Joint Power Control and Phase Shift Design for Future PD-NOMA IRS-Assisted Drone Communications under Imperfect SIC Decoding

• Published in: Sensors (Basel, Switzerland) Switzerland), 2022-11, Vol.22 (22), p.8603
• Main Authors: Aziz, Saddam, Irshad, Muhammad, Afef, Kallekh, Mohamed, Heba G, Alotaibi, Najm, Tarmissi, Khaled, Alnfiai, Mrim M, Hamza, Manar Ahmed
• Format: Article
• Language: English
• Subjects: Analysis; Approximation; Budgets; Channel capacity; Communications networks; Complex variables; drones; Efficiency; imperfect successive interference cancellation decoding; intelligent reflecting surfaces; Internet of Things; non-orthogonal multiple access; Nonorthogonal multiple access; Optimization; Phase shift; Power management; spectral efficiency optimization; Spectrum allocation; Tax administration and procedure; Urban areas; Wireless communications; Wireless networks
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s22228603

Intelligent reflecting surfaces (IRS) and power-domain non-orthogonal multiple access (PD-NOMA) have recently gained significant attention for enhancing the performance of next-generation wireless communications networks. More specifically, IRS can smartly reconfigure the incident signal of the source towards the destination node, extending the wireless coverage and improving the channel capacity without consuming additional energy. On the other side, PD-NOMA can enhance the number of devices in the network without using extra spectrum resources. This paper proposes a new optimization framework for IRS-enhanced NOMA communications where multiple drones transmit data to the ground Internet of Things (IoT) devices under successive interference cancellation errors. In particular, the power budget of each drone, PD-NOMA power allocation of IoT devices, and the phase shift matrix of IRS are simultaneously optimized to enhance the total spectral efficiency of the system. Given the system model and optimization setup, the formulated problem is coupled with three variables, making it very complex and non-convex. Thus, this work first transforms and decouples the problem into subproblems and then obtains the efficient solution in two steps. In the first step, the closed-form solutions for the power budget and PD-NOMA power allocation subproblem at each drone are obtained through Karush-Kuhn-Tucker (KKT) conditions. In the second step, the subproblem of efficient phase shift design for each IRS is solved using successive convex approximation and DC programming. Numerical results demonstrate the performance of the proposed optimization scheme in comparison to the benchmark schemes.