Energy Cost Minimization in Green Heterogeneous
Cellular Networks with Wireless Backhauls
Qiang Yang
(1)
, Xianjun Deng
(2)
and Bang Wang
(1)
(1)
The School of Electronic, Information and Communications,
Huazhong University of Science and Technology (HUST), Wuhan, China.
(2)
The Department of Communications Engineering, University of South China (USC), Hengyang, China.
Email: qiangyang
hust@qq.com, dengxj615@qq.com, wangbang@hust.edu.cn
Abstract—In this paper, we study the problem of energy
cost minimization in heterogenous cellular networks with hybrid
energy supplies, where the network architecture consisting of
radio access part and wireless backhaul links. Owing to the
diversities of mobile traffic and renewable energy, the energy
cost minimization problem involves both temporal and spatial
dimensional optimization. Our proposed solution consists of four
parts: At first, we obtain estimated average energy consumption
profiles for all base stations based on the temporal traffic
statistics; Second, we formulate the green energy allocation
optimization in the temporal domain to minimize energy cost for
each BS. Third, given the allocated green energy and practical
user distribution in each slot, we propose a user association
algorithm to minimize total energy cost in the spatial dimension.
Fourth, based on the actual user association scheme, we readjust
the green energy allocation for each BS. Simulation results show
that our proposed solution can significantly reduce the total
energy cost, compared with the recent peer algorithms.
Index Terms—Energy efficiency, renewable energy, heteroge-
neous cellular network, wireless backhauls, resource allocation.
I. INTRODUCTION
With the ever increasing of smart devices and multimedia
applications, wireless data traffic has been experiencing an
exponential increase in the wireless cellular networks, which
has also led to more and more energy consumption and green-
house gas emission [1], [2]. How to achieve energy efficient
network operation has become a main issue of concern in
wireless communications.
An attractive approach is to deploy a heterogeneous network
consisting of multiple tiers of small cell pico BSs and large cell
macro BSs with overlapped coverage areas [3]–[7]. To support
flexible heterogeneous network deployment, nowadays pico
BSs can use wireless backhauls to forward their traffic into the
core network through a multi-hop path where some pico BSs
serve as relay nodes [8]. In such heterogeneous networks, it
is important to take into account the energy efficiency of both
radio access networks and wireless backhaul links [9], [10].
Recently, operators and researchers have proposed to adopt
renewable energy, such as solar energy, wind energy and so
on, to power BSs for wireless data transmissions [11]–[14]. For
example, German mobile operator E-Plus [15] has launched
the first generation of green BSs by using a combination of
solar and wind power.
In this paper, we study the total energy cost minimization
problem in a heterogeneous cellular network, where BSs can
be powered by either on-grid energy or green energy. In such
a network, macro BSs connect to the core network directly
through an optical fiber backhaul network; While pico BSs
in each macro cell connect to the core network with the help
of a macro BS directly or using another pico BSs as relays
to reach the macro BS. We can divide pico BSs into two
kinds: subordinate pico BSs and superior pico BSs, based
on their roles in the backhaul network. Due to the temporal
and spatial diversities of mobile traffic and renewable energy,
our proposed solution consists of four parts to solve these sub-
problems. They are the energy consumption estimation (ECE)
algorithm, green energy allocation (GEA) algorithm, user
association (UA) algorithm, and green energy reallocation
(GER) algorithm. In the simulations, we compare the proposed
solution with two peer algorithms in a single macro cell with
a tree backhaul topology. Simulation results demonstrate that
our proposed solution can achieve significant improvement in
terms of the reduction of total energy cost.
The rest of the paper is organized as follows: Section II
presents the system model, and the problem formulation is
provided in Section III. The proposed solution is presented in
Section IV and evaluated in Section V. Finally, the paper is
concluded in Section VI.
II. S
YSTEM MODEL
Network Model: We adopt a tree topology in one macro
cell. As the tree root, the macro BS uses an optical fiber as its
backhaul link. Each pico BS uses an out-of-band microwave
backhaul to connect to the core network through the macro
BS, either directly or through the relay of another pico BS.
Each superior pico BS should relay the traffic from all of its
subordinate pico BSs. We use N = {1, 2, ··· ,N} to denote
the set of all N BSs in the network, and use N
1
, N
2
and
N
3
to denote the set of macro BSs, superior pico BSs and
subordinate pico BSs, respectively. We assume that the tree
topology and the superior-subordinate relation among all BSs
are known. Let N
sub
= {N
sub
1
, N
sub
2
, ..., N
sub
N
} indicate the
BS-BS layer relation set. We use N
sub
i
to denote the set of
subordinate BSs of BS i. We consider a cellular network with
M mobile users, and use M to denote the users set. The
continuous time line is divided into K = |K| consecutive time
slots each with length of τ seconds. The proposed algorithm
is executed at the beginning of each slot.
2016 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom)
and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)
978-1-5090-5880-8/16 $31.00 © 2016 IEEE
DOI 10.1109/iThings-GreenCom-CPSCom-SmartData.2016.150
697
2016 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom)
and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)
978-1-5090-5880-8/16 $31.00 © 2016 IEEE
DOI 10.1109/iThings-GreenCom-CPSCom-SmartData.2016.150
698