GENERALIZED POWER ALLOCATION (GPA) SCHEME FOR NON-ORTHOGONAL MULTIPLE ACCESS (NOMA) BASED WIRELESS COMMUNICATION SYSTEM

International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.8, No.5/6, December 2018
DOI : 10.5121/ijcseit.2018.8601 1
GENERALIZED POWER ALLOCATION (GPA)
SCHEME FOR NON-ORTHOGONAL MULTIPLE
ACCESS (NOMA) BASED WIRELESS
COMMUNICATION SYSTEM
Tofail Ahmed1
, Rubaiyat Yasmin2
, Halida Homyara2
and M.A.F.M Rashidul
Hasan2
1
Department of Information and Communication Engineering, Bangladesh Army
University of Engineering and Technology, Quadirabad Cantonment, Natore, Bangladesh
2
Department of Information and Communication Engineering, University of Rajshahi,
Rajshahi, Bangladesh
ABSTRACT
This paper presents a Generalized Power Allocation (GPA) scheme for different users in Non-Orthogonal
Multiple Access (NOMA) based wireless communication system. The power allocation to the users becomes
complex with the increased number of users. There are some conventional schemes for power allocation in
NOMA but they have to optimize some parameters arbitrarily. In this paper, a simple but effective power
allocation scheme has been formulated and tested by simulations. The proposed GPA scheme does not need
any parameter adjustment. Theoretical power distribution to different users of NOMA has been calculated
using the proposed GPA technique. The calculated powers of individual users with the proposed scheme
are different and more distributed than the arbitrary power allocation scheme which satisfies the basic
condition of NOMA. The total of calculated powers with GPA scheme shows only 01% variation with the
arbitrary power allocation scheme which shows the consistency of GPA scheme with other schemes. The
performance of NOMA based wireless communication system with GPA scheme has been simulated under
various conditions using Matlab. The simulated BER performance for NOMA based wireless
communication system using different modulation techniques show similar results with other conventional
schemes which validates the formulation of GPA scheme.
KEYWORDS
BER, power allocation, OFDMA, NOMA, FTPA, GPA, fairness index.
1. INTRODUCTION
The rapid growth of innovations in information and communication technology area has greatly
emphasized the wireless communication experience of current generation. In future, new
generation are expected to be surrounded by smart objects in smart homes, offices, streets, and
cities in the smart world [1]. Researchers and network service providers face many challenges due
to the exponential growth of data traffic and connected devices. In this context, we need to
improve network performance in terms of throughput and capacity, or number of users. However,
the radio resources, the wireless spectrum and transmit power are limited and current wireless
communication technologies are struggling to accommodate such increase in the traffic demand
within the available resources. The technologies and new ideas are needed to improve the
capacity and to provide high data rate. At multi-carrier wireless communication systems,
Orthogonal Frequency Division Multiplexing (OFDM) has been widely adopted based on its

