A new power allocation algorithm is proposed based on the Glicksberg game for cellular downlink non-orthogonal multiple access (NOMA) networks. First, a price-based user's utility function is proposed, and shown that it is effective and restrictive. Secondly, the Hessian matrix is used to derive an expression for power price based on the restricted transmission power and number of the served users in the cell. Then, the existence of a unique Nash equilibrium is proven and the optimum solution that maximises the utility function is presented. Finally, simulation results show that the proposed power allocation mechanism outperforms existing algorithms in terms of sum data rate and average data rate of the users.

The fifth generation (5G) networks must provide the massively increased number of users by thousand times higher data rate at lower power consumption. Thus, optimizing the energy efficiency (EE) becomes an essential issue that has to be researched from the green communication perspective. Non-orthogonal multiple access (NOMA) is considered one of the high potential techniques in fifth-generation systems. This technology is favorable to maximize the energy efficiency and the spectrum efficiency by composing different signals at the same time on the same carrier at different power levels. In this paper, a low complexity power allocation algorithm is proposed in imperfect channel state information (CSI) downlink NOMA cellular system, where obtaining full CSI at the base station is considered a challenge. The proposed algorithm relies on the fact that the allocated power is inversely proportional to the channel strength of the user to implement the successive interference cancellation (SIC) technique at the user terminal to reconstruct the desired signal. The performance of the system is analyzed in terms of energy efficiency and outage probability and compared to the conventional orthogonal multiple access (OMA) system. Results show that the proposed algorithm increases the energy efficiency by about 50% compared to the conventional OMA technology, and an improvement in the outage probability has been achieved. Furthermore, the effect of the error in the channel estimation on the energy efficiency in imperfect CSI NOMA system is evaluated. The simulation shows that the energy efficiency reduces when the channel estimation error increases; and the best performance is achieved in the perfect CSI case where the channel estimation error is zero.

Nonorthogonal multiple access (NOMA) is considered a promising technique for improving energy efficiency (EE) in beyond-5G wireless systems. In this paper, we investigate the maximization of EE of downlink wireless systems by combining mmWave with NOMA technologies, considering the asymmetric required data rate of user applications. We propose a genetic algorithm (GA) to solve the non-convex energy efficiency problem for an imperfect CSI downlink mmWave NOMA system. The studied mixed-integer optimization problem was converted to an integer optimization problem and solved using a GA, which determines the best clustering members in mmWave NOMA. The required population size of the proposed GA was determined to evaluate its effectiveness for a massive number of users. In addition, the GA’s convergence to the optimal solution for light traffic and relatively heavy traffic was also analyzed. Our results illustrate that the solution obtained solution via GA is almost equal to the optimal value and outperforms the conventional orthogonal multiple access, where the EE is improved by more than 75%. Finally, the impact of the estimation error of CSI on the system performance was evaluated at different required SINR scenarios. The results show that EE is degraded in the case of imperfect CSI case but is still close to the optimal solution.

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