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

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 stat...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on wireless communications Vol. 16; no. 2; pp. 872 - 884
Main Authors: Ho Huu Minh Tam, Hoang Duong Tuan, Duy Trong Ngo, Duong, Trung Q., Poor, H. Vincent
Format: Journal Article
Language:English
Published: New York IEEE 01.02.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Combinatorial optimization
Convexity
Downlink
heterogeneous network
Interference
Iterative algorithms
limited backhaul
Load balancing
Load management
Mixed integer
Optimization
power allocation
Quality of service
Resource management
successive convex programming
Throughput
ISSN:1536-1276, 1558-2248
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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: 1) to maximize the network sum rate subject to minimum throughput requirements at individual UEs, or 2) to maximize the minimum UE throughput. Both formulated problems belong to the difficult class of mixed-integer nonconvex optimization problems. 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 the binary BS-UE association problem and the nonconvex power allocation problem are dealt with one at a time. At each iteration of the proposed algorithms, only two simple convex problems need to be solved at the same time scale. It is proven that the algorithms improve the objective functions at each iteration and converge eventually. Numerical results demonstrate the efficiency of the proposed algorithms in both traffic offloading and interference mitigation.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2016.2633262