2
advantage of transforming a frequency selective fading channel into a number of narrowband flat
fading sub channels. Wireless multiple access technique can be realized in two ways: Orthogonal
Frequency Division Multiple Access (OFDMA) [2] and Non-Orthogonal Multiple Access
(NOMA) [3]. In view of increasing the spectral efficiency of the next generation networks and
reduction of inter cell interference levels, NOMA technique seems to be promising [4]. All the
users in NOMA use the same time and frequency resources which results in improved spectral
efficiency but power is different for all users. Hence NOMA is a power domain multiplexing
scheme [5]. However there are many challenges in NOMA to transmit the signal in efficient
ways. One of them is to handle the power allocation of different users in efficient ways; hence we
focused on power allocation technique for NOMA. Because in NOMA system, the frequency
spectrum is not divided likes OFDMA. Rather the frequency is same but the power is different for
different users in NOMA based wireless communication system. The application of NOMA for
5G communication is being studied [6-8] and explored.
2. RELATED WORKS
The selection of suitable power allocation technique is crucial to make NOMA more effective.
Paper [4, 5] showed the performance of NOMA by dividing the power to different users
arbitrarily, 20% of total power is allocated to one user and 80% is allocated to other user without
any mathematical modeling. In paper [9], the power for different users for NOMA have been also
done arbitrarily, there is no specific formulation or model of power allocation technique.
Therefore, there is no specific option of diving power as the number of user increases. On the
other hand there are some specific power allocation techniques. Paper [10] is one of them where
Fractional Transmit Power Allocation (FTPA) scheme has been used. In this scheme, a parameter
named ‘fairness index’ is to be optimized arbitrarily. Paper [11] also shows the calculation of
fairness index for power allocation to multiple users and need to be optimized for effective result.
Therefore we focused to formulate a generalized power allocation scheme [14] for NOMA where
no optimization is needed and designed for multiple users.
The rest of the paper is organized as follows. Section 3 introduces basic NOMA system design
with algorithm. Section 4 discusses the conventional power allocation schemes for NOMA. In
section 5, we have proposed a generalized power allocation scheme and calculated individual
powers for multiple users using our proposed scheme. The results with comparative study has
been shown and discussed in section 6. The paper is concluded with our findings and future work
in section 7.
3. NOMA SYSTEM DESIGN
A two user case is assumed with single transmitter, and a single receiver antenna. The overall
system transmission bandwidth is assumed to be 1 Hz. The base station transmits a signal for
User 1 and User 2 which is represented as xi with transmission power Pi (i=1,2). The sum of Pi is
restricted to be the total power P at maximum. In the NOMA, x1 and x2 are superposition coded
[13] as
(1)
The received signal at both users is represented as
(2)
where hi is the complex channel coefficient between users and the base station [8]. Term wi
denotes the receiver Gaussian noise including inter-cell interference.

3
3.1 NOMA Structure for Transmisson
Fig.1 shows that the NOMA uses a base station transmission scheme.
Fig. 1.Block diagram of NOMA in transmission section
Different users use the same frequency resources but are multiplexed in power domain.
Considering two users User 1 and User 2 in a cell, with the power allocation (PA) technique the
power of User 1 is superimposed to the power of User 2. The power of two users is different but
the frequency is same. Using equation (1), the transmitted signal X is calculated as the total of the
signal of User 1 multiplexed with √P1 and the signal of User 2 multiplexed with √P2.
3.2 Structure for Receiption
In transmission section of NOMA, signals emitted from the BS for each user are superimposed on
top of each other. More power is allocated to user located farther from the BS. In the network, all
users receive the same signal which contains the information for all users. Each user decodes the
strongest signal first and it decode from the received signal. The figure of receiver section is
given bellow.
Fig. 2.Block diagram of receiver section
3.3 Algorithm for NOMA based Appraoch
A general algorithm of NOMA based approach is shown below:
1. Choose total power and bandwidth for NOMA based system
2. Keep the bandwidth same for every users
3. Divide the total power into individual users using proposed scheme
User 2
SIC of
User 1
signal
User 2 signal
decoding
Base
Station
User 1
SIC of
User 2
signal
User 1 signal
decoding
User 2
User 1
PA
PA
Super
position
coding
Base
station

