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Ambient backscatter communication (AmBC) has emerged as a promising paradigm for enabling sustainable low-power operation of Internet of Things devices. This is due to its ability to enable sensing and communication through backscattering ambient wireless signals (e.g., WiFi and TV sig-nals). But a great impediment to AmBC-enabled networks is the difficulty in decoding the backscat-ter signals because the ambient signals are usually modulated and meant for other legacy receivers rather than AmBC devices. Drawing from the ability of machine learning (ML) to enhance the performance of wireless communication systems, some ML-aided techniques have been developed to assist signal detection in AmBC. Hence, this article aims to provide a comprehensive overview of the subject by describing the operation of the AmBC network, highlighting the major challenges to signal detection in AmBC, discussing and com-paring the performance of some existing ML-assisted solutions to AmBC signal detection, and highlighting some future research that could be carried out on the subject. [ABSTRACT FROM AUTHOR]

Millimetre wave (mmWave) communications, that is, 30 to 300 GHz, have intermittent short‐range transmissions, so the use of reconfigurable intelligent surface (RIS) seems to be a promising solution to extend its coverage. However, optimizing phase shifts (PSs) of both mmWave base station (BS) and RIS to maximize the received spectral efficiency at the intended receiver seems challenging due to massive antenna elements usage. In this paper, an online learning approach is proposed to address this problem, where it is considered a two‐phase multi‐armed bandit (MAB) game. In the first phase, the PS vector of the mmWave BS is adjusted, and based on it, the PS vector of the RIS is calibrated in the second phase and vice versa over the time horizon. The minimax optimal stochastic strategy (MOSS) MAB algorithm is utilized to implement the proposed two‐phase MAB approach efficiently. Furthermore, to relax the problem of estimating the channel state information (CSI) of both mmWave BS and RIS, codebook‐based PSs are considered. Finally, numerical analysis confirms the superior performance of the proposed scheme against the optimal performance under different scenarios. [ABSTRACT FROM AUTHOR]

In this review, we intend to present a complete literature survey on the conception and variants of the recent successful optimization algorithm, Harris Hawk optimizer (HHO), along with an updated set of applications in well-established works. For this purpose, we first present an overview of HHO, including its logic of equations and mathematical model. Next, we focus on reviewing different variants of HHO from the available well-established literature. To provide readers a deep vision and foster the application of the HHO, we review the state-of-the-art improvements of HHO, focusing mainly on fuzzy HHO and a new intuitionistic fuzzy HHO algorithm. We also review the applications of HHO in enhancing machine learning operations and in tackling engineering optimization problems. This survey can cover different aspects of HHO and its future applications to provide a basis for future research in the development of swarm intelligence paths and the use of HHO for real-world problems. [ABSTRACT FROM AUTHOR]

The hybrid combination between underwater optical wireless communication (UOWC) and radio frequency (RF) is a vital demand for enabling communication through the air–water boundary. On the other hand, non-orthogonal multiple access (NOMA) is a key technology for enhancing system performance in terms of spectral efficiency. In this paper, we propose a downlink NOMA-based dual-hop hybrid RF-UOWC with decode and forward (DF) relaying. The UOWC channels are characterized by exponential-generalized Gamma (EGG) fading, while the RF channel is characterized by Rayleigh fading. Exact closed-form expressions of outage probabilities and approximated closed-form expressions of ergodic capacities are derived, for each NOMA individual user and the overall system as well, under the practical assumption of imperfect successive interference cancellation (SIC). These expressions are then verified via Monte-Carlo simulation for various underwater scenarios. To gain more insight into the system performance, we analyzed the asymptotic outage probabilities and the diversity order. Moreover, we formulated and solved a power allocation optimization problem to obtain an outage-optimal performance. For the sake of comparison and to highlight the achievable gain, the system performance is compared against a benchmark orthogonal multiple access (OMA)-based system. [ABSTRACT FROM AUTHOR]

The mixture of wireless and power line communications (PLC) is vital for implementing new applications in smart grid and vehicular communications. In this work, we investigate the performance of non-orthogonal multiple access (NOMA) based dual-hop hybrid communication systems with decode-and-forward relay. The wireless channel is characterized by Nakagami-m fading under an additive white Gaussian noise (AWGN), while the PLC channels are characterized by Log-normal distribution with Bernoulli Gaussian noise including both background and impulsive noise components. New closed-form expressions for the outage probability, the asymptotic outage probability and ergodic capacity are derived and verified via extensive representative simulations. For more insights on the outage performance, we analyze the diversity order. Additionally, we proposed a power allocation optimization technique to achieve an outage-optimal performance. The results show that the system outage probability improves as the impulsive noise index and the arrival probability of the impulsive component of the PLC additive noise decrease, while their effect is negligible on the ergodic capacity. Finally, the performance of the proposed system is compared against a benchmark OMA-based system. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) and ambient backscatter communication (AmBC) have gained a lot of interest as key enabling technologies in wireless communications systems. NOMA is a key player for enhancing spectrum utilization either by multiplexing multiple messages for the same user or allowing multi-users access, while AmBC shows great potential for enhancing both spectrum and energy efficiency for battery-limited devices. In this paper, the performance of a downlink NOMA multiplexing based symbiotic-radio ($SR$) AmBC system is analyzed over Nakagami-m fading channels. New closed-form expressions for the exact and asymptotic outage probabilities are derived. Moreover, we analyze the diversity order and the influence of the system parameters on the outage performances. Besides, we proposed a power allocation optimization technique to achieve an outage-optimal performance. Through representative Monte-Carlo simulations, we have verified the analytical results. Finally, we compared the performance of the proposed system against a benchmark OMA-based system. [ABSTRACT FROM AUTHOR]