subject to the devices' QoS and the RRHs' power constraints. To avoid the high computational complexity, a low-complexity two-stage iterative algorithm is proposed.…”

Section: A Related Workmentioning

confidence: 99%

Green Communication for NOMA-Based CRAN

Hao

Chu

Zhou

et al. 2019

IEEE Internet Things J.

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Abstract-The wireless devices will rapidly growth with the application of the Internet of Thing (IoT), which results in the huge power consumption. To realize the green communication, in this paper, we study the energy efficiency (EE) problem in a non-orthogonal multiple access (NOMA)-based CRAN, where microwave and millimeter wave (mmWave) are applied in fronthaul and access links, respectively. Based on this, we formulate the power optimization problem to maximize the EE of the system subject to the fronthaul capacity and transmit power constraints. Due to the formulated problem is nonconvex, we first transform the fractional objective function into the subtractive form. After that, an algorithm containing outer and inner loops is proposed to deal with this non-convex problem. In particular, in the outer loop, the 1 -norm technique is adopted to transform the nonconvex fronthaul capacity constraint into the convex one; while in the inner loop, the weighted minimum mean square error (WMMSE) approach is applied to solve the formulated problem. Simulation results demonstrate that the proposed NOMA scheme can obtain higher EE as well as throughput in comparison with the conventional orthogonal multiple access (OMA) scheme.

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“…The resource management problem including RRA and PA for mobile user equipments (UEs) in H-CRAN has been studied in many research works. [4][5][6][7][8][9][10][11][12][13][14][15][16][17] In the work of Peng et al, 4 joint resource assignment and PA algorithm is suggested for H-CRAN to maximize the energy efficiency through enhancing the traditional soft fractional frequency reuse. The problem is designed as a nonconvex objective function, and then, it is reformulated as an equivalent convex feasibility and resolved using Lagrange dual decomposition technique.…”

Section: Related Workmentioning

confidence: 99%

“…Zheng et al 20 have studied the power control problem for interference management in SC networks, which is formulated to maximize the sum rate of all the SCs while maintaining the quality of service (QoS) of macro cell users. The resource allocation problem in the multicell orthogonal frequency-division multiple access networks, which consists of user scheduling, and PA has been tackled in the work of Zheng et al 21 All of the aforementioned research works [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21] have not been deemed the fronthaul capacity constraints and the intra-tier interference except the works of Zhan and Niyato, 13 Sun et al, 15 and Zhang et al, 19 which consider the latter constraint only. Actually, optical fiber is proposed as the ideal solution to provide high capacity fronthaul connections; however, it cannot be practically utilized in ultra-dense SCs' deployment due to its high cost.…”

Section: Related Workmentioning

confidence: 99%

“…Furthermore, there are many research studies on RRA and PA in HCN and CRAN that have been proposed and can be exploited as references in H‐CRAN. A power control scheme for multiple‐input–multiple‐output–based CRAN is suggested in the work of Huang et al to maximize the energy efficiency. The scheme is dependent on two algorithms: the first one is used to group the RRHs to a number of virtual BSs and decide their group of users, whereas the second algorithm performs the coordination among virtual BSs through the transmission beamforming.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Joint radio resource and power allocation using Nash bargaining game for H‐CRAN with nonideal fronthaul links

Esmat

Elmesalawy

Abdelhakam

2018

Trans Emerging Tel Tech

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Heterogeneous cloud radio access network (H‐CRAN) is introduced as a novel network architecture that takes the full rewards of both heterogeneous cellular network (HCNs) and cloud radio access network (CRAN). In H‐CRAN architecture, the remote radio heads of small cells (SCs) are overlaid within the coverage of macro cell and linked to the baseband unit pool through nonideal fronthaul connections. To improve the spectral efficiency of this network, the SCs are developed to reuse the same resources used by the macro cell. However, this will introduce inter‐tier interference between macro cell and SCs and intra‐tier interference among SCs that need to be efficiently managed. In this paper, the joint problem of radio resource and power allocation in H‐CRAN is formulated using cooperative Nash bargaining game. This optimization problem is designed to maximize the total throughput of SCs, while considering the fairness between user equipments (UEs) in each SC, interference protection requirements for macro UEs, outage probability requirements, and the capacity limitation of nonideal fronthaul connections. Then, by using Lagrangian dual decomposition, the near‐optimal bargaining allocation strategy for radio resources and power of each SC UE is determined. Simulation results illustrate that the performance of the suggested algorithm outperforms the other comparable algorithm in terms of the SCs' achieved throughput and fairness. Moreover, the effect of nonideal fronthaul capacity constraint and the interference protection limit of macro UEs on the performance of the suggested scheme are examined.

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Joint Scheduling and Beamforming Coordination in Cloud Radio Access Networks With QoS Guarantees

Cited by 71 publications

References 33 publications

Recent Advances in Cloud Radio Access Networks: System Architectures, Key Techniques, and Open Issues

Recent Advances in Cloud Radio Access Networks: System Architectures, Key Techniques, and Open Issues

Green Communication for NOMA-Based CRAN

Joint radio resource and power allocation using Nash bargaining game for H‐CRAN with nonideal fronthaul links

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