The advent of 6G-enabled real-time applications, such as remote surgery and autonomous driving, has sparked significant interest in a novel and integrated metric known as the age of information (AoI). This metric is particularly valuable because it effectively reflects the trade-offs between reliability, latency, and frequent updates. In this paper, we propose an intelligent framework for hybrid automated repeat request (HARQ) enabled rate splitting multiple access (RSMA) networks, aiming to optimize resource utilization while maintaining a balance between timeliness and reliability. Particularly, the source intelligently adapts power allocation and re-transmissions for common and private streams of RSMA carrying data packets of different priorities, considering the current state of AoI and feedback signals. Firstly, an analytical framework is established by deriving closed-form approximations for the individual average block error rates (BLER) of both common and private streams. Subsequently, an AoI minimization problem is formulated using the derived BLER. Following that, the problem is modeled as a Markov decision process (MDP), allowing us to develop an optimal policy for minimizing the system’s average AoI. Moreover, we also devise a near-optimal solution utilizing the Lyapunov drift function, accounting for the MDP’s complexity. Extensive simulations demonstrate that the proposed approach improves the AoI performance of the RSMA scheme and outperforms the conventional approaches.

Rate splitting multiple access (RSMA) has a variety of advantages, including higher throughput, enhanced capacity, and network efficiency, which makes it suitable for beyond fifth generation (5G) networks. Since the combining and splitting operations are performed on the transmitter side, one of the challenging aspects of RSMA is how a retransmission can be accomplished. In this article, an efficient hybrid automatic repeat request (HARQ) design for RSMA networks is presented in which three novel retransmission strategies are developed. More specifically, the main idea is choosing among RSMA, nonorthogonal multiple access (NOMA), and space division multiple access (SDMA) during the HARQ retransmission round, respectively, to do the retransmission. Therefore, a new link adaptation approach is proposed. The effectiveness of the proposed design is analyzed in terms of the average number of retransmissions, energy efficiency (EE), and achievable sum rate. Simulation results confirm the superiority of the proposed protocol in terms of packet error rate, EE, and sum-rate improvement up to 70%, 81%, and 76%, respectively, as compared to the conventional RSMA.

Cognitive radio-based non-orthogonal multiple access (CR-NOMA) is considered to be one of the promising multiple accessing technique candidates for 5G and beyond networks. These networks are facing a lot of challenges to achieve high spectral efficiency, low latency, and massive connectivity. Interference management and efficient power allocation are highly interesting among the researchers to investigate in CR-NOMA networks. This paper studies the power allocation of underlay CR-NOMA network using game theory approach by conducting the pricing technique to achieve efficient power allocation and minimum interference. In particular, the game is formulated, and its solution is achieved by exploring the suboptimal solution represented by the Pareto-efficiency of the Nash equilibrium point. The simulation results show the superiority of the proposed scheme in achieving higher spectral efficiency, fairness index, and sum utilities of secondary users compared to existing schemes.

Cognitive radio-based non-orthogonal multiple access (CR-NOMA) is considered to be one of the promising multiple accessing technique candidates for 5G and beyond networks. These networks are facing a lot of challenges to achieve high spectral efficiency, low latency, and massive connectivity. Interference management and efficient power allocation are highly interesting among the researchers to investigate in CR-NOMA networks. This paper studies the power allocation of underlay CR-NOMA networks using multi-input multi-outputs (MIMO) techniques to increase the achievements of getting higher spectral efficiency as well as spatial diversity among multiple users to be served. In particular, power allocation based on uniform and adaptive power allocation, and near-optimal for high and low signal to noise ratio are derived. Finally, the simulation results show the superiority of the proposed scheme in achieving higher spectral efficiency, fairness, and average capacity of secondary users compared to the conventional scheme.

Cognitive radio non-orthogonal multiple access (CRNOMA) networks promise improved spectrum utilization and capacity in 5G networks. In this work, we aim to investigate efficient power allocation for the secondary users (SUs) in underlay CR-NOMA networks using a game-theoretic approach. We present a novel power allocation to CR-NOMA network from a game-theoretic perspective. First, we specify the utility function of the primary users (PUs) and SUs, and formulate the game as a non-cooperative game. Then, the existence and uniqueness of the Nash equilibrium (NE) are investigated. Finally, the sum utilities of SUs is maximized by optimal power allocation at the NE point. Simulation results provided that the proposed scheme outperforms the conventional method, providing up to 37.5% increase in sum utilities of the SUs.