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Erschienen in:
Introduction to Cellular Mobile Communications Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

5. NOMA: An Information-Theoretic Perspective

verfasst von : Mojtaba Vaezi, H. Vincent Poor

Erschienen in: Multiple Access Techniques for 5G Wireless Networks and Beyond

Verlag: Springer International Publishing

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Abstract

Non-orthogonal multiple access (NOMA) is a potential enabler for the development of 5G and beyond wireless networks. By allowing multiple users to share the same resource (time/frequency/code/space), NOMA can scale up the number of served users, increase the spectral efficiency, and improve user-fairness compared to existing orthogonal multiple access (OMA) techniques. The basic premise behind NOMA in a single-cell network is to reap the benefits promised by information theory for the downlink and uplink transmission of wireless systems, modeled respectively by the broadcast channel (BC) and multiple access channel (MAC). The capacity regions of the BC and MAC have been established several decades ago, and concurrent non-orthogonal transmission is the optimal transmission strategy in both cases. Unlike the single-cell setting, the capacity region of multi-cell wireless networks, commonly modeled by the interference channel (IC), is in general unknown. However, it is known that OMA is suboptimal. This chapter reviews what information theory promises and proposes for NOMA in single- and multi-cell networks with both single- and multi-antenna nodes. Furthermore, relevant physical layer security channel models are proposed and discussed.

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Vorheriges Kapitel Generalized Frequency Division Multiplexing: A Flexible Multicarrier Waveform
Nächstes Kapitel Optimal Power Allocation for Downlink NOMA Systems
Fußnoten
1
We should highlight that in this chapter we are discussing non-orthogonal multiple access methods. This should not be confused with non-orthogonal random access which is another related topic and will be discussed in Chap. 17 of this book.
 
2
For example, CDMA with power control is capacity achieving for the single-antenna broadcast channel.
 
3
However, in the SDMA case, we assume that the system is overloaded. This is relevant in the MIMO (and MU-MIMO) case where “space” comes in as a new resource. We note that when the number of transmit antennas \(n_t\) is greater than the number of users K, different users can be served in different (orthogonal) spaces, reducing the underlying system to an OMA one.
 
4
Sparse code multiple access (SCMA) is an important variant of NOMA in the code domain.
 
5
FDMA has exactly the same performance [5].
 
6
Moore’s Law, hypothesized by Intel founder Gordon Moore in 1965, states that the number of transistors in a dense integrated circuit will double approximately every two years. This enables a larger number of transistors to be concentrated in a given area which, in turn, results in a faster processor that can operate at lower power.
 
