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Power Efficient IRS-Assisted NOMA | IEEE Journals & Magazine | IEEE Xplore

Abstract:

In this paper, we propose a downlink multiple-input single-output (MISO) transmission scheme, which is assisted by an intelligent reflecting surface (IRS) consisting of a...Show More

Abstract:

In this paper, we propose a downlink multiple-input single-output (MISO) transmission scheme, which is assisted by an intelligent reflecting surface (IRS) consisting of a large number of passive reflecting elements. In the literature, it has been proved that nonorthogonal multiple access (NOMA) can achieve the same performance as computationally complex dirty paper coding, where the quasi-degradation condition is satisfied, conditioned on the users’ channels fall in the quasi-degradation region. However, in a conventional communication scenario, it is difficult to guarantee the quasi-degradation, because the channels are determined by the propagation environments and cannot be reconfigured. To overcome this difficulty, we focus on an IRS-assisted MISO NOMA system, where the wireless channels can be effectively tuned. We optimize the beamforming vectors and the IRS phase shift matrix for minimizing transmission power. Furthermore, we propose an improved quasi-degradation condition by using IRS, which can ensure that NOMA achieves the capacity region with high possibility. For a comparison, we study zero-forcing beamforming (ZFBF) as well, where the beamforming vectors and the IRS phase shift matrix are also jointly optimized. Comparing NOMA with ZFBF, it is shown that, with the same IRS phase shift matrix and the improved quasi-degradation condition, NOMA always outperforms ZFBF. At the same time, we identify the condition under which ZFBF outperforms NOMA, which motivates the proposed hybrid NOMA transmission. Simulation results show that the proposed IRS-assisted MISO system outperforms the MISO case without IRS, and the hybrid NOMA transmission scheme always achieves better performance than orthogonal multiple access.
Published in: IEEE Transactions on Communications ( Volume: 69, Issue: 2, February 2021)
Page(s): 900 - 913
Date of Publication: 26 October 2020

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I. Introduction

In the beyond fifth generation (B5G) communication systems, there are high requirements in spectrum efficiency, energy consumption, and massive connectivity [1]. In order to meet these high demands, various technologies, such as massive multiple-input multiple-output (MIMO), millimeter wave, and small cell, are being investigated for the B5G communication systems. In addition, nonorthogonal multiple access (NOMA) has also been introduced as a promising multiple access candidate for future mobile networks [2], [3]. Different from the conventional multiple access scheme, i.e., orthogonal multiple access (OMA), NOMA allows multiple users sharing the same resources, such as time, frequency, space, and code, and hence significantly improves the spectrum efficiency [4]–[6].

