Dynamic load balancing and throughput optimization in 3GPP LTE networks

Wang, Hao; Ding, Lianghui; Wu, Peng; Pan, Zhiwen; Liu, Nan; You, Xiaohu

doi:10.1145/1815396.1815611

Cited by 45 publications

(45 citation statements)

References 6 publications

(7 reference statements)

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“…The term load balancing describes any mechanism that transfers some traffic from the cells with heavy load to the neighbors with less load in order to balance the load in the entire network, while improving the network performance, e.g. energy consumption [79,80]. Inappropriate BS-UE association can lead to large disparity in cells' load, that is, some cells, e.g., macro BSs, may be overloaded, whereas some neighboring low-power BSs, e.g., micro or pico BSs, are underloaded.…”

Section: Energy-efficient Scheduling In Ofdma Systemsmentioning

confidence: 99%

“…To deal with this problem, load balancing can make the use of the radio resource more efficient across the network. From the analysis in some research works [79], energy consumption can be reduced if the underloaded cells offload some traffic from neighboring overloaded cells, e.g., by applying LTE cell range expansion [80]. Several algorithmic solutions have been proposed to improve the performance of load balancing and energy savings [72,73].…”

Section: Energy-efficient Scheduling In Ofdma Systemsmentioning

confidence: 99%

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From Orthogonal to Non-orthogonal Multiple Access: Energy- and Spectrum-Efficient Resource Allocation

Lei¹

2016

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The rapid pace of innovations in information and communication technology (ICT) industry over the past decade has greatly improved people's mobile communication experience. This, in turn, has escalated exponential growth in the number of connected mobile devices and data traffic volume in wireless networks. Researchers and network service providers have faced many challenges in providing seamless, ubiquitous, reliable, and high-speed data service to mobile users. Mathematical optimization, as a powerful tool, plays an important role in addressing such challenging issues.This dissertation addresses several radio resource allocation problems in 4G and 5G mobile communication systems, in order to improve network performance in terms of throughput, energy, or fairness. Mathematical optimization is applied as the main approach to analyze and solve the problems. Theoretical analysis and algorithmic solutions are derived. Numerical results are obtained to validate our theoretical findings and demonstrate the algorithms' ability of attaining optimal or near-optimal solutions.Five research papers are included in the dissertation. In Paper I, we study a set of optimization problems of consecutive-channel allocation in single carrier-frequency division multiple access (SC-FDMA) systems. We provide a unified algorithmic framework to optimize the channel allocation and improve system performance. The next three papers are devoted to studying energy-saving problems in orthogonal frequency division multiple access (OFDMA) systems. In Paper II, we investigate a problem of jointly minimizing energy consumption at both transmitter and receiver sides. An energy-efficient scheduling algorithm is developed to provide optimality bounds and near-optimal solutions. Next in Paper III, we derive fundamental properties for energy minimization in load-coupled OFDMA networks. Our analytical results iii suggest that the maximal use of time-frequency resources can lead to the lowest network energy consumption. An iterative power adjustment algorithm is developed to obtain the optimal power solution with guaranteed convergence. In Paper IV, we study an energy minimization problem from the perspective of scheduling activation and deactivation of base station transmissions. We provide mathematical formulations and theoretical insights. For problem solution, a column generation approach, as well as a bounding scheme are developed. Finally, towards to 5G communication systems, joint power and channel allocation in nonorthogonal multiple access (NOMA) is investigated in Paper V in which an algorithmic solution is proposed to improve system throughput and fairness. iv Populärvetenskaplig SammanfattningDen snabba utvecklingen inom informations-och kommunikations teknikområdet har avsevärt förbättrat människors upplevelser av mobilkommunikation. Detta i sin tur har lett till en exponentiellökning av antalet anslutna mobila enheter och mängden datatrafik i mobila nätverk. Forskare och nätverksoperatörer har stått inför många utmaningar för att ...

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Section: Energy-efficient Scheduling In Ofdma Systemsmentioning

confidence: 99%

Section: Energy-efficient Scheduling In Ofdma Systemsmentioning

confidence: 99%

From Orthogonal to Non-orthogonal Multiple Access: Energy- and Spectrum-Efficient Resource Allocation

Lei¹

2016

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“…The approach is based on a network formulation of heterogeneous services with different quality of service requirements. In [5], Wang et al used a network utility-based load-balancing framework to develop an algorithm called Heaviest-First Load Balancing (HFLB). Another approach postulated in [6] involves the integration of another self-optimization functionhandover parameter optimization to offset handover problems associated with load balancing.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Neuro-Fuzzy Inference System for Dynamic Load Balancing in 3GPP LTE

Atayero¹,

Luka²

2012

IJARAI

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Abstract-ANFIS is applicable in modeling of key parameters when investigating the performance and functionality of wireless networks. The need to save both capital and operational expenditure in the management of wireless networks cannot be over-emphasized. Automation of network operations is a veritable means of achieving the necessary reduction in CAPEX and OPEX. To this end, next generations networks such WiMAX and 3GPP LTE and LTE-Advanced provide support for selfoptimization, self-configuration and self-healing to minimize human-to-system interaction and hence reap the attendant benefits of automation. One of the most important optimization tasks is load balancing as it affects network operation right from planning through the lifespan of the network. Several methods for load balancing have been proposed. While some of them have a very buoyant theoretical basis, they are not practically implementable at the current state of technology. Furthermore, most of the techniques proposed employ iterative algorithm, which in itself is not computationally efficient. This paper proposes the use of soft computing, precisely adaptive neurofuzzy inference system for dynamic QoS-aware load balancing in 3GPP LTE. Three key performance indicators (i.e. number of satisfied user, virtual load and fairness distribution index) are used to adjust hysteresis task of load balancing.

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“…But like GSM and WCDMA, it still has the problem of load unbalance. Much research has been done to deal with the load unbalance problem in LTE-liked packetswitched network [1]- [5]. Most of them use proportional fairness (PF) as the scheduling metric among competing users, and do not consider QoS requirements.…”

Section: Introductionmentioning

confidence: 99%

Dynamic load balancing in 3GPP LTE multi-cell networks with heterogenous services

Wang¹,

Ding²,

Wu³

et al. 2010

Proceedings of the 5th International ICST Conference on Communications and Networking in China

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Abstract-Load balancing among multi-cells in 3GPP LongTerm Evolution (LTE) networks with heterogeneous services is investigated. It is formulated as a multi-objective optimization problem, the objectives of which are load balancing index of services with QoS requirements and network utility of other services. The constraints are physical resource limits and QoS demands. Then the property and complexity of the problem are analyzed, and sequential optimization method is employed to solve it. After that, a practical algorithm for load balancing is developed which includes QoS-guaranteed hybrid scheduling, handover of users with and without QoS requirements, and call admission control. Simulation is made extensively and the results show that the proposed load balancing algorithm can significantly enhance the performance of LTE networks with heterogeneous services, decreasing call block probability of users with QoS requirements, and increasing throughput of boundary users with only a bit degradation of total throughput.Index Terms-3GPP LTE, dynamic load balancing, Quality of Service (QoS)

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Dynamic load balancing and throughput optimization in 3GPP LTE networks

Cited by 45 publications

References 6 publications

From Orthogonal to Non-orthogonal Multiple Access: Energy- and Spectrum-Efficient Resource Allocation

From Orthogonal to Non-orthogonal Multiple Access: Energy- and Spectrum-Efficient Resource Allocation

Adaptive Neuro-Fuzzy Inference System for Dynamic Load Balancing in 3GPP LTE

Dynamic load balancing in 3GPP LTE multi-cell networks with heterogenous services

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