A Robust and Resilient Load Balancing Framework for SoftRAN-Based HetNets With Hybrid Energy Supplies

Awad, Mohamad Khattar; Behiry, Ali A. M. R.; Alrashed, Ebrahim

doi:10.1109/tnsm.2020.2991339

Cited by 6 publications

(3 citation statements)

References 30 publications

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“…In cellular networks, load balancing refers to the distribution of loads among cells in proportion to their resources [ 13 ]. For instance, the lowest traffic delivery latency or the highest green energy usage in networks with hybrid energy BSs are taken into account for load balancing functions in some studies [ 14 , 17 , 18 ]. In the case of load imbalance in multi-tier networks, the deployment of small-scale BSs is not beneficial, and the network performance is significantly reduced.…”

Section: Background and Related Workmentioning

confidence: 99%

Joint downlink user association and interference avoidance with a load balancing approach in backhaul-constrained HetNets

Chinipardaz,

Amraee,

Sarlak

2024

PLoS ONE

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In heterogeneous networks (HetNets), different lower-power base stations are added in a typically unplanned manner to the well-planned macro-only network, bringing new challenges to the network functions. Small cells experience limited backhaul capacity since cost-effective backhaul is not easily accessible to them. This study focuses on the issue of user association in backhaul-constrained HetNets. It shows that it is necessary to associate users with cells using a load balancing approach in order to fully leverage the addition of small cells. The cell association needs to be done jointly with an interference management technique that protects offloaded users and those prone to harmful interference. After modeling the system and describing the interference model, the problem of cell and subband allocation is formulated. We first examine the problem in a time-sharing mode and present a centralized heuristic solution to the cell and subband allocation problem. This is accomplished by solving the convex problem using the gradual removal method. The importance of providing distributed algorithms for HetNets leads to the development of a new algorithm through the application of the dual decomposition method to a reformulated problem and the use of an admission control mechanism. In the achieved algorithm, all computations are performed locally, with each user and base station relying only on local information. This algorithm obtains near-optimal answers, as confirmed by the simulation results. Compared with conventional cell allocation methods, our distributed algorithm prevents intensive interference for all users and achieves better load balance between network tiers, resulting in improved network utility.

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Section: Background and Related Workmentioning

confidence: 99%

Joint downlink user association and interference avoidance with a load balancing approach in backhaul-constrained HetNets

Chinipardaz,

Amraee,

Sarlak

2024

PLoS ONE

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“…Many channel estimation strategies proposed in the literature [11]- [16]. The works in [17]- [25] investigated the radio resource management assuming channel state information is perfectly known between the transmitter and all the users. Nevertheless, the perfect CSI assumption at all user terminals is unrealistic in practical communications scenarios due to time varying wireless channel conditions, channel estimation errors and quantization errors.…”

Section: A Related Workmentioning

confidence: 99%

Robust Channel Estimation in Multiuser Downlink 5G Systems Under Channel Uncertainties

Pourkabirian

Anisi

2022

IEEE Trans. on Mobile Comput.

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In wireless communication, the performance of the network highly relies on the accuracy of channel state information (CSI). On the other hand, the channel statistics are usually unknown, and the measurement information is lost due to the fading phenomenon. Therefore, we propose a channel estimation approach for downlink communication under channel uncertainty. We apply the Tobit Kalman filter (TKF) method to estimate the hidden state vectors of wireless channels. To minimize the maximum estimation error, a robust minimax minimum estimation error (MSE) estimation approach is developed while the QoS requirements of wireless users is taken into account. We then formulate the minimax problem as a non-cooperative game to find an optimal filter and adjust the best behavior for the worst-case channel uncertainty. We also investigate a scenario in which the actual operating point is not exactly known under model uncertainty. Finally, we investigate the existence and characterization of a saddle point as the solution of the game. Theoretical analysis verifies that our work is robust against the uncertainty of the channel statistics and able to track the true values of the channel states. Additionally, simulation results demonstrate the superiority of the model in terms of MSE value over related techniques.

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“…A distributed user connection scheme for HetNets is proposed in [66] for optimizing the trade-off between traffic latency and grid consumption. The study of trade-off between renewable energy utilization and QoS provisioning in the form of traffic latency for hybrid powered heterogeneous cellular networks is carried out in [67]. Authors studied catch enabled load balancing solutions for small cell networks adopting interference management technique for the future generation mobile communication systems [68].…”

Section: Related Workmentioning

confidence: 99%

Energy Efficient Throughput Aware Traffic Load Balancing in Green Cellular Networks

et al. 2021

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With the augmentation of affordable multimedia wireless gadgets, the ubiquitous availability of internet access and the rapid pace of mobile traffic motivate research towards fifth generation (5G) communications to realize energy-efficient cloud radio access networks (C-RAN) with guaranteed quality of experience. Exploiting green energy harvesting for powering the C-RAN substantially alleviates the energy procurement from the utility grid, carbon footprint and operational expenses. In this paper, we propose a new dynamic point selection coordinated multipoint (DPS CoMP) based load balancing paradigm emphasizing on achievable throughput and energy efficiency by reducing utility grid consumption from a network level perspective. This paper investigate the radio efficiency, energy efficiency (EE) and average on-grid energy saving addressing the key challenges of tempo-spatial dynamics of traffic intensity and renewable energy (RE) generation under a wide range of networks setup. Endeavoring load balancing technique strives a balance in network utilities such as green energy utilization and user association based on BS coordination in a cluster. Provision of cell sleep approach is contemplated for energy saving by turning off lightly base stations (BSs) during low traffic arrivals. The proposed CoMP based load balancing algorithm proficiently manages resource block allocation to the new users and elevated the energy efficiency over the conventional location and traffic centric mechanisms. Extensive system-level simulations manifest that the suggested framework enable adjustable trade-off between radio efficiency and EE, and saves 22% on-grid power consumption and increases EE index by 32%. Afterwards, an exhaustive comparison of the proposed method with the existing schemes is pledged for further validation highlighting sustainable 5G wireless systems.INDEX TERMS Energy efficiency, coordinated multipoint, hybrid power supply, centralized RAN, load balancing, cell zooming, green communication.

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A Robust and Resilient Load Balancing Framework for SoftRAN-Based HetNets With Hybrid Energy Supplies

Cited by 6 publications

References 30 publications

Joint downlink user association and interference avoidance with a load balancing approach in backhaul-constrained HetNets

Joint downlink user association and interference avoidance with a load balancing approach in backhaul-constrained HetNets

Robust Channel Estimation in Multiuser Downlink 5G Systems Under Channel Uncertainties

Energy Efficient Throughput Aware Traffic Load Balancing in Green Cellular Networks

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