7
In LTE one resource block is 180 kHz.
 
Literatur
1.
D. Tse, P. Viswanath, Fundamentals of Wireless Communication (Cambridge university press, 2005)
2.
Y. Saito, Y. Kishiyama, A. Benjebbour, T. Nakamura, A. Li, K. Higuchi, Non-orthogonal multiple access (NOMA) for cellular future radio access, in Proceedings of the 77th IEEE Vehicular Technology Conference (VTC Spring) (2013), pp. 1–5
3.
P. Wang, J. Xiao, P. Li, Comparison of orthogonal and non-orthogonal approaches to future wireless cellular systems. IEEE Veh. Technol. Mag. 1(3), 4–11 (2006)CrossRef
4.
T.M. Cover, J.A. Thomas, Elements of Information Theory (Wiley, New York, 2006)MATH
5.
A. El Gamal, Y.H. Kim, Network Information Theory (Cambridge University Press, 2011)
6.
T. Han, K. Kobayashi, A new achievable rate region for the interference channel. IEEE Trans. Inf. Theory 27, 49–60 (1981)MathSciNetCrossRef
7.
M. Vaezi, H.V. Poor, Simplified Han-Kobayashi region for one-sided and mixed Gaussian interference channels, in Proceedings of the IEEE International Conference on Communications (ICC) (2016), pp. 1–6
8.
9.
S.R. Islam, N. Avazov, O.A. Dobre, K.-S. Kwak, Power-domain non-orthogonal multiple access (NOMA) in 5G systems: potentials and challenges. IEEE Commun. Surv. Tutor. (2017)
10.
Z. Ding, Y. Liu, J. Choi, Q. Sun, M. Elkashlan, I. Chih-Lin, H.V. Poor, Application of non-orthogonal multiple access in LTE and 5G networks. IEEE Commun. Mag. 55(2), 185–191 (2017)CrossRef
11.
W. Shin, M. Vaezi, B. Lee, D.J. Love, J. Lee, H.V. Poor, Non-orthogonal multiple access in multi-cell networks: theory, performance, and practical challenges. IEEE Commun. Mag. 55(10), 176–183 (2017)CrossRef
12.
3GPP TD RP-150496, Study on Downlink Multiuser Superposition Transmission, Mar 2015
13.
Q. Sun, S. Han, C.-L. I, Z. Pan, On the ergodic capacity of MIMO NOMA systems. IEEE Wirel. Commun. Lett. 4(4), 405–408 (2015)
14.
Z. Ding, F. Adachi, H.V. Poor, The application of MIMO to non-orthogonal multiple access. IEEE Trans. Wirel. Commun. 15(1), 537–552 (2016)CrossRef
15.
Z. Ding, R. Schober, H.V. Poor, A general MIMO framework for NOMA downlink and uplink transmission based on signal alignment. IEEE Trans. Wirel. Commun. 15(6), 4438–4454 (2016)CrossRef
16.
R.H. Etkin, D.N. Tse, H. Wang, Gaussian interference channel capacity to within one bit. IEEE Trans. Inf. Theory 54(12), 5534–5562 (2008)MathSciNetCrossRef
17.
A.S. Motahari, A.K. Khandani, Capacity bounds for the Gaussian interference channel. IEEE Trans. Inf. Theory 55(2), 620–643 (2009)MathSciNetCrossRef
18.
X. Shang, G. Kramer, B. Chen, A new outer bound and the noisy-interference sum-rate capacity for Gaussian interference channels. IEEE Trans. Inf. Theory 55(2), 689–699 (2009)MathSciNetCrossRef
19.
V.S. Annapureddy, V.V. Veeravalli, Gaussian interference networks: sum capacity in the low-interference regime and new outer bounds on the capacity region. IEEE Trans. Inf. Theory 55(7), 3032–3050 (2009)MathSciNetCrossRef
20.
M. Vaezi, H.V. Poor, On limiting expressions for the capacity regions of Gaussian interference channels, in Proceedings of the 49th Asilomar Conference on Signals, Systems and Computers, Nov (2015), pp. 1292–1298
21.
22.
H. Weingarten, Y. Steinberg, S.S. Shamai, The capacity region of the Gaussian multiple-input multiple-output broadcast channel. IEEE Trans. Inf. Theory 52(9), 3936–3964 (2006)MathSciNetCrossRef
23.
24.
V.O.L. Yijie Mao, B. Clerckx, Rate-splitting multiple access for downlink communication systems: bridging, generalizing and outperforming SDMA and NOMA, arXiv:​1710.​11018v3
25.
M.A. Maddah-Ali, A.S. Motahari, A.K. Khandani, Signaling over MIMO multi-base systems: combination of multi-access and broadcast schemes, in Proceedings of the IEEE International Symposium on Information Theory (2006), pp. 2104–2108
26.
M.A. Maddah-Ali, A.S. Motahari, A.K. Khandani, Communication over MIMO X channels: interference alignment, decomposition, and performance analysis. IEEE Trans. Inf. Theory 54(8), 3457–3470 (2008)MathSciNetCrossRef
27.
V.R. Cadambe, S.A. Jafar, Interference alignment and degrees of freedom of the \(K\)-user interference channel. IEEE Trans. Inf. Theory 54(8), 3425–3441 (2008)MathSciNetCrossRef
28.
C.M. Yetis, T. Gou, S.A. Jafar, A.H. Kayran, On feasibility of interference alignment in MIMO interference networks. IEEE Trans. Signal Process. 58(9), 4771–4782 (2010)MathSciNetCrossRef
