Reconfigurable intelligent surface (RIS), nonorthogonal multiple access (NOMA), and underwater optical wireless communication (UOWC) are paradigms of technologies that drive the development of next generation communication systems. In this paper, we investigate the performance of a NOMA-based RIS-assisted hybrid radio frequency (RF) UOWC system. The ship works as a relay that redirects the received signal to two underwater destinations simultaneously. Due to the interruption of the direct link between the base station and the ship floating on the surface of the water, communication will be carried out via an RIS fixed to an intermediate building. In this paper, we provide new analytical expressions for the outage probability (OP), asymptotic analyses of the OP, and diversity order (D) to gain insights into the system performance. The results showed that the diversity order depends on the UOWC receiver detection technique. In the end, we illustrated that the NOMA-based RIS-assisted system significantly improves the outage performance of hybrid RF-UWOC systems over a benchmark system.

This paper investigates the performance of non-orthogonal multiple access (NOMA) based hybrid satellite-unmanned aerial vehicle (UAV) systems, where a low Earth orbit (LEO) satellite communicates with the ground users via a decode and forward (DF) UAV relay. We investigate a two NOMA users system, where a far user (FU) and a near user (NU) are served by the UAV which is located at a certain height above the origin of the coverage circle. The channel between satellite and UAV is assumed to follow a Shadowed-Rician fading and the channels between UAV and users are assumed to follow a Nakagami-m fading. New closed-form expressions of the outage probabilities for the two users and the system are derived. Different from other work in literature, we take into consideration different parameters affecting the total link budget. Additionally, we propose an algorithm for minimizing the system outage probability. The mathematical analysis is verified by extensive representative Monte-Carlo (MC) simulations. Finally, simulations are provided to demonstrate the impact of important parameters on the considered system as well as the superiority of the NOMA scheme the over reference scheme.

Non-orthogonal multiple access (NOMA) and ambient backscatter communication (AmBC) play major roles to enhance spectrum efficiency in wireless communication systems. Besides, the AmBC provides good reinforcement for the current trend toward dispensing batteries for battery-free Internet-of-Things (IoT) devices. In this paper, we propose a symbiotic battery-free IoT system, that exploits the downlink transmission of a NOMA multiplexing enabled cellular network, to permit an IoT spectrum-efficient uplink communication. The IoT backscatter device (BD) performs a symbiotic radio (SR) relation with the cellular source to power its communication by intelligently reflecting the received power. We derive a closed-form expression of the ergodic capacity (EC) of the BD transmission and tight approximations of the ECs of the cellular source transmission, where all channels undergo Nakagami-m fading. Additionally, we validate the analytical results obtained using Monte-Carlo simulations. The influences of several system parameters such as power allocation factor, reflection coefficient, and channels’ severity factors have been investigated. Finally, the performance of the proposed system is compared with a benchmark OMA-based system to highlight the achievable performance improvement.

Long-range wide area network (LoRaWAN) is a promising low-power network standard that allows for longdistance wireless communication with great power saving. LoRa is based on pure ALOHA protocol for channel access, which causes collisions for the transmitted packets. The collisions may occur in two scenarios, namely the intra-spreading factor (intra-SF) and the inter-spreading factor (inter-SF) interference. Consequently, the SFs assignment is a very critical task for the network performance. This paper investigates a smart SFs assignment technique to reduce collisions probability and improve the network performance. In this work, we exploit different architectures of artificial neural networks for detecting collisions and selecting the optimal SF. The results show that the investigated technique achieves a higher prediction accuracy than traditional machine learning algorithms and enhances the energy consumption of the network.

In this work, a non-orthogonal multiple access NOMA) relying on a two-way relaying (TWR) approach is investigated to promote more efficient use of the available spectrum. Specifically, a NOMA-enabled half-duplex decode-and-forward relay node is used to simultaneously exchange data between two cellular users and a base station (BS), while assuming that the direct links between the two users and the BS are unavailable or negligible. In our analysis, the ergodic capacity is evaluated, in which high signal-to-noise ratio approximations, as well as upper bounds are derived owing to the intractability related to the exact analysis. The results reveal the superiority of the proposed TWRNOMA scheme compared with the traditional one-way relaying (OWR-NOMA) scheme. Additionally, simulation results show that selecting a relay station (RS) closer to the BS can achieve a higher ergodic sum capacity or the system than selecting a far RS.

The paper describes ML techniques that can be leveraged to assist signal detection in ambient backscatter communication networks.

This paper proposes an energy-efficient resource allocation framework for the AmBC-enabled NOMA IoV network under imperfect Successive Interference Cancellation (SIC) decoding. In particular, multiple Road-Side Units (RSUs) transmit superimposed signals to their associated IoVs utilizing downlink NOMA transmission. Meanwhile, the Backscatter Tags (BackTags) also transmit data symbols towards nearby IoVs by reflecting the superimposed signals of RSUs. Thus, the objective is to maximize the total energy efficiency of the NOMA IoV network subject to the minimum data rate of all IoVs. A joint problem that simultaneously optimizes the total power budget of each RSU, power allocation coefficient of IoVs and reflection power of BackTags under imperfect SIC decoding is formulated.