• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3394-3408
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• 2014

Conventional mobile state (MS) and base station (BS) association based on average signal strength often results in imbalance of cell load which may require more powerful processor at BSs and degrades the perceived transmission rate of MSs. To deal with this problem, a Markov decision process (MDP) for load balancing in a multi-cell system with multi-carriers is formulated. To solve the problem, exploiting Sarsa algorithm of on-line learning type [12], ${\alpha}$-controllable load balancing algorithm is proposed. It is designed to control tradeoff between the cell load deviation of BSs and the perceived transmission rates of MSs. We also propose an ${\varepsilon}$-differential soft greedy policy for on-line learning which is proven to be asymptotically convergent to the optimal greedy policy under some condition. Simulation results verify that the ${\alpha}$-controllable load balancing algorithm controls the behavior of the algorithm depending on the choice of ${\alpha}$. It is shown to be very efficient in balancing cell loads of BSs with low ${\alpha}$.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2563-2568
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• 2013

Recently, various solutions to support explosively growing mobile data traffic have attracted intensive attentions. However, the range of spectrum which can be exploited for mobile communications is very limited. Small cell networks are actively investigated because they can efficiently offload mobile data traffic from macro cells without using additional spectrum. In this paper, we developed a system-level simulator considering small cell networks in the indoor environments. We compare the performance of outage probability when a load-balancing algorithm is utilized or not. We can reduce the outage probability of congested BS with the load-balancing algorithm. In addition, overall outage probability of whole wireless systems can be reduced by using the proposed load-balancing algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.7A
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• pp.757-767
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• 2008

Start Ongoing next generation networks are expected to be deployed over current existing networks, in the form of overlayed heterogeneous networks, in particular, in hot spot areas. Therefore, it will be necessary to develop an interworking technique such as load balancing, to achieve increased overall resource utilization in the various heterogeneous networks. In this paper, we present a new load balancing mechanism termed 'soft' load balancing where the IP(Internet Protocol) traffic of a user is divided into sub-traffic, each of which flows into a different access network. The terminology of soft load balancing involves the use of both load sharing and handover techniques. Through a numerical analysis, we obtain an optimal LBR (Load Balancing Ratio) for determining the volume of traffic delivered to each network over an overlayed multi-cell environment. Using the optimal LBR, a more reliable channel transmission can be achieved by reducing the outage probability efficiently for a given user traffic.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2230-2237
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• 2015

Inspired by the synchronization phenomena observed in the Nature, we propose an autonomous load balancing method for a wireless network. We model the load balancing problem of cells providing wireless access services as a synchronization problem in the Nature and design an algorithm for each cell to distribute loads in a self-determining way based on the load differences among its neighbor cells. Through simulations, we verify the feasibility of the proposed method in that cell loads can be balanced efficiently eve if cells make decision autonomously using their local information.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.2
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• pp.1-11
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• 2001

This paper considers the scheduling of cell-based handoffs to balance the traffic in a fiber-optic microcelluar system. In the system depending on the order of cell based handoff, periodical balancing of the traffic among microcells can be achieved. The cell based handoff problem is formulated as a dynamic programming and the computational complexity is analyzed. Since the scheduling problem requires real time solution, heuristic algorithms are proposed and the computational results are discussed.

• Journal of Communications and Networks
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• v.10 no.1
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• pp.38-43
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• 2008

In this paper, adaptive channel borrowing approach fuzzy neural networks for load balancing (ACB-FNN) is presented to maximized the number of served calls and the depending on asymmetries traffic load problem. In a wireless network, the call's arrival rate, the call duration and the communication overhead between the base station and the mobile switch center are vague and uncertain. A new load balancing algorithm with cell involved negotiation is also presented in this paper. The ACB-FNN exhibits better learning abilities, optimization abilities, robustness, and fault-tolerant capability thus yielding better performance compared with other algorithms. It aims to efficiently satisfy their diverse quality-of-service (QoS) requirements. The results show that our algorithm has lower blocking rate, lower dropping rate, less update overhead, and shorter channel acquisition delay than previous methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1569-1586
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• 2015

This paper considers the optimal cell association and resource allocation for load balancing in a heterogeneous cellular network subject to user's quality-of-service (QoS) constraints. We adopt the proportional fairness (PF) utility maximization formulation which also accommodates the QoS constraints in terms of minimum rate requirements. With equal resource allocation this joint optimization problem is either infeasible or requires relaxation that yields a solution which is difficult to implement. Nevertheless, we show that this joint optimization problem can be effectively solved without any priori assumption on resource allocation and yields a cell association scheme which enforces single BS association for each user. We re-formulated the joint optimization problem as a network-wide resource allocation problem with cardinality constraints. A reweighted heuristic l₁-norm regularization method is used to obtain a sparse solution to the re-formulated problem. The cell association scheme is then derived from the sparsity pattern of the solution, which guarantees a single BS association for each user. Compared with the previously proposed method based on equal resource allocation, the proposed framework results in a feasible cell association scheme and yields a robust solution on resource allocation that satisfies the QoS constraints. Our simulations illustrate the impact of user's minimum rate requirements on cell association and demonstrate that the proposed approach achieves load balancing and enforces single BS association for users.

• ETRI Journal
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• v.36 no.5
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• pp.761-771
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• 2014

Long-Term Evolution employs a hard handover procedure. To reduce the interruption of data flow, downlink data is forwarded from the serving eNodeB (eNB) to the target eNB during handover. In cellular networks, unbalanced loads may lead to congestion in both the radio network and the backhaul network, resulting in bad end-to-end performance as well as causing unfairness among the users sharing the bottleneck link. This work focuses on congestion in the transport network. Handovers toward less loaded cells can help redistribute the load of the bottleneck link; such a mechanism is known as load balancing. The results show that the introduction of such a handover mechanism into the simulation environment positively influences the system performance. This is because terminals spend more time in the cell; hence, a better reception is offered. The utilization of load balancing can be used to further improve the performance of cellular systems that are experiencing congestion on a bottleneck link due to an uneven load.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.10
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• pp.45-49
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• 2014

In this paper, the performance of the interference cancellation using multiple receive antennas is evaluated for heterogeneous cellular systems when user association and load balancing problems are optimized for cell edge users. The simulation results show that the interference cancellation method remarkably improves the rate performance of load-balanced cells.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.205-206
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• 2008

We propose load balancing algorithm based on cross layer designing for MIMO OFDM system. When there are many users using data service, base station(BS) should distribute traffic. Moreover, cross layer design gives benefit managing radio resource and network bandwidth management. Proposed cross layer load balancing technique manages both BS's bandwidth allocation and MS’s power control. One BS request bandwidth to other BSes and other BSes reduce each bandwidth. And BSes reduce power of sub carriers for reserving available bandwidth of backhaul. MSes that didn't get service can be served by obtaining bandwidth from other BSes. The simulation result shows more users can be served and cell throughput was increased