Power allocation technique with soft performance guarantees in hybrid OFDMA–NOMA cognitive radio systems: Modeling and simulation

Abstract

The integration between orthogonal frequency division multiple access (OFDMA), non-orthogonal multiple access (NOMA), and cognitive radio (CR) technology has been recently configured as promising candidate to support the massive high-speed connectivity requirements of beyond fifth generation (B5G) systems. This combination is referred to in the literature as a hybrid OFDMA–NOMA CR network. In such a system, each primary user’s (PU) idle channel, i.e., sub-band, is opportunistically utilized to serve multiple secondary users (SUs) by exploiting power-domain NOMA. This study soughs to explore the resource allocation technique for a hybrid OFDMA–NOMA CR system to further elaborate the potential capabilities of this system. Specifically, a power minimization resource allocation framework is developed, in which the objective is to serve the contending CR users, i.e., SUs, with minimum possible total transmission power, while achieving a set of relevant NOMA and CR constraints. These constraints include the dynamic nature of PU activities, rate demand, probability of success and imposed CR power mask constraints. However, the developed power minimization framework is non-convex in nature. Therefore, we employ the sequential convex approximation (SCA) along with a second-order cone approach to deal with the non-convexity issues of the developed optimization problem, and thus evaluating the corresponding optimization parameters. Compared to the conventional orthogonal resource allocation techniques, simulation results reveal that our proposed resource allocation technique for the hybrid OFDMA–NOMA CR system has a considerable performance enhancement in terms of the overall network throughput and total required transmit power.