Joint User Clustering and Passive Beamforming for Downlink NOMA System with Reconfigurable Intelligent Surface

Reconfigurable intelligent surface (RIS) is an emerging technology to achieve energy-efficient wireless communication. This technology has the potential of turning the wireless environment, which is highly probabilistic in nature, into a programmable and partially deterministic space. This paper focuses on the joint user clustering, passive beamforming and power allocation for the downlink RIS-assisted nonorthogonal-multiple-access (NOMA) system, with the target of maximizing energy efficiency. This is an optimization problem which is solved by optimizing three sub-problems iteratively. In particular, user clustering sub-problem is solved with a matching algorithm, power allocation sub-problem is solved with the difference of two convex functions (DC) programming, and passive beamforming sub-problem is solved with univariate search technique. Simulation results demonstrate that the downlink RIS-assisted NOMA system can improve the energy efficiency by 7.8%-23.1%, compared with NOMA system without RIS and traditional orthogonal-multiple-access (OMA) system without RIS.

[1]  Qingqing Wu,et al.  Beamforming Optimization for Intelligent Reflecting Surface with Discrete Phase Shifts , 2018, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[2]  Jiaru Lin,et al.  Exploiting Intelligent Reflecting Surfaces in Multi-Antenna Aided NOMA Systems. , 2019, 1910.13636.

[3]  Victor C. M. Leung,et al.  Energy-Efficient Resource Allocation for Downlink Non-Orthogonal Multiple Access Network , 2016, IEEE Transactions on Communications.

[4]  Qi Zhang,et al.  Relay Beamforming for Amplify-and-Forward Multi-Antenna Relay Networks with Energy Harvesting Constraint , 2014, IEEE Signal Processing Letters.

[5]  Sean Victor Hum,et al.  Reconfigurable Reflectarrays and Array Lenses for Dynamic Antenna Beam Control: A Review , 2013, IEEE Transactions on Antennas and Propagation.

[6]  Zhiguo Ding,et al.  A Simple Design of IRS-NOMA Transmission , 2019, IEEE Communications Letters.

[7]  Ming Chen,et al.  On the Optimality of Power Allocation for NOMA Downlinks With Individual QoS Constraints , 2017, IEEE Communications Letters.

[8]  Yuanming Shi,et al.  Intelligent Reflecting Surface for Downlink Non-Orthogonal Multiple Access Networks , 2019, 2019 IEEE Globecom Workshops (GC Wkshps).

[9]  Walid Saad,et al.  A Joint Learning and Communications Framework for Federated Learning Over Wireless Networks , 2021, IEEE Transactions on Wireless Communications.

[10]  Shi Jin,et al.  Large Intelligent Surface-Assisted Wireless Communication Exploiting Statistical CSI , 2018, IEEE Transactions on Vehicular Technology.

[11]  H. Vincent Poor,et al.  Energy-Efficient Wireless Communications With Distributed Reconfigurable Intelligent Surfaces , 2020, IEEE Transactions on Wireless Communications.

[12]  Suvra Sekhar Das,et al.  Power allocation in OFDM based NOMA systems: A DC programming approach , 2014, 2014 IEEE Globecom Workshops (GC Wkshps).

[13]  Pingzhi Fan,et al.  On the Performance of Non-Orthogonal Multiple Access in 5G Systems with Randomly Deployed Users , 2014, IEEE Signal Processing Letters.

[14]  Walid Saad,et al.  A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems , 2019, IEEE Network.

[15]  Ying-Chang Liang,et al.  Intelligent Reflecting Surface Assisted Non-Orthogonal Multiple Access , 2019, 2020 IEEE Wireless Communications and Networking Conference (WCNC).

[16]  Yoshihisa Kishiyama,et al.  Non-Orthogonal Access with Random Beamforming and Intra-Beam SIC for Cellular MIMO Downlink , 2013, 2013 IEEE 78th Vehicular Technology Conference (VTC Fall).