In this paper, we propose an integration of compressive sensing (CS) and clustering in WSNs utilizing block diagonal matrices (BDMs) as the measurement matrices. Such an integration results in a significant reduction in the power consumption related to the data collection. The main idea is to partition a WSN into clusters, where each cluster head (CH) collects the sensor readings within its cluster only once and then generates CS measurements to be forwarded to the base station (BS). We considered two methods to forward CS measurements from CHs to the BS: (i) direct and (ii) multi-hop routing through intermediate CHs. For the latter case, a distributed tree-based algorithm is utilized to relay CS measurements to the BS. The BS then implements a CS recovery process in the collected M CS measurements to reconstruct all N sensory data, where M N . Under this novel framework, we formulated the total power consumption and discussed the effect of different sparsifying bases on the CS performance as well as the optimal number of clusters for reaching the minimum power consumption.

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This paper proposes an exhaustive analysis of a particle swarm optimization (PSO)-based configuration applied in non-orthogonal multiple access (NOMA) systems in order to perform user aggregation along different sub-channels. The idea behind this is to highlight the main characteristics of this PSO-based configuration for understanding how this policy enables the transmitter to require the minimum downlink transmitting power while guaranteeing the quality-of-service (QoS) constraint of each user. The analysis is carried out for two representative power-constrained scenarios, i.e., disaster relief network communications and unmanned aerial vehicle (UAV) communications, in which performing low-power transmissions represent an important aspect. Our results find applicability in the definition of explicit channel-state-aware strategies for user multiplexing in NOMA systems, which, at the date, represents a research field that remains to be investigated more in depth. Insightful discussions are provided from our analysis. For instance, depending on the number of available sub-channels and the channel gains experienced by each users along with the whole available bandwidth, it is shown how users must be multiplexed by the transmitter in order to reach the minimum transmitting power.

Wireless power transfer (WPT) techniques are important in a variety of applications in both civilian and military fields. Unmanned aerial vehicles (UAVs) are being used for many practical purposes, such as monitoring or delivering payloads. There is a trade-off between the weight of the UAVs or their batteries and their flying time. Their working time is expected to be as long as possible. In order to support the UAVs to work effectively, WPT techniques are applied with UAVs to charge secondary energy supply sources in order to increase their working time. This paper reviews common techniques of WPT deployed with UAVs to support them while working for different purposes. Numerous approaches have been considered to illustrate techniques to exploit WPT techniques. The charging distances, energy harvesting techniques, electronic device improvements, transmitting issues, etc., are considered to provide an overview of common problems in utilizing and charging UAVs. Moreover, specific problems are addressed to support suitable solutions with either techniques or applications for UAVs.

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