Joint Optimization of User Association and Inter-Cell Interference Coordination for Proportional Fair-Based System Throughput Maximization in Heterogeneous Cellular Networks

2017 ◽  
Vol E100.B (8) ◽  
pp. 1334-1342 ◽  
Author(s):  
Yoshitaka IKEDA ◽  
Shozo OKASAKA ◽  
Kenichi HIGUCHI
Keyword(s):  
Cellular Networks ◽  
Throughput Maximization ◽  
Joint Optimization ◽  
System Throughput ◽  
User Association ◽  
Interference Coordination ◽  
Heterogeneous Cellular Networks ◽  
Proportional Fair ◽  
Inter Cell Interference

scholarly journals Joint User Association and Energy Offloading in Downlink Heterogeneous Cellular Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Rui Li ◽  
Ning Cao ◽  
Minghe Mao ◽  
Yunfei Chen ◽  
Yifan Hu
Keyword(s):  
Power Allocation ◽  
Cellular Networks ◽  
Communication Systems ◽  
System Throughput ◽  
User Association ◽  
Heterogeneous Cellular Networks ◽  
Macro Cell ◽  
System Resource ◽  
Resource Allocation Scheme

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-of-service (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 iteration-based algorithm outperforms existing algorithms.

scholarly journals Joint Optimization of Content Placement and User Association in Cache-Enabled Heterogeneous Cellular Networks Based on Flow-Level Models

2018 ◽  
Vol 2018 ◽  
pp. 1-20
Author(s):  
Hua Qu ◽  
Gongye Ren ◽  
Jihong Zhao ◽  
Zhenjie Tan ◽  
Shuyuan Zhao
Keyword(s):  
Cellular Networks ◽  
Content Delivery ◽  
Mixed Integer ◽  
Joint Optimization ◽  
User Association ◽  
Heterogeneous Cellular Networks ◽  
Coupled Models ◽  
Average Delay ◽  
Delivery Delay ◽  
Content Placement

Cache-enabled heterogeneous cellular networks (HCNs) have been investigated extensively to alleviate backhaul congestion and reduce content delivery delay. In this paper, we jointly optimize content placement and user association to minimize the average content delivery delay in cache-enabled HCNs based on flow-level models. This formulation considers (1) different timescales of content placement and content delivery, (2) locality of content popularity, and (3) the heterogeneity of spatial traffic distribution, which are often neglected in existing researches. The joint optimization problem is formulated as a mixed integer nonlinear programming problem in load-non-coupled and load-coupled models, respectively. We decouple this problem into two interrelated subproblems and resolve them individually. For the user association problem under a given content placement situation, we propose a content-level selective association algorithm, which allows the requests for different contents at the same location to connect to different base stations (BSs). In addition, we propose a greedy content caching algorithm to add contents to the caches of BSs in an iterative manner. These two algorithms are alternately executed until the caches of all the BSs are filled to capacity. Simulation results show that the proposed algorithm achieves better performance in terms of average delay and backhaul usage compared with traditional content placement and user association approaches.

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