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...

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Vydané v:	IEEE transactions on wireless communications Ročník 16; číslo 2; s. 872 - 884
Hlavní autori:	Ho Huu Minh Tam, Hoang Duong Tuan, Duy Trong Ngo, Duong, Trung Q., Poor, H. Vincent
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 01.02.2017 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	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
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Abstract	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.
AbstractList	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.
Author	Duong, Trung Q. Hoang Duong Tuan Poor, H. Vincent Duy Trong Ngo Ho Huu Minh Tam
Author_xml	– sequence: 1 surname: Ho Huu Minh Tam fullname: Ho Huu Minh Tam email: huuminhtam.ho@student.uts.edu.au organization: Fac. of Eng. & Inf. Technol., Univ. of Technol. Sydney, Ultimo, NSW, Australia – sequence: 2 surname: Hoang Duong Tuan fullname: Hoang Duong Tuan email: tuan.hoang@uts.edu.au organization: Fac. of Eng. & Inf. Technol., Univ. of Technol. Sydney, Ultimo, NSW, Australia – sequence: 3 surname: Duy Trong Ngo fullname: Duy Trong Ngo email: duy.ngo@newcastle.edu.au organization: Sch. of Electr. Eng. & Comput., Univ. of Newcastle, Callaghan, NSW, Australia – sequence: 4 givenname: Trung Q. surname: Duong fullname: Duong, Trung Q. email: trung.q.duong@qub.ac.uk organization: Sch. of Electron., Queen's Univ. Belfast, Belfast, UK – sequence: 5 givenname: H. Vincent surname: Poor fullname: Poor, H. Vincent email: poor@princeton.edu organization: Dept. of Electr. Eng., Princeton Univ., Princeton, NJ, USA
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SubjectTerms	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
Title	Joint Load Balancing and Interference Management for Small-Cell Heterogeneous Networks With Limited Backhaul Capacity
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