An Association Approach that Combines Resource Consumption and Load Balancing in Heterogeneous Cellular Networks

Zhao, Liqun; Wang, Hongpeng; Zhong, Xiaofeng

doi:10.1109/ithings-greencom-cpscom-smartdata.2017.119

Cited by 1 publication

(4 citation statements)

References 15 publications

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“…In the past few years, user association or cell selection have been studied for HetNets [2][3][4][5][6][7]. In [2], the authors address the user association problem in the downlink transmissions of a multi-tier HetNet and propose a unified distributed algorithm, which aims at maximizing the sum utility of long-term rate and minimizing global outage probability at the same time.…”

Section: User Association Schemes Of Hetnetsmentioning

confidence: 99%

“…In [6], the authors consider the joint optimization problem of user association, subchannel allocation, and power allocation for downlink transmission in multi-cell multi-association orthogonal frequency division multiple access (OFDMA) HetNets with the objective of maximizing the weighted sumrate and propose an alternating optimization method to solve the joint optimization problem. The authors in [7] deal with the problem of user association in HetNets and propose a novel collaborative filtering (CF)-based wireless network recommendation system, which involves social interactions among UEs. A satisfaction game is formulated to deal with this problem, and a utility function is defined to measure a UE's satisfaction.…”

Section: User Association Schemes Of Hetnetsmentioning

confidence: 99%

“…Different user association or cell selection strategies may result in different network transmission performance and quality of service (QoS) to users due to the heterogeneity of RANs. While various user association schemes have been proposed for HetNets [2][3][4][5][6][7] and effectively enhanced the transmission performance of the RANs, the backhaul links may still cause challenges and difficulties in offering QoS guaranteed services to UEs. In particular, the demanding requirements of user services, such as multimedia streaming, web browsing applications, and socially interconnected networks, may cause network congestion and long transmission delay in backhaul links [8].…”

Section: Introductionmentioning

confidence: 99%

“…• The problem of user association or content placement in HetNets has been studied separately in previous works [2][3][4][5][6][7] and [11][12][13][14][15][16]. In this paper, we jointly consider the user association and content placement problem in cache-enabled HetNets and design jointly optimal strategies so that the overall performance of the networks can be maximized.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Network utility optimization-based joint user association and content placement in heterogeneous networks

Chen

Chai

et al. 2018

J Wireless Com Network

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The rapid growth of traffic demands has posed challenges and difficulties on both the radio access networks (RANs) and the backhaul links. While heterogeneous networks (HetNets) are expected to offer diverse radio access capabilities and improve the transmission performance of user equipments (UEs) significantly through integrating various RANs efficiently, the backhaul links may still experience challenges in offering quality of service (QoS) guaranteed services to UEs. To tackle these problems, caching technology, more specifically, caching user contents at the infrastructures of different RANs is proposed as an effective approach. In this paper, we consider the joint user association and cache content placement problem in cache-enabled HetNets. Stressing the tradeoff between user download delay and caching cost, we introduce the concept of utility function which characterizes the joint network performance as the weighted sum of user download delay and the caching cost and formulate the joint user association and cache content placement problem as a network utility optimization problem. As the formulated optimization problem is a nonlinear integer optimization problem which cannot be solved conveniently using traditional optimization tools, we transform the original optimization problem equivalently into three convex subproblems by applying Lagrange partial relaxation and McCormick envelopes, and then propose an iterative algorithm. Within each iteration, for a given set of Lagrange multipliers, the three subproblems are solved respectively by means of the modified Kuhn-Munkres (K-M) algorithm and the locally optimal solutions can be obtained, based on which the Lagrange multipliers can be updated through applying subgradient method. Simulation results demonstrate the effectiveness of the proposed algorithm.

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