29.
T. Gou, S.A. Jafar, Degrees of freedom of the K user \(M\,\times \,N\) MIMO interference channel. IEEE Trans. Inf. Theory 56(12), 6040–6057 (2010)MathSciNetCrossRef
30.
3GPP TR 36.866 V12.0.1, Study on Network-Assisted Interference Cancellation and Suppression (NAIC) for LTE (Release 12), Mar 2014
31.
Q. Li, G. Li, W. Lee, M.-i. Lee, D. Mazzarese, B. Clerckx, Z. Li, MIMO techniques in WiMAX and LTE: a feature overview. IEEE Commun. Mag. 48(5), (2010)
32.
Y. Yuan, Z. Yuan, G. Yu, C.-H. Hwang, P.-K. Liao, A. Li, K. Takeda, Non-orthogonal transmission technology in LTE evolution. IEEE Commun. Mag. 54(7), 68–74 (2016)CrossRef
33.
D. Lee, H. Seo, B. Clerckx, E. Hardouin, D. Mazzarese, S. Nagata, K. Sayana, Coordinated multipoint transmission and reception in LTE-advanced: deployment scenarios and operational challenges. IEEE Commun. Mag. 50(2), 148–155 (2012)CrossRef
34.
W. Shin, M. Vaezi, B. Lee, D.J. Love, J. Lee, H.V. Poor, Coordinated beamforming for multi-cell MIMO-NOMA. IEEE Commun. Lett. 21(1), 84–87 (2017)CrossRef
35.
E. Ekrem, S. Ulukus, The secrecy capacity region of the Gaussian MIMO multi-receiver wiretap channel. IEEE Trans. Inf. Theory 57(4), 2083–2114 (2011)MathSciNetCrossRef
36.
R. Liu, T. Liu, H.V. Poor, S. Shamai, Multiple-input multiple-output Gaussian broadcast channels with confidential messages. IEEE Trans. Inf. Theory 56(9), 4215–4227 (2010)MathSciNetCrossRef
37.
K. Wang, X. Wang, X. Zhang, SLNR-based transmit beamforming for MIMO wiretap channel. Wirel. Pers. Commun. 71(1), 109–121 (2013)CrossRef
38.
S.A.A. Fakoorian, A.L. Swindlehurst, Optimal power allocation for GSVD-based beamforming in the MIMO Gaussian wiretap channel, in Proceedings of the IEEE International Symposium on Information Theory (2012), pp. 2321–2325
39.
A. Khisti, G.W. Wornell, Secure transmission with multiple antennas I: the MISOME wiretap channel. IEEE Trans. Inf. Theory 56(7), 3088–3104 (2010)
40.
W. Mei, Z. Chen, J. Fang, GSVD-based precoding in MIMO systems with integrated services. IEEE Signal Process. Lett. 23(11), 1528–1532 (2016)CrossRef
41.
M. Vaezi, W. Shin, V. Poor, Optimal beamforming for Gaussian MIMO wiretap channels with two transmit antennas. IEEE Trans. Wirel. Commun. 16, 6726–6735 (2017)CrossRef
42.
R. Liu, H.V. Poor, Secrecy capacity region of a multiple-antenna Gaussian broadcast channel with confidential messages. IEEE Trans. Inf. Theory 55(3), 1235–1249 (2009)MathSciNetCrossRef
43.
R. Bustin, R. Liu, H. V. Poor, S. Shamai, An MMSE approach to the secrecy capacity of the MIMO Gaussian wiretap channel. EURASIP J. Wirel. Commun. Netw. (1) (2009)
44.
M. Vaezi, W. Shin, H. V. Poor, J. Lee, MIMO Gaussian wiretap channels with two transmit antennas: optimal precoding and power allocation, in Proceedings of the IEEE International Symposium on Information Theory (2017), pp. 1708–1712
45.
Q. Li, W.-K. Ma, Optimal and robust transmit designs for MISO channel secrecy by semidefinite programming. IEEE Trans. Signal Process. 59(8), 3799–3812 (2011)MathSciNetCrossRef
46.
Q. Li, M. Hong, H.-T. Wai, Y.-F. Liu, W.-K. Ma, Z.-Q. Luo, Transmit solutions for MIMO wiretap channels using alternating optimization. IEEE J. Sel. Areas Commun. 31(9), 1714–1727 (2013)CrossRef
47.
S. Goel, R. Negi, Guaranteeing secrecy using artificial noise. IEEE Trans. Wirel. Commun. 7(6), 2180–2189 (2008)
48.
Z. Li, P. Mu, B. Wang, X. Hu, Optimal semiadaptive transmission with artificial-noise-aided beamforming in MISO wiretap channels. IEEE Trans. Veh. Technol. 65(9), 7021–7035 (2016)CrossRef
49.
T.-X. Zheng, H.-M. Wang, J. Yuan, D. Towsley, M.H. Lee, Multi-antenna transmission with artificial noise against randomly distributed eavesdroppers. IEEE Trans. Commun. 63(11), 4347–4362 (2015)CrossRef
50.
S. Gerbracht, C. Scheunert, E.A. Jorswieck, Secrecy outage in MISO systems with partial channel information. IEEE Trans. Inf. Forensics Secur. 7(2), 704–716 (2012)CrossRef
Metadaten
Titel
NOMA: An Information-Theoretic Perspective
verfasst von
Mojtaba Vaezi
H. Vincent Poor
Copyright-Jahr
2019
Buch
Multiple Access Techniques for 5G Wireless Networks and Beyond

Print ISBN: 978-3-319-92089-4

Electronic ISBN: 978-3-319-92090-0

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-319-92090-0_5