1458 IEEE COMMUNICATIONS LETTERS, VOL. 22, NO. 7, JULY 2018
Coverage Performance of NOMA in Wireless Caching Networks
Zhongyuan Zhao , Member, IEEE, Mingfeng Xu, Weiliang Xie, Zhiguo Ding , Senior Member, IEEE,
and George K. Karagiannidis
, Fellow, IEEE
Abstract—In order to keep a balance between the transmission
delay of backhaul and the spectrum efficiency of access
links, the coverage performance of wireless networks with
non-orthogonal multiple access (NOMA) and content caching is
studied. First, an explicit expression for the coverage probability
of a typical user is presented by using stochastic geometry and
order statistics. This expression can provide useful insights in
order to improve the coverage performance of NOMA com-
munications. Second, a closed-form expression for the average
coverage probability is derived. Finally, simulation results are
provided to validate the accuracy of the analytical framework
and demonstrate the performance gain, due to NOMA.
Index Terms—Non-orthogonal multiple access (NOMA),
content caching, coverage probability, stochastic geometry.
I. INTRODUCTION
N
ON-ORTHOGONAL multiple access (NOMA) is con-
sidered as a very promising technique to significantly
improve the spectrum efficiency of fifth generation (5G) and
beyond communication systems [1]. Since multiple users can
be served simultaneously, NOMA can achieve significant
performance gains, in terms of system throughput as well as
connectivity. Furthermore, the outage performance of NOMA
with cooperation and user pairing has been studied in [2],
which show that NOMA can achieve higher transmission data
rate than the conventional orthogonal multiple access (OMA)
schemes. In [3] and [4], NOMA has been used in large-
scale heterogeneous networks and multicast cognitive radio
networks, respectively.
Although NOMA can improve the delivery efficiency of the
BSs, it causes long waiting delay, since the NOMA transmis-
sions cannot begin until all the requested messages are sent to
the BSs via the backhaul. Therefore, to mitigate the increased
loading of the backhaul, the joint design of NOMA and
Manuscript received March 18, 2018; revised April 17, 2018; accepted
April 19, 2018. Date of publication April 26, 2018; date of current version
July 10, 2018. The work of Z. Zhao and M. Xu was supported in part by
the National Natural Science Foundation of China (Grant No. 61501045),
in part by the State Major Science and Technology Special Projects (Grant
No. 2017ZX03001014). The work of Z. Ding was supported by the UK
EPSRC under grant number EP/L025272/1 and by H2020-MSCA-RISE-2015
under grant number 690750. The associate editor coordinating the review of
this paper and approving it for publication was T. Ngatched. (Corresponding
author: Zhongyuan Zhao.)
Z. Zhao and M. Xu are with the Key Laboratory of Universal Wireless
Communications, Ministry of Education, Beijing University of Posts and
Telecommunications, Beijing 100876, China (e-mail: zyzhao@bupt.edu.cn;
xu_mingf@bupt.edu.cn).
W. Xie is with the China Telecom Technology Innovation Center,
Beijing 102209, China (e-mail: xiewl@ctbri.com.cn).
Z. Ding is with the School of Electrical and Electronic Engineer-
ing, The University of Manchester, Manchester M13 9PL, U.K. (e-mail:
zhiguo.ding@manchester.ac.uk).
G. K. Karagiannidis is with the Electrical and Computer Engineering
Department, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
(e-mail: geokarag@auth.gr).
Digital Object Identifier 10.1109/LCOMM.2018.2830376
content caching has been investigated in [5] and [6]. However,
due to the complicated interference effect and the non-uniform
coverage, it is difficult to assess if NOMA can reduce the total
transmission delay. In order to find a sophisticated balance
between the transmission delay of backhaul and the spectrum
efficiency of access links, we study the coverage performance
of NOMA in wireless caching networks.
The main contributions of this letter can be summarized
as follow: First, by employing stochastic geometry and order
statistics, an explicit expression for the coverage probability of
a typical user is derived, which can provide useful insights on
how to improve the coverage performance. Second, a closed-
form expression for the average coverage probability is pre-
sented, which shows that the transmission performance of
NOMA can be guaranteed, when the data rate of backhaul is
high enough. Finally, simulation results are provided to verify
the accuracy of the analysis and to show the performance gain
of NOMA in wireless caching networks.
II. S
YSTEM MODEL
Consider a downlink transmission scenario in wireless
caching networks, where each BS serves multiple users. The
locations of BSs are modeled as a homogeneous Poisson point
process (PPP) Φ, with a given density λ. In order to character-
ize the fact that the users are more likely to lie close to their
associated BSs, the locations of users are modeled as a Mat´ern
cluster process Ψ. In particular, we focus on a representative
cell C
i
, where its coverage area can be modeled as a disc
D(B
i
,r),wherer is its radius, and the location of the serving
BS B
i
acts as its center, B
i
∈ Φ. All the associated users of
C
i
form a point cluster ψ
i
of Ψ, which are independently and
uniformly distributed in D(B
i
,r). Moreover, the number of
users belonging in ψ
i
is denoted as M
i
, which follows Poisson
distribution with a given expectation μ, i.e., M
i
∼ Poi(μ).
Without loss of generality, U
j
is selected as a typical user,
U
j
∈ ψ
i
. Denoting the distance between U
j
and B
i
as d
j
,
the cumulative distribution function (CDF) and the probability
density function (PDF) of d
j
can be expressed as:
F (d
j
)=
d
2
j
r
2
,f(d
j
)=
2d
j
r
2
,d
j
∈ [0,r],U
j
∈ ψ
i
. (1)
In this letter, we assume that each user belonging to Ψ,
requests a different content object simultaneously, while
NOMA transmissions are employed to improve the spectrum
efficiency. Without loss of generality, the representative cell C
i
is taken as an example. All the content objects required by the
users of ψ
i
can be denoted as a set Ω
i
= {s
1
,...,s
M
i
},where
s
j
is the content object required by U
j
. The NOMA scheme
under investigation consists of the following two phases:
1) Backhaul Transmission Phase: In order to support
NOMA transmissions, B
i
should obtain all the content objects
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