Joint Optimization of Beamforming, Phase-Shifting and Power Allocation in a Multi-Cluster IRS-NOMA Network | IEEE Journals & Magazine | IEEE Xplore

Joint Optimization of Beamforming, Phase-Shifting and Power Allocation in a Multi-Cluster IRS-NOMA Network


Abstract:

The combination of non-orthogonal multiple access (NOMA) and intelligent reflecting surface (IRS) is an efficient solution to significantly enhance the energy efficiency ...Show More

Abstract:

The combination of non-orthogonal multiple access (NOMA) and intelligent reflecting surface (IRS) is an efficient solution to significantly enhance the energy efficiency of the wireless communication system. In this paper, a downlink multi-cluster NOMA network is considered, where each cluster is supported by one IRS. This paper aims to minimize the transmit power by jointly optimizing the beamforming, the power allocation and the phase shift of each IRS. The formulated problem is non-convex and challenging to be solved due to the coupled variables, i.e., the beamforming vector, the power allocation coefficient and the phase shift matrix. To address this non-convex problem, an alternating optimization based algorithm is proposed. Specifically, the primal problem is divided into two subproblems for beamforming optimization and phase shifting feasiblity, where the two subproblems are solved iteratively. Moreover, to guarantee the feasibility of the beamforming optimization problem, an iterative algorithm is proposed to search the feasible initial points. To reduce the complexity, a simplified algorithm based on partial exhaustive search for this system model is also proposed. Simulation results demonstrate that the proposed alternating algorithm can yield a better performance gain than the partial exhaustive search algorithm, NOMA with random IRS phase shift scheme and OMA-IRS scheme.
Published in: IEEE Transactions on Vehicular Technology ( Volume: 70, Issue: 8, August 2021)
Page(s): 7705 - 7717
Date of Publication: 17 June 2021

ISSN Information:

Funding Agency:

References is not available for this document.

I. Introduction

The 5 G communication system has been commercialized world-widely, and the beyond 5 G (B5G) system starts attracting more and more researchers’ attention due to its low energy consumption, high spectrum efficiency and massive multi-device interconnections [1]–[3]. In order to satisfy the increasing demand caused by the fast-growing number of users, various techniques, including millimetre wave [4], massive multi-inputs and multi-outputs (MIMO) system [5], and small cell [6], have been investigated and extensively used in practice. As a potential technique of B5G, non-orthogonal multiple access (NOMA) has received widespread attention due to its high spectral efficiency [7], [8]. Different from conventional orthogonal multiply access (OMA), such as frequency division multiple access (FDMA), time division multiple access (TDMA), code division multiple access (CDMA), and orthogonal frequency-division multiple access (OFDMA), NOMA allows multiple users to share the same time slot, frequency block and channel code, which dramatically increases the spectral efficiency. In particular, the users in a NOMA network usually adopt successive inference cancellation (SIC) to remove the inference from other NOMA users, which can efficiently improve the signal to interference and noise ratio (SINR) and reception reliability [9]. Recently, intelligent reflective surface (IRS) has also been proposed as a potential solution to further improve the performance of wireless networks, including enlarging the communication coverage, and improving transmission robustness. Specifically, the IRS can reflect the electromagnetic wave to extend the cover rage of the base station (BS). It also has the ability to tune the channel by adjusting the phase shift of each element, which will greatly improve the quality of users’ received signal [10]. The typical architecture of IRS consists of a reflecting panel and a smart controller. The reflecting panel is composed of many reflecting elements and a control circuit. The control circuit is responsible for tuning the phase shift of each reflecting element. Moreover, the smart controller determines the reflection adaptation and also performs as a gateway to communicate with the BS. The smart controller can receive the control signal from the BS and then adjust the phase shift of each reflecting element [11].

