Recently, cutting-edge techniques, such as Non-Orthogonal Multiple Access (NOMA), have been highlighted to enable wireless networks to handle massive access scenarios and further improve the spectral efficiency. Nevertheless, these advantages come at the price of privacy exposure since a received signal may contain information belonging to several users. Usual security mechanisms, such as upper-layer encryption and sophisticated authentications, are not well suited to low-capacity Internet of Things (IoT) devices. These technical challenges have spotlighted Physical Layer Security (PLS) as a key enabling technology since it takes advantage of the wireless communication characteristics to secure communications without adding complex encryption mechanisms at higher layers. In this paper, we propose a PLS approach based on a network coding technique in order to ensure secure NOMA-based downlink transmissions taking into account the Quality of Service (QoS) requirements of the users. By doing so, decoding successfully some of the transmitted packets by an eavesdropper does not reveal useful information about the data. In fact, we develop a sequence-based algorithm with the aim of ensuring the confidentiality by changing the users’ positions in the Successive Interference Cancellation (SIC) decoding process. Henceforth, using its corresponding sequence, the legitimate user becomes the only one able to decode the information sent by the Base Station (BS). We show that the eavesdropper decoding complexity increases exponentially with the sequence length making the task intractable for relatively long ones.

Facing the exponential number of Internet of Things (IoT) devices and the scarcity of available resources, next-generation wireless networks have to meet very challenging performance targets in terms of providing massive access and ensuring higher spectral efficiency . In this vein, Non-Orthogonal Multiple Access (NOMA) has been widely recognized as one of the advantageous techniques to handle the proliferation of the IoT. Nevertheless, from a security standpoint, enabling a user to decode the signals of the other users, while using Successive Interference Cancellation (SIC), raises serious concerns regarding confidentiality and vulnerability to malicious attacks . Meanwhile, conventional security paradigms, such as upper-layer encryption and sophisticated authentication mechanisms , require high computational complexity and additional processing, which impose an overwhelming burden on energy-efficient IoT devices. Alternatively, Physical layer Security (PLS) has sparked a significant interest as a promising complement to cryptographic techniques . The key idea of PLS is to avail wireless communication properties to secure communications without adding complex encryption mechanisms at higher layers. In this paper, we propose a PLS approach based on a network coding technique to prevent eavesdroppers from decoding users’ information transmitted through a downlink-based NOMA system. This results in correlating the packets to be transmitted with each other, making the interception of a single packet useless. We demonstrate that the eavesdropper’s decoding complexity increases exponentially with the sequence length , making the task intractable for relatively long ones.

Attracted by the advantages of Non-Orthogonal Multiple Access (NOMA) in accommodating multiple users within the same resources, this paper jointly addresses the resource allocation and power control problem for Machine Type Devices (MTDs) in a Hybrid NOMA system. Particularly, we model the problem using a Mean Field Game (MFG) framework underlying a Multi-Armed Bandit (MAB) approach. Firstly, the devices invoke the MAB tool to arrange themselves into multiple NOMA coalitions. Then, within each coalition, the MTDs apply the MFG approach to autonomously adjust their transmit power based on limited feedback received from the Base Station (BS). Simulation results are given to illustrate the equilibrium behavior of the proposed resource allocation algorithm and to underline its robustness compared to existing works in the literature.

Attracted by the advantages of Non-Orthogonal Multiple Access (NOMA) in accommodating multiple users within the same resource, this paper investigates the power allocation problem for Machine Type Devices (MTDs) in a Hybrid NOMA system. Particularly, we consider a densely deployed network in which the devices are divided into orthogonal coalitions. Firstly, the power control problem is modeled as a differential game. Then, we formulate the proposed game as a Mean Field Game (MFG) in order to handle massive Internet of Things (IoT) access scenarios. Furthermore, we design an iterative algorithm that paves the way for distributed control in which the devices can appropriately regulate their transmit power in response to brief information received from the Base Station (BS). The analysis of the proposed approach is conducted through coupled equations, namely the Hamilton-Jacobi-Bellman (HJB) and the Fokker-Planck-Kolmogorov (FPK). Our simulation results prove the convergence of the proposed power control strategy and spotlight the robustness of our formulated MFG.

The steady expansion of the number of wireless devices and the ubiquity of the networks give rise to various interesting challenges for the future sixth generation (6G) of wireless communication systems. Particularly, the operators have to handle massive connectivity among Machine Type Devices (MTDs) and increasing demand for eMMB through limited spectrum resources. Non-Orthogonal Multiple Access (NOMA) has been spotlighted as an emerging technology to meet the above-mentioned challenges. In this paper, we consider a densely deployed network in which users are divided into NOMA coalitions. Firstly, we model the power allocation problem as a differential game. Then, we extend the formulated game using a Mean Field Game (MFG) theoretic framework by considering the effect of the collective behavior of devices. Furthermore, we derive a distributed power control algorithm that enables the users to appropriately regulate their transmit power according to brief information received from the BS. Indeed, the analysis of the proposed approach is governed by the two fundamental Hamilton- Jacobi-Bellman (HJB) and Fokker-Planck-Kolmogorov (FPK) equations. Numerical results are presented to analyze the equilibrium behaviors of the proposed power control algorithm and to demonstrate the effectiveness of the formulated MFG compared to existing works in the literature.

Non-Orthogonal Multiple Access (NOMA) is an interesting candidate to tackle the massive access challenges in Beyond 5G (B5G) systems. However, arranging Machine Type Devices (MTDs) into NOMA clusters and allocating resources to these clusters is a non-trivial task. In this paper, we consider a Hybrid NOMA system where every NOMA cluster is allocated an orthogonal sub-carrier and propose a game theoretical framework based on a bi-level game in order to achieve joint channel selection and power allocation for MTDs. Indeed, the proposed approach is composed of a non-cooperative power control game underlying a cooperative Hedonic game that enables MTDs to self-organize into coalitions. Furthermore, we propose two low-complexity algorithms that enable us to obtain a Nash-Stable partition where MTDs decide autonomously the appropriate Resource Block (RB) and the transmit power to use in order to deliver their packets. Our simulation results show that the proposed bi-level game allows the devices to achieve a high successful packet transmission rate while consuming less energy.