noma as a candidate for 5G

1. Submitted By:-
Kanukanti Siddartha
19H51A0413
ECE TR-3
Supervisor:-
Dr.A.Pradeep kumar
Associate Professor
NOMA AS A
CANDIDATE FOR 5G
TECHNICAL SEMINAR-II
CMR COLLEGE OF ENGINEERING & TECHNOLOGY
(Autonomous)
(NAAC Accredited with ‘A+’ Grade & NBA Accredited)
(Approved by AICTE, Permanently Affiliated to JNTU Hyderabad)
KANDLAKOYA, MEDCHAL ROAD, HYDERABAD - 501401

2.  Introduction
 Technologies used in 5G
 Motivations of NOMA
 Working
 Far-User and Near-User Processing
 Capacity Comparisons
 Advantages
 Disadvantages
 Conclusion
 References
CONTENTS

3.  Demand for cellular mobile communications is increasing every
day.
Internet of things
Internet of vehicles
HD real-timevideo
Mobile gaming
Cloud Computing
Robots
 Requirements to solve the above use-cases
High energy efficiency
Lower latency
Higher reliability
High Availability
Faster speeds
INTRODUCTION

4.  Using millimeter waves (30 GHz – 300GHz)
 Small Cells
 Massive number of antennas per base station and devices
 Beamforming antenna patterns
 Non-Orthogonal Multiple Access
TECHNOLOGIES USED IN 5G

5. MOTIVATIONSOFNOMA
• Serve more than one user at the same time and frequency
resource
• Higher spectral efficiency (more data rate per Hz)
• Benefit from the geographical distribution ofusers
• Better serve cell edge users (users far from the base station)

6. • Consider two users’example
• The base station selects two appropriate users to pair
Near‐user (strong channel gain)
Far‐user (weak channel gain)
• Served at the same time and frequency.
• TxPower is split betweenthem
High power share toFar‐user
Low power share toNear‐user
Typically interference
should happen!!
WORKING
Fig: Two users served at same frequency
and time

7. • Far‐user signal has small interference from the Near‐user
signal
Far‐user decodes its signalnormally
Suffers from slight extrainterference
• Near‐user signal has large interference from Far‐user
Near‐user decodes Far‐user signalfirst
Subtracts this interference from the composite NOMA
signal
Hence, Far‐user interference is canceled.
Near‐user decodes its data from the cleaned signal
• Note that Far‐user is unable to cancel Near‐user
interference because it is too weak to be decoded
WORKING

8. FAR‐USERANDNEAR‐USER
PROCESSING
Far‐UserProcessing
Near‐User Processing

9. CAPACITYCOMPARISON
• In OMA each user takes half the bandwidth, but no interference
• OMA: SNRnear = Pnear
and SNRf a r =
P f a r
noise noise
• NOMA Near‐user can cancel Far‐user signal: SNRnear = Pnear
• NOMAFar‐user can't cancel Near‐user signal: SNRfar =
noise
P f a r
Pnear+noise

10. CAPACITYCOMPARISON
log + log bits/s
2 2
OMA
Pnear Pfar
W
C
noise noise
   

W
1 1
2   2  
   
2 2 bits/s
NOMA
near
Pnear Pfar
C +W log
noise
 
 
W log 1 1

  P  noise 
   
Pfar Pnear  Ptotal = constant

11. ADVANTAGES
 It offers higher spectral efficiency due to the use of
multiple users on the same frequency resource.
It offers massive connectivity by serving more uses
simultaneously at the same time.
It offers lower latency due to simultaneous transmission all
the time rather than a dedicated scheduled time slot.
It offers better QoS (Quality of Service) to all the users
using flexible power control algorithms. It helps in
increasing cell-edge throughput and better user experience
at cell edges.
The NOMA along with MIMO delivers enhanced performance.

12.  Each of the users within the cluster needs to decode the
information of all the other users even one having the worst
channel gains. This leads to complexity in the receiver.
Moreover, energy consumption is higher.
 In order to achieve desired functionalities of the power
domain concept in NOMA at the receiver, channel gain
difference between users should be adequate. This limits
the effective number of user pairs served by clusters.
DISADVANTAGES

13. CONCLUSION
• NOMA is based on sharing resources between users
• Sharing allows a higher sum data rate
• Can help increase the number of users and higher
data rate.
• Adopted as a candidate for 5G
• Considerable research is going on to put it into
practice

14. REFERENCES
[1] Y. Gao, J. Xu, W. Xu, D. W. K. Ng, and M.-S. Alouini, “Distributed
IRS with statistical passive beamforming for MISO
communications,” IEEE Wireless Commun. Lett., vol. 10, no. 2, pp.
221 – 225, Feb. 2021.
[2] A. Benjebbour, K. Saito, and Y. Kishiyama, “Experimental trials
on non-orthogonal multiple access,” in In Multiple Access
Techniques for 5G Wireless Networks and Beyond, pp. 587– 607,
Springer, 2019.
[3] X. Dai, Z. Zhang, B. Bai, S. Chen, and S. Sun, “Pattern division
multiple access: new multiple access technologies for 5G,” IEEE
Wireless Communications, vol. 25, no. 2, pp. 54– 60, 2018
[4] Y. Chen, A. Bayesteh, Y. Wu et al., “Toward the standardization
of non-orthogonal multiple access for next-generation wireless
networks,” IEEE Communications Magazine, vol. 56, no. 3, pp. 19–
27, 2018.