Select All
1.
Z. Zhang et al., "6G wireless networks: Vision requirements architecture and key technologies", IEEE Veh. Technol. Mag., vol. 14, no. 3, pp. 28-41, Sep. 2019.
2.
W. Saad, M. Bennis and M. Chen, "A vision of 6G wireless systems: Applications trends technologies and open research problems", IEEE Netw., vol. 34, no. 3, pp. 134-142, May/Jun. 2020.
3.
IEEE Wireless Commun., vol. 27, no. 4, pp. 118-125.
4.
V. Jamali, A. Tulino, G. Fischer, R. Müller and R. Schober, "Intelligent reflecting and transmitting surface aided millimeter wave massive MIMO".
5.
E. G. Larsson, O. Edfors, F. Tufvesson and T. L. Marzetta, "Massive MIMO for next generation wireless systems", IEEE Commun Mag, vol. 52, no. 2, pp. 186-195, Feb. 2014.
6.
Y. Guo, "Method and apparatus of small cell enhancement in a wireless communication system", vol. 295, pp. 77, Mar. 2016.
7.
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.
8.
M. Vaezi, Z. Ding and H. V. Poor, Multiple Access Techniques for 5G Wireless Networks and Beyond, Springer, 2019.
9.
K. Saito, A. Benjebbour, Y. Kishiyama, Y. Okumura and T. Nakamura, "Performance and design of SIC receiver for downlink NOMA with open-loop SU-MIMO", Proc. IEEE Int. Conf. Commun. Workshop, pp. 1161-1165, 2015.
10.
Q. Wu and R. Zhang, "Intelligent reflecting surface enhanced wireless network: Joint active and passive beamforming design", Proc. IEEE Glob. Commun. Conf., pp. 1-6, 2018.
11.
IEEE Trans. Commun., vol. 69, no. 5, pp. 3313-3351.
12.
X. Sun et al., "Joint beamforming and power allocation in downlink NOMA multiuser MIMO networks", IEEE Trans. Wireless Commun., vol. 17, no. 8, pp. 5367-5381, Aug. 2018.
13.
F. Fang, H. Zhang, J. Cheng, S. Roy and V. C. Leung, "Joint user scheduling and power allocation optimization for energy-efficient NOMA systems with imperfect CSI", IEEE J. Sel. Areas Commun., vol. 35, no. 12, pp. 2874-2885, Dec. 2017.
14.
G. Surabhi, R. M. Augustine and A. Chockalingam, "On the diversity of uncoded OTFS modulation in doubly-dispersive channels", IEEE Trans. Wirel. Commun., vol. 18, no. 6, pp. 3049-3063, Jun. 2019.
15.
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.
16.
F. Fang, H. Zhang, J. Cheng and V. C. Leung, "Energy-efficient resource allocation for downlink non-orthogonal multiple access network", IEEE Trans. Commun., vol. 64, no. 9, pp. 3722-3732, Sep. 2016.
17.
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.
18.
M. Di Renzo et al., "Smart radio environments empowered by reconfigurable AI meta-surfaces: An idea whose time has come", EURASIP J. Wirel. Commun. Netw., vol. 2019, no. 1, pp. 1-20, 2019.
19.
Q. Wu and R. Zhang, "Intelligent reflecting surface enhanced wireless network via joint active and passive beamforming", IEEE Trans. Wireless Commun., vol. 18, no. 11, pp. 5394-5409, Nov. 2019.
20.
W. Tang et al., "Wireless communications with reconfigurable intelligent surface: Path loss modeling and experimental measurement", IEEE Trans. Wireless Commun., vol. 20, no. 1, pp. 421-439.
21.
A. S. Sena et al., "What role do intelligent reflecting surfaces play in non-orthogonal multiple access", IEEE Wireless Commun. Mag, vol. 27, no. 5, pp. 24-31, Oct. 2020.
22.
F. Fang, Y. Xu, Q.-V. Pham and Z. Ding, "Energy-efficient design of IRS-NOMA networks", IEEE Trans. Veh. Technol, vol. 69, no. 11, pp. 14088-14092, Nov. 2020.
23.
J. Zhu, Y. Huang, J. Wang, K. Navaie and Z. Ding, "Power efficient IRS-assisted NOMA", IEEE Trans. Commun., vol. 69, no. 2, pp. 900-913.
24.
Z. Ding, R. Schober and H. V. Poor, "On the impact of phase shifting designs on IRS-NOMA", IEEE Wireless Commun. Lett., vol. 9, no. 10, pp. 1596-1600, Oct. 2020.
25.
IEEE Trans. Commun., vol. 69, no. 6, pp. 3802-3817.
26.
X. Liu, Y. Liu, Y. Chen and H. V. Poor, "RIS enhanced massive non-orthogonal multiple access networks: Deployment and passive beamforming design", IEEE J. Sel. Areas Commun., vol. 39, no. 4, pp. 1057-1071.
27.
X. Mu, Y. Liu, L. Guo, J. Lin and N. Al-Dhahir, "Exploiting intelligent reflecting surfaces in multi-antenna aided NOMA systems", 2019.
28.
J. Zuo, Y. Liu, Z. Qin and N. Al-Dhahir, "Resource allocation in intelligent reflecting surface assisted NOMA systems", IEEE Trans. Commun., vol. 68, no. 11, pp. 7170-7183.
29.
M. Zeng, X. Li, G. Li, W. Hao and O. Dobre, "Sum rate maximization for IRS-assisted uplink NOMA", IEEE Commun. Lett., vol. 25, no. 1, pp. 234-238.
30.
Y. Li, M. Jiang, Q. Zhang and J. Qin, "Joint beamforming design in multi-cluster MISO NOMA intelligent reflecting surface-aided downlink communication networks", 2019.

Contact IEEE to Subscribe

References

References is not available for this document.