Joint User Association and Energy Offloading in Downlink Heterogeneous Cellular Networks

Hindawi Mobile Information Systems Volume 2018, Article ID 7091512, 9 pages https://doi.org/10.1155/2018/7091512 Research Article Joint User Association and Energy Offloading in Downlink Heterogeneous Cellular Networks Rui Li ,1 Ning Cao ,1 Minghe Mao ,1 Yunfei Chen ,1,2 and Yifan Hu 1 2 1 School of Computer and Information, Hohai University, Nanjing 210098, China School of Engineering, University of Warwick, Coventry CV4 7AL, UK Correspondence should be addressed to Ning Cao; Received 22 January 2018; Revised 28 May 2018; Accepted 12 June 2018; Published 19 August 2018 Academic Editor: Alessandro Bazzi Copyright © 2018 Rui Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. As a key technology in Long-Term Evolution-Advanced (LTE-A) mobile communication systems, heterogeneous cellular networks (HCNs) add low-power nodes to offload the traffic from macro cell and therefore improve system throughput performance. In this paper, we investigate a joint user association and resource allocation scheme for orthogonal frequency division multiple access- (OFDMA-) based downlink HCNs for maximizing the energy efficiency and optimizing the system resource. The algorithm is formulated as a nonconvex optimization, with dynamic circuit consumption, limited transmit power, and quality-ofservice (QoS) constraints. As a nonlinear fractional problem, an iteration-based algorithm is proposed to decompose the problem into two subproblems, that is, user association and power allocation. For each iteration, we alternatively solve the two subproblems and obtain the optimal user association and power allocation strategies. Numerical results illustrate that the proposed iterationbased algorithm outperforms existing algorithms. 1. Introduction Shortage of power resource and scarcity of spectrum resource are two major factors in restricting communication development, and thus, green-oriented communication system design has gradually attracted attention of academics particularly in wireless communication filed. Energy consumption in information and communication technology (ICT) industry accounts for about 2%–6% of global total consumption, 60% of which are consumed on base stations (BSs). In recent years, innovations in this area facilitate the unprecedented growth of traffic data which accelerates the problem more seriously [1–4]. In order to improve resource efficiency, energy harvesting can be used [5], but more effectively wireless systems are prone to miniaturization and heterogeneity, which may be composed of various types of networks to support growth of traffic demand. For instance, coordinating with macro cell, for example, pico BSs and femto BSs are used to offload the traffic and energy consumption from the large-scaled BSs. The layout of heterogeneous cellular networks (HCNs) is more reasonable and economical than that of macro-only networks. However, extreme densification of BSs would bring a new challenge: cochannel interference is introduced by spectrum sharing in a local-area, which has significantly negative impact on system capacity [6]. Considering its high spectrum efficiency and flexibility in allocating radio resource, orthogonal frequency division multiple access- (OFDMA-) based HCNs system is a good candidate to achieve better performance wireless communications [7]. Resource allocation for HCNs is investigated from different perspectives in one/multi-cell scenarios. In previous researches, studying of user association is more attractive in HCNs [8–11], as user allocation have an impact on the interference as well as capacity. Power consumption is also a factor that affects the communication performance especially for intra- and intercell interference suppression in networks [12–15]. However, capacity and coverage enhancement are not always achieved by increasing transmit power. Increased transmit power may generate more interference to neighboring cells which has became a challenging issue. As a result, energy-efficient designs have 2 recently attracted a lot of interest to exploit the potential performance gains toward green wireless communication systems [16–18]. Energy efficiency is defined as the ratio of system throughput to total energy consumption. In [19], the authors proposed a utility-based energy-efficient (UEE) resource allocation algorithm with mixed traffic in downlink HCNs which only achieves a suboptimal solution. Zhou et al. [20] proposed a fractional programming framework, by solving the weighted energy efficiency problem iteratively consisting of channel allocation and power allocation. A non-cooperative resource competition game was introduced in [21] for energy efficiency optimization in dense networks under traffic-related minimum rate requirement. Cheng et al., Zhou et al., and Wang et al. [19–21] focused on jointly channel allocation and power control where the set of users associated with the BS were predetermined in the optimal process. In most of the previous works, they only consider either user association or subchannel allocation but not both of them. However, the system performance is affected by both of them. Additionally, for the above works, system power consumption only involves the transmit power and static circuit power. For energy efficient resource allocation, circuit power is also accounted in addition to the transmitted power with the increasing demand for highcapacity networks, which is more practical and general [22, 23]. The novelty of this work is to consider both user association and subchannel allocation in the optimization of energy efficiency with circuit power. These practical conditions have not been studied together in the literature. In this paper, we formulate an energy efficiency maximization problem via jointly optimizing user association, subchannel association, and power control for OFDMAbased downlink HCNs in terms of QoS requirement and available power constraints. In particular, the circuit power consumption is modeled as a function of system rate, not just as a constant. We address the nonconvex mixed integer optimization problems by applying proposed iterationbased algorithm. By utilizing the Dinkelbach method, it transforms the primary problem to a subtractive form problem. The EE maximization problem is decomposed equivalently into two subproblems which can then be solved by using the iterative method alternatively. Compared with the previous algorithms, simulation results demonstrate that the proposed scheduling strategy gains a tradeoff between system capacity and overall consumption and then obtains an optimal resource allocation. The remainder of the paper is formulated as follows: Section 2 briefly introduces the system model and formulates the energy efficiency maximization problem. Based on this model, an iteration-based algorithm is proposed to solve the three-layer p (...truncated)