We examine a general wireless sensor network (WSN) model which incorporates a large number of sensors distributed over a large and complex geographical area. The study proposes solutions for a flexible deployment, low cost and high reliability in a wireless sensor network. To achieve these aims, we propose the application of an unmanned aerial vehicle (UAV) as a flying relay to receive and forward signals that employ nonorthogonal multiple access (NOMA) for a high spectral sharing efficiency. To obtain an optimal number of subclusters and optimal UAV positioning, we apply a sensor clustering method based on K-means unsupervised machine learning in combination with the gap statistic method. The study proposes an algorithm to optimize the trajectory of the UAV, i.e., the centroid-to-next-nearest-centroid (CNNC) path. Because a subcluster containing multiple sensors produces cochannel interference which affects the signal decoding performance at the UAV, we propose a diagonal matrix as a phase-shift framework at the UAV to separate and decode the messages received from the sensors. The study examines the outage probability performance of an individual WSN and provides results based on Monte Carlo simulations and analyses. The investigated results verified the benefits of the K-means algorithm in deploying the WSN.

In long-range wireless communication networks, the fading channels described in channel state information are strongly related to distance and the path loss exponent and represent a major challenge in delivering the performance required to support emerging applications. Conveniently, multiple antennas and cooperative relays are efficient solutions that can combat fading channels, thereby improving networking capacity and transmission reliability. This study investigated the use of multi-antenna unmanned aerial vehicle (UAV)s as aerial Internet of Things (IoT) relays and employed their direct line-of-sight benefits to assist IoT wireless networks. To improve the outage probability, system throughput, and energy efficiency (EE), we first considered a combination of transmit antenna selection at the transmitter and the selection combining technique at the receiver to determine the best channel from the pre-coding channel matrix. Then, based on a practical model in a three-dimensional earth environment and thanks to the K-means algorithm, we investigated optimal UAV placement to obtain optimal channel state information for the non-orthogonal multiple access (NOMA)-IoT device cluster globally, thereby ensuring the quality of service for the IoT devices. We introduced a max-successive interference cancellation-min-rate framework for non-ordered NOMA devices, thus deriving theoretical expressions in novel closed forms for two independent scenarios: ( i ) Rayleigh and ( ii ) Nakagami- m fading channels. By optimizing the UAV placement, the investigated results applied to the UAV scheme delivered a better performance in a NOMA-IoT network than in a terrestrial relay (TR) scheme. Finally, this study examines a variety of models and presents algorithms for Monte Carlo simulations to verify the theoretical results.

Thanks to the benefits of non-orthogonal multiple access (NOMA) in wireless communications, we evaluate a wireless sensor network deploying NOMA (WSN-NOMA), where the destination can receive two data symbols in a whole transmission process with two time slots. In this work, two relaying protocols, so-called time-switching-based relaying WSN-NOMA (TSR WSN-NOMA) and power-splitting-based relaying WSN-NOMA (PSR WSN-NOMA) are deployed to study energy-harvesting (EH). Regarding the system performance analysis, we obtain the closed-form expressions for the exact and approximate outage probability (OP) in both protocols, and the delay-limited throughput is also evaluated. We then compare the two protocols theoretically, and two optimization problems are formulated to reduce the impact of OP and optimize the data rate. Our numerical and simulation results are provided to prove the theoretical and analytical analysis. Thanks to these results, a great performance gain can be achieved for both TSR WSN-NOMA and PSR WSN-NOMA if optimal values of TS and PS ratios are found. In addition, the optimized TSR WSN-NOMA outperforms that of PSR WSN-NOMA in terms of OP.

This work studies the SWIPT-based half-duplex (HD) decode-and-forward (DF) relay network, wherein the relay user can scavenge power from the source’s radio-frequency (RF) signals and then utilize it to convey the information to the destination. Specifically, two SWIPT-based relaying schemes, termed static power splitting- (SPS-) based relaying (SPSR) and optimal dynamic power splitting- (DPS-) based relaying (ODPSR), are proposed to investigate the benefits of each one fully. Based on the above discussions, the relaying system’s performance for outage probability (OP) is studied. Concretely, we derive the analytical expressions for both SPSR and DPSR methods. Finally, the numerical simulations are executed to corroborate the analysis and simulation results.

Hybrid decode-amplify and forward protocol of FD EH relaying network: outage probability analysis