4
4. Assign larger power for far users
5. Calculate the transmit signal using superposition coding using individual signal and
individual powers
6. Transmit the signal through channel
4. CONVENTIONAL POWER ALLOCATION SCHEMES FOR NOMA
Different power allocation schemes for users are there for NOMA based wireless communication
system. In this section, we discussed two popular but simple conventional techniques.
4.1 Arbitrary Power Allocation Technique
In paper [4, 9], the total transmit power P is arbitrarily divided into users. P1 is chosen to be 20%
of total power for User1 and, P2 is 80% of the total power for the User2. However, it has no
explicit mechanism or explanation for choosing these specific powers for users. Therefore, if the
number of users are increased, the choice of power allocation will be complex.
4.2 Fractional Transmit Power Allocation (FTPA)
The total transmit power P is fractionally divided into users based on their corresponding channel
gain using fractional transmit power allocation [10, 15]. Based on the corresponding users
channel gains, the power allocation factors for two users are selected as a1 for User 1 and a2 for
User 2 where a1 <a2. Each user is loaded with power αP followed by superposition of all
constellation points. The power allocation factor is calculated using fairness index [11]. The
fairness index is optimized to be 0.7 arbitrarily. Therefore we concentrated on formulization of an
effective power allocation scheme for NOMA.
5. PROPOSED GENERALIZED POWER ALLOCATION (GPA) SCHEME FOR
NOMA
5.1 Formulation of GPA for NOMA
As power allocation is a crucial point for NOMA, we have proposed a simple general formula
which satisfies the power allocation requirement of NOMA. The equation of the proposed
Generalized Power Allocation (GPA) scheme is represented as
(3)
where C is termed as Choice Factor and is calculated as follows
(4)
Using the equation (3), the power of all individual users P1, P2, P3, ……, Pr have been allocated
where r=1,2,3……..n. The equation shows that the power allocation of all users cannot be same
which is the basic requirement of the NOMA system. The sum of the allocated power for
individual users must satisfy the following equation.
. (5)

5
5.2 Individual Power Calculation using Proposed GPA Scheme for NOMA
To verify equation (3) and (5), we have calculated individual power for 6 users. We have
considered total power P to be 100 watt. The calculated powers for 6 users with our proposed
scheme have been shown in Table 1 and Fig.3.
TABLE 1: POWER ALLOCATION FOR 6 USERS
Power
notation of
Users
Calculated
powers(watt)
Total
Power of 6
Users
P1 2
P2 7
P3 12
P4 20
P5 27
P6 31
P1
P2
P3
P4
P5
P6
0
5
10
15
20
25
30
35
User 1 User 2 User 3 User 4 User 5 User 6
Users
Power
in
watt
Fig. 3.Calculated power for 6 users with GPA scheme
The Table 1 and Fig.3 show that the power of individual user is not same, they are distinguishably
different with each other which is a prerequisite for NOMA power allocation. The power of users
from User1 to User6 is gradually increased which is needed for near user and far user. The near
user is needed small power than far user. The table also shows that the sum of individual user
power is approximately equal to the total power which also satisfies the equation (5). Therefore,
our formulated GPA scheme is simple and satisfies the basic prerequisites of power allocation for
NOMA.
6. RESULTS AND DISCUSSION
We have presented simulation results using MATLAB to verify our formulized GPA scheme and
compared the effectiveness of the proposed GPA schemes for NOMA with other schemes in this
section. We used synthetic input data and the method is simulated for 2 users. Additive White
Gaussian Noise (AWGN) channel is used. The individual power for 2 users has been calculated
with equation (3) using GPA scheme and compared with other schemes to validate the proposed
formula. The implementation system is designed to observe the BER performance of our
6
r=1
∑Pr ≈100

6
proposed GPA scheme in noisy environment and also to compare our scheme with conventional
other schemes.
6.1 Calculated Power Comparion of GPA Scheme with Other Schemes for NOMA
We have considered total power P to be 100 watt for all users. In the table, the number of user is
2 and their power is calculated by using different types of power allocation technique. We have
considered 20% of total power for User1 and 80% of total power for User2 for Arbitrary Power
Allocation scheme [9]. We have calculated the power of User 1 is α1*P watt and User 2 α2*P by
using the FTPA scheme [10]. Power allocation factor α1 for User1 is 0.17 and α2 for User2 is 0.82
and they are calculated by using fairness index 0.7 as of [11]. Finally we have calculated the
power by using our proposed GPA scheme. The calculated power for 2 different users with
different power allocation schemes have been shown in Table 2 and Fig.4.
TABLE2: CALCULATED POWER FOR 2 USERS USING DIFFERENT SCHEMES
Power
allocation
schemes
Power in Watt
(P1+P2) ≈
P
Power of
User 1, P1
Power of
User 2,
P2
Arbitrary
Power
Allocation
20 80 100
FTPA 17 82 99
GPA 18 81 99
Fig. 4.Calculated powers with different power allocation schemes of NOMA for 2 users
The Table 2 and Fig.4 show that the calculated power for both the users is almost similar for
different schemes. Therefore, we can say that our proposed scheme shows the similar result with
other schemes but our proposed GPA scheme is simple and there is no need to optimize any
arbitrary values for efficient calculation of power for different users.
6.2 Performance Comparion of GPA Scheme with Other Schemes for NOMA
The BER performance of proposed GPA scheme and two other conventional power allocation
schemes are simulated under implementation of convolutional channel coding techniques with

