Distributed Learning for Energy-Efficient Resource Management in Self-Organizing Heterogeneous Networks

Arani, Atefeh Hajijamali; Mehbodniya, Abolfazl; Omidi, Mohammad Javad; Adachi, Fumiyuki; Saad, Walid; Güvenç, İsmail

doi:10.1109/tvt.2017.2696974

Cited by 27 publications

(13 citation statements)

References 49 publications

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“…The problem was formulated as a multiobjective optimization by aiming to maximize the EE of BSs under the constraints of the BS power and minimum UE data rate. The optimization problem GUIA has higher complexity with a high convergence time [86] was solved by applying the iterative method and Kuhn-Munkres algorithm. This work introduced the concept of secrecy EE, which is defined as the ratio of the transmission rate over a secured channel and the BS power consumption.…”

Section: ) Joint User Associationmentioning

confidence: 99%

Survey of Radio Resource Management in 5G Heterogeneous Networks

et al. 2020

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Radio resource management (RRM) for future fifth-generation (5G) heterogeneous networks (HetNets) has emerged as a critical area due to the increased density of small-cell networks and radio access technologies. Recent research has mostly concentrated on resource management, including spectrum utilization and interference mitigation, but the complexities of these resources have been given little attention. This paper provides an overview of the issues arising from future 5G systems and highlights their importance. The different approaches used in recently published surveys categorizing RRM schemes are discussed, and the survey method is presented. We report on a survey of HetNet RRM schemes that have been studied recently, with a focus on the joint optimization of radio resource allocation with other mechanisms. These RRM schemes were subcategorized according to their optimization metrics and qualitatively analyzed and compared. An analysis of the complexity of RRM schemes in terms of implementation and computation is presented. Several potential scopes of research for future RRM in 5G HetNets are also identified.

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Section: ) Joint User Associationmentioning

confidence: 99%

Survey of Radio Resource Management in 5G Heterogeneous Networks

et al. 2020

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“…The (6) confirm the QoS for each FCUs, where, 4 denotes the interference of total power at MCU receiver, and the main problem is ℎ , = 1 which is mixed integer and "non-convex programming" difficulty, , signifies the feedback of channel gains that provided through MCU to FCU. In recent development, majority of the researchers has aimed towards power allocation strategy in the HetNets [27] which focus on improvement power with perfect CSI [28]. However, in particle scenario, the quantization errors presence reasons the channel uncertainty which is harmful for MCUs, in order to overcome this problem, we should consider some improve technique so that can deal with these type of uncertainties.…”

Section: Robustified Power Controllermentioning

confidence: 99%

“…)] + (27) Where, the iteration number is given by , the 1 , 2 and 3 shows the small step sizes, whenever these step size are appropriately small the "Lagrange multipliers" can congregate to equilibrium points [30]. In the implementation process, initially maximum iteration count is given by , and initialization of = 0, > 0 > 0; the Lagrange multipliers are initializes as 0 < (0), 0 < (0) and 0 < (0), though the threshold value of outage probability is ∈ [0,1], ∈ [0,1].…”

Section: Robust Resource Allocation Approachmentioning

confidence: 99%

Heterogeneous network optimization using robust power-and-resource based algorithm

Patil¹,

Bhavikatti²

2019

IJECE

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<p>In order to meet the increasing mobile data-traffic, spatial densification of network with several low-power nodes, the high-power macro BS and HetNet are the major key enabling solution. However, the HetNet is unplanned in nature, causes irregularities and interferences that without any user association rules. The appropriate deployment of the femto-cell in HetNet can provide effective traffic offloading, where the alleviate mobbing in the macro-cells can decrease the power consumption therefore it optimizes the user experience. Moreover, the protection is also important for the macro and femto cell users in a network through maintaining the min-max level of interferences. In this paper, we proposed RPRA that comprises two robust approach such as robust power-controller and the robust channel-allocation approach, which can improve the spectral efficiency and user experiences at lower network coverage areas via eliminating the week coverage zones. Also provide high user rate connection by effective interference in an efficient spectrum, lowering in transmission power and cost-effectiveness via less time delay. To show the effectiveness of our proposed model we have compared with several existing techniques and we got significant improvement in throughput, also reduction in time delay and transmission power.</p>

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“…Where, 4 shows the total power interference at MCU receiver side, the major difficulty is ℎ , = 1 is mixed integer and non-convex programming difficulty and , shows the channel gains feedback that provided by MCU to FCU. In current development, mostly of the researchers has focused on power allocation strategy in HetNets [34] that focus on enhancement power with considering perfect CSI [35]. In particle, the present of quantization errors and estimation error causes the channel uncertainty that is harmful for MCUs and, in order to decrease that, we should consider some advancement technique, which can deal with these uncertainties.…”

Section: Robust User Quality Based Power Controllermentioning

confidence: 99%

Channel Capacity Maximization using NQHN Approach at Heterogeneous Network

Patil¹,

Bhavikatti²

2019

IJECE

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<p>In present scenario, the high speed data transmission services has pushed limits for wireless communication network capacity, at same time multimedia transmission in real-time needs provision of QoS, therefore the network capacity and small cell coverage has comes with lots of challenges. Improving the channel capacity and coverage area within the available bandwidth is necessary to provide better QoS to users, and improved channel capacity for the FCUs and MCUs in network. In this paper, we are proposing an NQHN approach that incorporate with efficient power allocation, improving the channel capacity by optimized traffic scheduling process in a small cell HetNets scenario. This work efficiently handle the interference with maintaining the user QoS and the implemented power controller uses HeNB power as per the real time based approach for macro-cell and femto-cell. Moreover, we consider the real traffic scenario to check the performance of our proposed approach with respect to existing algorithm</p>

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Distributed Learning for Energy-Efficient Resource Management in Self-Organizing Heterogeneous Networks

Cited by 27 publications

References 49 publications

Survey of Radio Resource Management in 5G Heterogeneous Networks

Survey of Radio Resource Management in 5G Heterogeneous Networks

Heterogeneous network optimization using robust power-and-resource based algorithm

Channel Capacity Maximization using NQHN Approach at Heterogeneous Network

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