Active and Passive Beamforming Design for Reconfigurable Intelligent Surface Assisted CR-NOMA Networks

Authors: Liang, W., Luo, W., Zhang, J. and Ding, Z.

Journal: IEEE Communications Letters

Volume: 26

Issue: 10

Pages: 2409-2414

eISSN: 1558-2558

ISSN: 1089-7798

DOI: 10.1109/LCOMM.2022.3194116

Abstract:

In this letter, a underlay cognitive radio inspired non-orthogonal multiple access (CR-NOMA) network assisted by the reconfigurable intelligent surface (RIS) technique is conceived to maximize the energy efficiency (EE), while all the cognitive users (CUs) are located in the 'dead zone'. In particular, the CUs could only receive the information from the cognitive base station (CBS) via RIS. The EE maximization optimization problem which is a non-convex problem has been constructed to realize joint beamforming design at both the CBS and RIS with the constraints of the primary user's (PU) interference power restriction and the CUs' rate fairness. Moreover, we propose the alternating pragmatic iterative algorithm (APIA) to optimize the non-convex optimization problem until the final value of EE converges. Based on the simulation results, our proposed algorithm attains the significant gain than the two benchmarks of the random phase scheme as well as the fixed phase scheme on the RIS.

https://eprints.bournemouth.ac.uk/37364/

Source: Scopus

12mm Active and Passive Beamforming Design for Reconfigurable Intelligent Surface Assisted CR-NOMA Networks

Authors: Liang, W., Luo, W., Zhang, J. and Ding, Z.

Journal: IEEE Communications Letters

ISSN: 1089-7798

Abstract:

In this paper, a underlay cognitive radio inspired non-orthogonal multiple access (CR-NOMA) network assisted by the reconfigurable intelligent surface (RIS) technique is conceived to maximize the energy efficiency (EE), while all the cognitive users (CUs) are located in the “dead zone". In particular, the CUs could only receive the information from the cognitive base station (CBS) via RIS. The EE maximization optimization problem which is a non-convex problem has been constructed to realize joint beamforming design at both the CBS and RIS with the constraints of the primary user’s (PU) interference power restriction and the CUs’ rate fairness. Moreover, we propose the alternating pragmatic iterative algorithm (APIA) to optimize the non-convex optimization problem until the final value of EE converges. Based on the simulation results, our proposed algorithm attains the significant gain than the two benchmarks of the random phase scheme as well as the fixed phase scheme on the RIS.

https://eprints.bournemouth.ac.uk/37364/

Source: BURO EPrints