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Reconfigurable intelligent surfaces (RISs) have been proposed as a key enabler to improve the coverage of the signals and mitigate the frequent blockages in millimeter wave (mmWave) multiple-input multiple-output (MIMO) communications. However, the channel state information (CSI) acquisition is one of the major challenges for the practical deployment of the RIS. The passive RIS without any baseband processing capabilities brings difficulty on the channel estimation (CE), since the individual channels or the cascaded one can be estimated only at base station (BS) via uplink training or mobile station (MS) via downlink training. In order to facilitate the CSI acquisition, we focus on the hybrid RIS architecture, where a small number of elements are active and able to receive and process the pilot signals at the RIS. The CE is performed in two stages by following the atomic norm minimization to recover the channel parameters, i.e., angles of departure (AoDs), angles of arrival (AoAs), and propagation path gains. Simulation results show that the proposed scheme can outperform the passive RIS CE under the same training overhead. Furthermore, we also study the theoretical performance limits in terms of mean square error (MSE) via Cramér-Rao lower bound (CRLB) analyses. [ABSTRACT FROM AUTHOR]

This work proposes an algorithm to optimize the positioning and the transmit power of Drone Small Cells (DSCs) based on Q‐learning, a technique where the agents learn to maximize a given reward. We consider two different rewards in this work, the first focusing on coverage, while the second maximizes the lifetime. Then, the Q‐learning solution determines the best positioning of the DSC in the 3D space, as well as the optimal transmit power. Results show that the optimization of the transmit power is of paramount importance to reduce the outage probability. In addition, we show that the second reward can considerably increase the network lifetime with a small penalty to the coverage. [ABSTRACT FROM AUTHOR]

Providing higher data rate is a momentous goal for wireless communications systems, while interference is an important obstacle to reach this purpose. To cope with this problem, interference alignment (IA) has been proposed. In this paper, we propose two rank minimization methods to enhance the performance of IA in the presence of uncoordinated interference, i.e., interference that cannot be properly aligned with the rest of the network and thus is a crucial issue. In this scenario, perfect and imperfect channel state information (CSI) cases are considered. Our proposed approaches employ the $l_{2}$ and the Schatten- $p$ norms to approximate the rank function, due to its non-convexity. Also, we propose a new convex relaxation to expand the feasible set of our optimization problem, providing lower rank solutions compared to other IA methods from the literature. In addition, we propose a modified weighted-sum method to deal with interference in the relay-aided MIMO interference channel, which employs a set of weighting parameters in order to find more solutions. [ABSTRACT FROM AUTHOR]

Cooperative communications can substantially improve the performance in fading channels. However, in energy-constrained wireless sensor networks, the benefits of cooperation only go until certain limits, beyond which the energy cost of cooperation can be significant and unprofitable. We propose a cooperative scheme in which the relays activate the receiving circuitry based on a switching ON–OFF probability. We derive analytic expressions for the amount of effective information transmitted through the network and the associated outage probability under Nakagami-mfading channels. Based on the developed analysis, we formulate an optimization problem in which the switching ON–OFF probabilities are adjusted to reduce the energy consumption, subject to an outage probability constraint. We evaluate the performance of the proposed scheme under fixed and random network topologies. Our results indicate that the proposed scheme substantially outperforms the standard cooperative reception approach in terms of the amount of effective information transmitted through the network. [ABSTRACT FROM AUTHOR]

This paper employs game theory to optimize the performance of multiple secondary users (SUs) in a cognitive radio ad hoc network where the primary and SUs have quality of service (QoS) constraints. The proposed algorithm utilizes a distributed noncooperative game theory mechanism among SUs that compete to maximize their individual capacities. We propose two utility functions, UcLog and UcLin, with logarithmic and linear cost functions of the perceived interference in the primary receiver, respectively. The value of the utility function varies according to the transmit power and the relay selection strategy. Simulation results show that both utility functions obtain similar results in most scenarios. However, UcLin causes less interference to the primary receiver and has better convergence than UcLog. The two consecutive games mechanism used in the proposed algorithm allows us to achieve rates above 95% in all simulated scenarios without QoS constraints in secondary links. [ABSTRACT FROM AUTHOR]

We study the cross-layer energy efficiency of cooperative MIMO networks. At the physical layer, the transmit power determines the outage probability and the number of contending nodes per unit area. At the medium access control (MAC) layer, accessing the channel takes additional time and energy, which impacts the throughput and the energy efficiency. Then, we propose a new cooperative MAC protocol based on IEEE 802.11 in order to coordinate cooperation and to improve the energy efficiency. Moreover, we focus on slow fading scenarios and we analyze the performance of antenna selection (AS), singular value decomposition (SVD) diversity beamforming, and spatial multiplexing (SM) transmission schemes. Results show that SVD and SM have smaller delay and, consequently, larger throughput; however, AS is more energy efficient. [ABSTRACT FROM PUBLISHER]

