Joint Beamforming Design in Multi-Cluster MISO NOMA Reconfigurable Intelligent Surface-Aided Downlink Communication Networks

Li, Yiqing; Jiang, Miao; Zhang, Qi; Qin, Jiayin

doi:10.1109/tcomm.2020.3032695

Cited by 124 publications

(86 citation statements)

References 41 publications

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“…It was demonstrated that LIS can potentially reduce the total transmission power in NOMA systems. The authors in [32] considered an LIS-assisted multi-cluster multiple-input singleoutput (MISO) NOMA system. They proposed a mathematical framework in order to jointly optimize the beamforming vector at BS and the reflection coefficient vector at LIS.…”

Section: B Related Workmentioning

confidence: 99%

Large Intelligent Surface-Assisted Nonorthogonal Multiple Access for 6G Networks: Performance Analysis

Bariah

Muhaidat

Sofotasios

et al. 2021

IEEE Internet Things J.

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Large intelligent surface (LIS) has recently emerged as a potential enabling technology for 6G networks, offering extended coverage and enhanced energy and spectral efficiency. In this work, motivated by its promising potentials, we investigate the error rate performance of LIS-assisted non-orthogonal multiple access (NOMA) networks. Specifically, we consider a downlink NOMA system, in which data transmission between a base station (BS) and L NOMA users is assisted by an LIS comprising M reflective elements. First, we derive the probability density function of the end-to-end wireless fading channels between the BS and NOMA users. Then, by leveraging the obtained results, we derive an approximate expression for the pairwise error probability (PEP) of NOMA users under the assumption of imperfect successive interference cancellation. Furthermore, accurate expressions for the PEP for M = 1 and large M values (M > 10) are presented in closed-form. To gain further insights into the system performance, an asymptotic expression for the PEP in high signal-to-noise ratio regime, the asymptotic diversity order, and a tight union bound on the bit error rate are provided. Finally, numerical and simulation results are presented to validate the derived mathematical results. Index terms-Asymptotic diversity order, bit error rate, large intelligent surfaces, NOMA, pairwise error probability, union bound, 6G.

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Section: B Related Workmentioning

confidence: 99%

Large Intelligent Surface-Assisted Nonorthogonal Multiple Access for 6G Networks: Performance Analysis

Bariah

Muhaidat

Sofotasios

et al. 2021

IEEE Internet Things J.

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“…In this paper, we focus on the design of beamforming vectors and the IRS phase shift matrix for an IRS-assisted multiple-input single-output (MISO) NOMA communication system. Among the existing works, there is a few similar works, e.g., [17]- [21], investigating the application of IRS in NOMA systems. In [17], the authors optimized the beamforming vectors and the IRS phase shift matrix for minimizing downlink transmission power in the IRS-empowered NOMA system.…”

Section: Introductionmentioning

confidence: 99%

“…[19] maximized the sum rate of all users by jointly optimizing the active beamforming at the BS and the passive beamforming at the IRS, where the ideal and non-ideal IRS assumptions are both studied. In a multi-cluster IRS-aided MISO NOMA communication network, [21] jointly optimized the beamforming vectors and the IRS element matrix for minimizing the transmission power. In [20], the authors discussed the comparison between IRS OMA and IRS NOMA.…”

Section: Introductionmentioning

confidence: 99%

Power Efficient IRS-Assisted NOMA

Zhu

Huang

Wang

et al. 2021

IEEE Trans. Commun.

160

126

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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 capacity region when the quasi-degradation condition is satisfied, which is characterized by users' channels. 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.

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“…The above-mentioned works [14]- [22] mainly studied the NOMA-MEC networks or the RIS assisted MEC networks. Since RIS can significantly enhance the system performance by reconfiguring the channel conditions and NOMA can be used to serve multiple users simultaneously at the same resource block [24]- [26], we consider to utilize RIS in the NOMA-MEC networks to further improve the energy efficiency. In this paper, we focus on an RIS-aided NOMA-MEC network where the direct links between users and the BS are in poor conditions and the RIS is used to guarantee the quality of service (QoS) requirements of MEC services.…”

Section: B Motivations and Contributionsmentioning

confidence: 99%

Energy Efficient Reconfigurable Intelligent Surface Enabled Mobile Edge Computing Networks With NOMA

Chen

Yang

et al. 2021

IEEE Trans. Cogn. Commun. Netw.

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Reconfigurable intelligent surface (RIS) has emerged as a promising technology for achieving high spectrum and energy efficiency in future wireless communication networks. In this paper, we investigate an RIS-aided single-cell multi-user mobile edge computing (MEC) system where an RIS is deployed to support the communication between a base station (BS) equipped with MEC servers and multiple single-antenna users. To utilize the scarce frequency resource efficiently, we assume that users communicate with BS based on a non-orthogonal multiple access (NOMA) protocol. Each user has a computation task which can be computed locally or partially/fully offloaded to the BS. We aim to minimize the sum energy consumption of all users by jointly optimizing the passive phase shifters, the size of transmission data, transmission rate, power control, transmission time and the decoding order. Since the resulting problem is non-convex, we use the block coordinate descent method to alternately optimize two separated subproblems. More specifically, we use the dual method to tackle a subproblem with given phase shift and obtain the closed-form solution; and then we utilize penalty method to solve another subproblem for given power control. Moreover, in order to demonstrate the effectiveness of our proposed algorithm, we propose three benchmark schemes: the time-division multiple access (TDMA)-MEC scheme, the full local computing scheme and the full offloading scheme. We use an alternating 1-D search method and the dual method that can solve the TDMA-based transmission problem well. Numerical results demonstrate that the proposed scheme can increase the energy efficiency and achieve significant performance gains over the three benchmark schemes.

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Joint Beamforming Design in Multi-Cluster MISO NOMA Reconfigurable Intelligent Surface-Aided Downlink Communication Networks

Cited by 124 publications

References 41 publications

Large Intelligent Surface-Assisted Nonorthogonal Multiple Access for 6G Networks: Performance Analysis

Large Intelligent Surface-Assisted Nonorthogonal Multiple Access for 6G Networks: Performance Analysis

Power Efficient IRS-Assisted NOMA

Energy Efficient Reconfigurable Intelligent Surface Enabled Mobile Edge Computing Networks With NOMA

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