Distributed Base Station Association and Power Control for Heterogeneous Cellular Networks

Ha, Vu Nguyen; Le, Long Bao

doi:10.1109/tvt.2013.2273503

Cited by 92 publications

(50 citation statements)

References 34 publications

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“…For CDMA-based networks, joint optimization of BS-UE association and interference management is considered in [22] for network sum-rate maximization and in [23] for minimum UE's SINR maximization. It is not straightforward to apply the results of [22] and [23] to networks in which a BS uses orthogonal channels to serve its UEs to eliminate intracell interference.…”

Section: Introductionmentioning

confidence: 99%

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Joint Load Balancing and Interference Management for Small-Cell Heterogeneous Networks With Limited Backhaul Capacity

Tam

Tuan

Ngo

et al. 2017

IEEE Trans. Wireless Commun.

110

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Abstract-In this paper, new strategies are devised for joint load balancing and interference management in the downlink of a heterogeneous network, where small cells are densely deployed within the coverage area of a traditional macrocell. Unlike existing work, the limited backhaul capacity at each base station (BS) is taken into account. Here users (UEs) cannot be offloaded to any arbitrary BS, but only to ones with sufficient backhaul capacity remaining. Jointly designed with traffic offload, transmit power allocation mitigates the intercell interference to further support the quality of service of each UE. The objective here is either (i) to maximize the network sum rate subject to minimum throughput requirements at individual UEs, or (ii) to maximize the minimum UE throughput. Both formulated problems belong to the difficult class of mixed-integer nonconvex optimization. The inherently binary BS-UE association variables are strongly coupled with the transmit power variables, making the problems even more challenging to solve. New iterative algorithms are developed based on an exact penalty method combined with successive convex programming, where we deal with the binary BS-UE association problem and the nonconvex power allocation problem one at a time. At each iteration of the proposed algorithms, only two simple convex problems need to be solved in the same time scale. It is proven that the algorithms improve the objective functions in each iteration and converge eventually. Numerical results demonstrate the efficiency of the proposed algorithms in both traffic offloading and interference mitigation.

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Section: Introductionmentioning

confidence: 99%

“…It is not straightforward to apply the results of [22] and [23] to networks in which a BS uses orthogonal channels to serve its UEs to eliminate intracell interference. Different from CDMA, each UE here is only assigned with a fraction of the time/frequency slots depending on the current load at its serving BS.…”

Section: Introductionmentioning

confidence: 99%

Joint Load Balancing and Interference Management for Small-Cell Heterogeneous Networks With Limited Backhaul Capacity

Tam

Tuan

Ngo

et al. 2017

IEEE Trans. Wireless Commun.

110

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“…Game theory based resource allocation and interference mitigation in small cells have been widely investigated in existing works [4]- [11]. In [4], non-cooperative power allocation with signal-to-interference-plus-noise ratio (SINR) adaptation is used to alleviate the interference from femtocells to macrocells, while in [5] Stackelberg game based power control is formulated to maximize femtocells' capacity under a cross-tier interference constraint.…”

Section: Introductionmentioning

confidence: 99%

“…A non-cooperative game based power control algorithm is proposed in [11] together with a base station association scheme for heterogeneous networks. In our previous work [12] [13], resource scheduling (based on uniform pricing and differential pricing game) and power control were proposed for small cell networks.…”

Section: Introductionmentioning

confidence: 99%

Resource Allocation for Cognitive Small Cell Networks: A Cooperative Bargaining Game Theoretic Approach

Zhang

Jiang

Beaulieu

et al. 2015

IEEE Trans. Wireless Commun.

332

191

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Abstract-Cognitive small cell networks have been envisioned as a promising technique to meet the exponentially increasing mobile traffic demand. Recently, many technological issues pertaining to cognitive small cell networks have been studied, including resource allocation and interference mitigation, but most studies assume non-cooperative schemes or perfect channel state information (CSI). Different from the existing works, we investigate the joint uplink subchannel and power allocation problem in cognitive small cells using cooperative Nash bargaining game theory, where the cross-tier interference mitigation, minimum outage probability requirement, imperfect CSI and fairness in terms of minimum rate requirement are considered. A unified analytical framework is proposed for the optimization problem, where the near optimal cooperative bargaining resource allocation strategy is derived based on Lagrangian dual decomposition by introducing time-sharing variables and recalling the Lambert-W function. The existence, uniqueness, and fairness of the solution to this game model are proved. A cooperative Nash bargaining resource allocation algorithm is developed, and is shown to converge to a Pareto-optimal equilibrium for the cooperative game. Simulation results are provided to verify the effectiveness of the proposed cooperative game algorithm for efficient and fair resource allocation in cognitive small cell networks.

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“…[6] investigated the main challenging interference management techniques in dense cellular network (DenseNet) and proposed two interference coordination schemes based on time-domain and carrier-domain respectively. [7] recommended a power control algorithm within two-tier network based on non-cooperative gaming, the goal of which is to fulfill SINR requirements of users whenever possible and maximize system throughput simultaneously. [8] designed a price-based Stackelberg Gaming strategy used for power control of femtocells.…”

Section: Introductionmentioning

confidence: 99%

An Iterative Power Allocation Algorithm Aimed at Maximization of System Capacity in Two-Tier Cellular Network

Shi¹,

Song²,

Dong³

et al. 2017

dtcse

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Abstract. To fulfill the urgent requirement for ubiquitous information exchange, the infrastructure of the next-generation mobile system is developing toward a densely distributed cellular network with multiple tiers of base stations and access technologies serving users with different mobility styles and bandwidth demands. Therefore, the need for an advanced power control and interference mitigation strategy is even more prominent. This paper proposes an iterative power allocation algorithm for mobile users within a two-tier mobile network infrastructure. The algorithm is based on Newton's method and is aimed at maximizing system capacity of the whole system. Simulation results prove that, compared to the traditional power control scheme, the proposed scheme remarkably improves utilization of latent system capacity and effectively reduces user power consumptions, and the algorithm possesses a favorable performance of convergence.

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Distributed Base Station Association and Power Control for Heterogeneous Cellular Networks

Abstract: and an addendum degree from the École Nationale Supérieure des Télécommunications de Bretagne-Groupe des Écoles des Télécommunications, Bretagne, France, in 2007. He is currently working toward the Ph.D. degree with the

Cited by 92 publications

References 34 publications

Joint Load Balancing and Interference Management for Small-Cell Heterogeneous Networks With Limited Backhaul Capacity

Joint Load Balancing and Interference Management for Small-Cell Heterogeneous Networks With Limited Backhaul Capacity

Resource Allocation for Cognitive Small Cell Networks: A Cooperative Bargaining Game Theoretic Approach

An Iterative Power Allocation Algorithm Aimed at Maximization of System Capacity in Two-Tier Cellular Network

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