The document discusses Non-orthogonal Multiple Access (NOMA) with Successive Interference Cancellation (SIC). It introduces NOMA and how it differs from Orthogonal Multiple Access. NOMA allows signals to be superimposed in the power domain and uses SIC at receivers. The document covers NOMA system models for downlink and uplink transmission, component technologies like power allocation and scheduling, performance evaluations that show higher throughput compared to OFDMA, and concludes that NOMA provides efficient spectrum usage and is compatible with technologies like MIMO and LTE.

1. Non-orthogonal Multiple Access with SIC
Short Discourse
Jiljo K Moncy
jkmoncy@caltech.edu
http://www.linkedin.com/in/jiljokmoncy
California Institute of Technology
Pasadena, CA
March 9, 2018
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2. Agenda
• Introduction
• Concept of NOMA
• System Model
• Downlink
• Uplink
• Component Technologies
• Power allocation
• Scheduling
• Receiver
• Multiple antennas
• Performance Evaluation
• Receiver test-bed
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3. Introduction
• Orthogonal Random
Access
• RA procedure
• Preamble collision
• Excessive Overhead
RA Procedure
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4. Concept of NOMA
Concept of NOMA [3]
• Signals superimposed in power domain
• Superimposed signal considered as interference
• SIC employed at user with higher SINR
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5. Concept of NOMA
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6. NOMA Vs OMA
• OMA splits available BW
• NOMA uses different power for transmissions
Spectrum Usage [2]
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7. System Model
Downlink
Transmission
• Each sub-band caters multiple users
• Scheduling to determine multiplicity
• Transmission power assigned to users
• Cell centered users have smaller power allocation than cell edge
users
x =
m
k=1
Pk sk (1)
Pk = βk
PBS
NSB
(2)
Downlink: Resource allocation [3]
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8. System Model
Downlink
Reception
• Assumption: Users in descending SINR order
• SIC performed at usern to remove intra cell interference
• Cell centered users have more SIC stages than cell edge users
• SIC performed in ascending SINR order
yn = hn
N
k=1
sk Pk + In + nn (3)
yn =
Desired signal
hn sn Pn + hn
N
k=n+1
sk Pk
Removed by SIC
+
Intra cell interfernce
hn
n−1
k=1
sk Pk +In + nn (4)
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9. System Model
Uplink
Signals from cell centered users are decoded prior to other users
Uplink SIC [2]
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10. Component Technologies
• Multi-user transmission power allocation
• Scheduling algorithm
• Receiver design
• Combination with multiple antennas
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11. Multi-user transmission power
Post-processing SINR of usern after SIC,
SINRPost
n =
βn
n−1
k=1 βk + 1
SINRn
(5)
SINRn = |hn|2 PBS
NSBPI+N
(6)
• Power assignment ratios control the user throughput
• [3] proposes allocation by maximizing geometric mean user
throughput
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12. Power allocation
Maximizing geometrical mean user throughput
Choose {β∗
1 , β∗
2 , ...} such that geometric mean of user throughput is
maximized
{β∗
1 , β∗
2 , ...β∗
N} = argmax
{β∗
1
,β∗
2
,...β∗
N
}
N
N
n=1
SEn (7)
Spectral efficiency of usern,
SEn = SEMCS∗
n 1 − BLERMCS∗
n
SINRPost
n
(8)
where,
MCS∗
= arg max
{MCS}
SEMCS
n 1 − BLERMCS
n
SINRPost
n
(9)
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13. Power allocation
Algorithms
Computational complexity increases exponentially with users
Other algorithms proposed:
• Allocation proportional to pathloss
• Allocation with limited power assignment ratio sets
• Tree-search based low complexity algorithm
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14. Scheduling algorithm
Determine the best user set
User set cardinality
M
1
+
M
2
+ .... +
M
Nmax
(10)
Example:
• Maximize proportional fairness
• Trade off between total throughput and minimal level of user
service.
• SINRPost
calculated for all sets
• Metric:
Λψj
=
n ψj
1 +
rk,n(t)
(tc − 1)Rn(t)
(11)
ψoptimal
= arg max
ψj
(Λψj
) (12)
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15. Receiver design
Two kinds of receiver
1 Symbol-level SIC receiver
2 Codeword-level SIC
Receiver Design [3]
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16. Multiple Antennas
• MIMO exploits spatial domain
• NOMA exploits power domain
Two modes:
SU-MIMO
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17. Multiple Antennas
• MIMO exploits spatial domain
• NOMA exploits power domain
Two modes:
MU-MIMO
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18. Performance Evaluation
Link-level
Performance comparison of different receivers [3]
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19. Performance Evaluation
System-level
Cummulative throughput of downlink
user throughput [2] Downlink total user throughput [2]
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20. Performance Evaluation
System-level
Performance comparison: NOMA Vs OFDMA [3]
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21. Experimental Trial
NOMA test bed [1]
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22. Conclusion
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23. Conclusion
1 Efficient spectrum usage & higher throughput
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24. Conclusion
1 Efficient spectrum usage & higher throughput
2 Robust performance gain in high-mobility scenarios
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25. Conclusion
1 Efficient spectrum usage & higher throughput
2 Robust performance gain in high-mobility scenarios
3 Compatible with OFDMA (thus LTE)
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26. Conclusion
1 Efficient spectrum usage & higher throughput
2 Robust performance gain in high-mobility scenarios
3 Compatible with OFDMA (thus LTE)
4 Compatible with beamforming and multi-antenna
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27. Conclusion
1 Efficient spectrum usage & higher throughput
2 Robust performance gain in high-mobility scenarios
3 Compatible with OFDMA (thus LTE)
4 Compatible with beamforming and multi-antenna
5 Avoids collision and overload
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28. Conclusion
1 Efficient spectrum usage & higher throughput
2 Robust performance gain in high-mobility scenarios
3 Compatible with OFDMA (thus LTE)
4 Compatible with beamforming and multi-antenna
5 Avoids collision and overload
6 Random access procedures eliminated
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29. References
A. Benjebbour, K. Saito, A. Li, Y. Kishiyama, and T. Nakamura, “Non-orthogonal multiple
access (noma): Concept, performance evaluation and experimental trials,” in Wireless
Networks and Mobile Communications (WINCOM), 2015 International Conference on,
pp. 1–6, IEEE, 2015.
K. Higuchi and A. Benjebbour, “Non-orthogonal multiple access (noma) with successive
interference cancellation for future radio access,” IEICE Transactions on Communications,
vol. 98, no. 3, pp. 403–414, 2015.
L. Anxin, L. Yang, C. Xiaohang, and J. Huiling, “Non-orthogonal multiple access (noma) for
future downlink radio access of 5g,” China Communications, vol. 12, no. Supplement,
pp. 28–37, 2015.
M. Shirvanimoghaddam, M. Dohler, and S. J. Johnson, “Massive non-orthogonal multiple
access for cellular iot: Potentials and limitations,” IEEE Communications Magazine, vol. 55,
no. 9, pp. 55–61, 2017.
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