Abstract

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.

Highlights

  • The rapidly growing requirements for high-speed mobile broadband applications, such as video streaming and online games, have posed great challenges on both radio access networks (RANs) and core networks

  • Chen et al EURASIP Journal on Wireless Communications and Networking (2018) 2018:122 reducing user download latency is to deploy cache storages at the mobile edge networks, e.g., the base stations (BSs) or article points (APs) of the heterogeneous networks (HetNets) [9, 10]. It has been shown in previous research works that the transmission performance of user equipments (UEs) can be enhanced significantly by caching contents at the infrastructures of the RANs [11,12,13,14,15,16]; designing reasonable cache content placement schemes by taking into account both caching constraints and possible performance enhancement is of particular importance

  • Different from previous works, the joint user association and cache content placement problem for cache-enabled HetNets is studied in this paper by emphasizing the tradeoff between user download delay and caching cost

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Summary

Introduction

The rapidly growing requirements for high-speed mobile broadband applications, such as video streaming and online games, have posed great challenges on both radio access networks (RANs) and core networks. We study the joint user association and content placement problem of cache-enabled HetNets which consists multiple RANs. To achieve joint resource management and performance enhancement of various access networks, we propose a joint resource management architecture, based on which a joint user association and content placement algorithm is designed. 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. Different from previous works, the joint user association and cache content placement problem for cache-enabled HetNets is studied in this paper by emphasizing the tradeoff between user download delay and caching cost. We define the network utility of the HetNet as a weighted sum of file downloading delay and caching cost and find the optimum user association and content placement solution to optimize the utility

System model and proposed joint resource management architecture
Content fetching delay
Maximum cache capacity constraint
Equivalent transformation of original optimization problem
K-M algorithm-based optimal solutions to the subproblems
4: Solve SP1 to obtain the locally optimal solution of xij
Conclusions
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