7
BPSK digital modulation technique. The results are presented and compared in Fig.5. It is
observed from the figure that GPA scheme shows a satisfactory BER performance and the
performance is similar with two other conventional power allocation schemes in the context of
BER.
Fig. 5.Performance comparison of proposed GPA scheme with other existing schemes using BPSK
modulation technique.
Fig. 6.Performance comparison of Proposed GPA scheme with other existing schemes using 4-QAM
modulation technique.
Fig.6 shows the BER performance with different power allocation schemes for NOMA using 4-
QAM modulation technique. In this figure, we observe that the GPA scheme shows similar BER
performance in case of 4-QAM digital modulation technique also. Therefore the proposed GPA
scheme shows consistent BER performance for different modulation techniques as well.
7. CONCLUSION AND FUTURE WORKS
Power allocation need to be effectively addressed for NOMA. In this paper, we have proposed a
Generalized Power Allocation (GPA) scheme which is simple but effective. GPA scheme does
not need to use any arbitrary value for power calculation of different users and the calculated

8
powers are distinguishably different for different users. We demonstrated by calculation and
simulation that GPA scheme satisfies the conditions and prerequisites of basic NOMA design.
The calculated total power using GPA scheme in NOMA based wireless communication system
shows only 01% variation than the arbitrary power calculation for multiple users. The simulation
results show that GPA scheme performs in a similar way to other conventional power allocation
schemes for NOMA. Therefore this simple GPA scheme is targeted to address the challenge of
power allocation in NOMA and can enhance its performance for future wireless communication.
Though the BER performance of GPA scheme is compatible with other conventional power
allocation schemes for NOMA, the overall BER performance is needed to be improved for future
wireless communication system. Therefore, our future target is to accomplish an effective BER
minimization technique for NOMA based wireless communication system.
ACKNOWLEDGEMENTS
This work has been done under the scholarship support of NST fellowship program of the
Ministry of Science and Technology, People’s Republic of Bangladesh and the work has been
conducted in the Communication Signal Processing Laboratory of the Department of Information
and Communication Engineering, University of Rajshahi, Bangladesh.
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AUTHORS
Tofail Ahmed is a lecturer in the Department of Information and Communication
Engineering, Bangladesh Army University of Engineering and Technology
(BAUET), Natore, Bangladesh. He earned his B.Sc.(Engg.) degree and M.Sc. (Engg.)
degree from University of Rajshahi, Bangladesh in 2015 and 2016 respectively. His
research interest is on wireless communication.
Rubaiyat Yasmin is serving as a Professor in the Department of Information and
Communication Engineering, University of Rajshahi, Bangladesh. She earned her
PhD degree from Saitama University, Japan in 2011. She did her M.Sc. from Waseda
University, Japan in 2005. She published a number of journal and conference papers
in her area. Her research area is Communication Signal Processing.
Halida Homyara is serving as an Associate Professor in the Department of
Information and Communication Engineering, University of Rajshahi, Bangladesh.
She earned her PhD degree from Chubu University, Japan in 2004. She did her M.Sc.
from University of Rajshahi, Bangladesh. She published a number of journal and
conference papers in her area.
M.A.F.M. Rashidul Hasan is serving as a Professor in the Department of
Information and Communication Engineering, University of Rajshahi, Bangladesh.
He earned his D.Engg. degree from Saitama University, Japan in 2012. He was a
visiting researcher in Waseda University, Japan from 2004 to 2005. He published a
number of journal and conference papers. His research area is Signal Processing.

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