Select All
1.
K. David and H. Berndt, "6G vision and requirements: Is there any need for beyond 5G?", IEEE Veh. Technol. Mag., vol. 13, no. 3, pp. 72-80, Sep. 2018.
2.
L. Dai, B. Wang, Y. Yuan, S. Han, I. Chih-lin and Z. Wang, "Non-orthogonal multiple access for 5G: Solutions challenges opportunities and future research trends", IEEE Commun. Mag., vol. 53, no. 9, pp. 74-81, Sep. 2015.
3.
L. Dai, B. Wang, Z. Ding, Z. Wang, S. Chen and L. Hanzo, "A survey of non-orthogonal multiple access for 5G", IEEE Commun. Surveys Tuts., vol. 20, no. 3, pp. 2294-2323, 3rd Quart. 2018.
4.
J. Zhu, J. Wang, Y. Huang, S. He, X. You and L. Yang, "On optimal power allocation for downlink non-orthogonal multiple access systems", IEEE J. Sel. Areas Commun., vol. 35, no. 12, pp. 2744-2757, Dec. 2017.
5.
Z. Ding et al., "Application of non-orthogonal multiple access in LTE and 5G networks", IEEE Commun. Mag., vol. 55, no. 2, pp. 185-191, Feb. 2017.
6.
Z. Ding, M. Peng and H. V. Poor, "Cooperative non-orthogonal multiple access in 5G systems", IEEE Commun. Lett., vol. 19, no. 8, pp. 1462-1465, Aug. 2015.
7.
Y. Liu, H. Xing, C. Pan, A. Nallanathan, M. Elkashlan and L. Hanzo, "Multiple-antenna-assisted non-orthogonal multiple access", IEEE Wireless Commun., vol. 25, no. 2, pp. 17-23, Apr. 2018.
8.
Z. Ding, F. Adachi and H. V. Poor, "The application of MIMO to non-orthogonal multiple access", IEEE Trans. Wireless Commun., vol. 15, no. 1, pp. 537-552, Jan. 2016.
9.
Z. Chen, Z. Ding, X. Dai and G. K. Karagiannidis, "On the application of quasi-degradation to MISO-NOMA downlink", IEEE Trans. Signal Process., vol. 64, no. 23, pp. 6174-6189, Dec. 2016.
10.
W. Tang et al., "Wireless communications with programmable metasurface: New paradigms opportunities and challenges on transceiver design", IEEE Wireless Commun., vol. 27, no. 2, pp. 180-187, Apr. 2020.
11.
W. Tang et al., "Wireless communications with reconfigurable intelligent surface: Path loss modeling and experimental measurement" in arXiv:1911.05326, 2019, [online] Available: http://arxiv.org/abs/1911.05326.
12.
Q. Wu and R. Zhang, "Towards smart and reconfigurable environment: Intelligent reflecting surface aided wireless network", IEEE Commun. Mag., vol. 58, no. 1, pp. 106-112, Jan. 2020.
13.
X. Yu, D. Xu, Y. Sun, D. W. K. Ng and R. Schober, "Robust and secure wireless communications via intelligent reflecting surfaces", IEEE J. Sel. Areas Commun., Jul. 2020.
14.
Q. Wu and R. Zhang, "Intelligent reflecting surface enhanced wireless network: Joint active and passive beamforming design", Proc. IEEE Global Commun. Conf. (GLOBECOM), pp. 1-6, Dec. 2018.
15.
D. Xu, X. Yu, Y. Sun, D. W. K. Ng and R. Schober, "Resource allocation for secure IRS-assisted multiuser MISO systems", Proc. IEEE Globecom Workshops (GC Wkshps), pp. 1-6, Dec. 2019.
16.
Q. Wu and R. Zhang, "Beamforming optimization for wireless network aided by intelligent reflecting surface with discrete phase shifts", IEEE Trans. Commun., vol. 68, no. 3, pp. 1838-1851, Mar. 2020.
17.
M. Fu, Y. Zhou and Y. Shi, "Intelligent reflecting surface for downlink non-orthogonal multiple access networks", Proc. IEEE Globecom Workshops (GC Wkshps), pp. 1-6, Dec. 2019.
18.
Z. Ding and H. Vincent Poor, "A simple design of IRS-NOMA transmission", IEEE Commun. Lett., vol. 24, no. 5, pp. 1119-1123, May 2020.
19.
X. Mu, Y. Liu, L. Guo, J. Lin and N. Al-Dhahir, "Exploiting intelligent reflecting surfaces in multi-antenna aided NOMA systems" in arXiv:1910.13636, 2019, [online] Available: http://arxiv.org/abs/1910.13636.
20.
B. Zheng, Q. Wu and R. Zhang, "Intelligent reflecting surface-assisted multiple access with user pairing: NOMA or OMA?", IEEE Commun. Lett., vol. 24, no. 4, pp. 753-757, Apr. 2020.
21.
Y. Li, M. Jiang, Q. Zhang and J. Qin, "Joint beamforming design in multi-cluster MISO NOMA intelligent reflecting surface-aided downlink communication networks" in arXiv:1909.06972, 2019, [online] Available: http://arxiv.org/abs/1909.06972.
22.
J. Zhu, J. Wang, Y. Huang, K. Navaie, Z. Ding and L. Yang, "On optimal beamforming design for downlink MISO NOMA systems", IEEE Trans. Veh. Technol., vol. 69, no. 3, pp. 3008-3020, Mar. 2020.
23.
H. Weingarten, Y. Steinberg and S. S. Shamai (Shitz), "The capacity region of the Gaussian multiple-input multiple-output broadcast channel", IEEE Trans. Inf. Theory, vol. 52, no. 9, pp. 3936-3964, Sep. 2006.
24.
Z. Chen, Z. Ding, P. Xu and X. Dai, "Optimal precoding for a QoS optimization problem in two-user MISO-NOMA downlink", IEEE Commun. Lett., vol. 20, no. 6, pp. 1263-1266, Jun. 2016.
25.
T. Hou, Y. Liu, Z. Song, X. Sun, Y. Chen and L. Hanzo, "Reconfigurable intelligent surface aided NOMA networks", IEEE J. Sel. Areas Commun., Jul. 2020.
26.
A. Taha, M. Alrabeiah and A. Alkhateeb, "Enabling large intelligent surfaces with compressive sensing and deep learning" in arXiv:1904.10136, 2019, [online] Available: http://arxiv.org/abs/1904.10136.
27.
Y. Yang, B. Zheng, S. Zhang and R. Zhang, "Intelligent reflecting surface meets OFDM: Protocol design and rate maximization", IEEE Trans. Commun., vol. 68, no. 7, pp. 4522-4535, Jul. 2020.
28.
M. Di Renzo et al., "Smart radio environments empowered by AI reconfigurable meta-surfaces: An idea whose time has come" in arXiv:1903.08925, 2019, [online] Available: http://arxiv.org/abs/1903.08925.
29.
K. Shen and W. Yu, "Fractional programming for communication systems—Part I: Power control and beamforming", IEEE Trans. Signal Process., vol. 66, no. 10, pp. 2616-2630, May 2018.
30.
Z.-Q. Luo, W.-K. Ma, A. M.-C. So, Y. Ye and S. Zhang, "Semidefinite relaxation of quadratic optimization problems", IEEE Signal Process. Mag., vol. 27, no. 3, pp. 20-34, May 2010.

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