In this paper, we consider a scenario where two multiple-aperture legitimate nodes (Alice and Bob) communicate by means of free-space optical communication in the presence of a multiple-aperture eavesdropper (Eve), which is subject to pointing errors. Two different schemes are considered depending on the availability of channel state information (CSI) at Alice: 1) the adaptive scheme, where Alice possesses the instantaneous CSI with respect to Bob and 2) the fixed-rate scheme, where such information is not available at Alice. The performance of the aforementioned schemes is evaluated in terms of a recently proposed metric named effective secrecy throughput (EST), which encompasses both the reliability and secrecy constraints. By constraining the system to operate below a given maximum allowed secrecy outage probability, we evaluate the EST analytically and through numerical results, showing that the use of multiple apertures at Alice is very important toward achieving the optimal EST. [ABSTRACT FROM PUBLISHER]

In this letter, we investigate the secure energy efficiency (SEE) in a cooperative scenario where all nodes are equipped with multiple antennas. Moreover, we employ secrecy rate and power allocation at Alice and at the relay in order to maximize the SEE, subjected to a constraint in terms of a minimal required secrecy outage probability. Only the channel state information (CSI) with respect to the legitimate nodes is available. Then, we compare the artificial-noise (AN) scheme with CSI-aided decode-and-forward (CSI-DF), which exploits the CSI to choose the best communication path (direct or cooperative). Our results show that CSI-DF outperforms AN in terms of SEE in most scenarios, except when eavesdropper (Eve) is closer to the relay or with the increase of antennas at Eve. Additionally, we also show that the maximization of SEE implies in an optimal number of antennas to be used at each node, which is due to the tradeoff between secure throughput and power consumption. [ABSTRACT FROM AUTHOR]

Underwater acoustic networks (UAN) allow for efficiently exploiting and monitoring the sub-aquatic environment. These networks are characterized by long propagation delays, error-prone channels and half-duplex communication. In this paper, we address the problem of energy-efficient communication through the use of optimized channel coding parameters. We consider a two-layer encoding scheme employing forward error correction (FEC) codes and fountain codes (FC) for UAN scenarios without feedback channels. We model and evaluate the energy consumption of different channel coding schemes for a K-distributed multipath channel. The parameters of the FEC encoding layer are optimized by selecting the optimal error correction capability and the code block size. The results show the best parameter choice as a function of the link distance and received signal-to-noise ratio. [ABSTRACT FROM AUTHOR]

We investigate the use of discrete-time analog joint source channel coding (JSCC) in a wireless sensor network where the source of information is wirelessly powered by the destination. Wireless energy transfer and information transmission are multiplexed via a time-switching protocol. As a fraction of the time slot is spent for energy transfer, the source samples are saved and compressed using either parametric or non-parametric $N$ : $K$ dimension compression analog JSCC to transmit the information in the remaining fraction of the time slot. We analyze both matched and unmatched source and channel bandwidths. Moreover, we investigate the time-sharing parameter that optimizes the analog system performance and show that the proposed analog scheme can outperform a fully digital system. [ABSTRACT FROM PUBLISHER]

Many applications of wireless sensor networks require that nodes, besides monitoring a given phenomenon, must be able to detect and communicate asynchronous events (e.g. alarms), implying that they have to often listen to the medium in idle mode, which is inherently energy wasteful. In such a scenario time synchronization is crucial to efficiently operate in duty-cycles and minimize energy consumption. In this work we assess the impact of the trade-off between spending energy with more frequent synchronizations and in return saving it by reducing the idle listening window necessary for the desired reliability of the communication. The optimal frequency of time synchronizations is obtained analytically and corroborated by numerical results, showing that several times less overall energy may be spent with a finer synchronization when compared with maintaining the minimum clock precision required by the phenomenon being monitored, greatly extending the life-span of the network. [ABSTRACT FROM PUBLISHER]

Retransmissions due to decoding errors have a big impact on the energy budget of low-power wireless communication devices, which can be reduced by using hybrid automatic repeat request (HARQ) techniques. Nevertheless, this reduction comes at the cost of extra energy consumption introduced by the added computational load. No complete analysis of the tradeoff between retransmissions reduction and baseband consumption of low-power communications over fading channels has been reported so far. In this paper, we study the energy efficiency achievable by HARQ schemes when the code rate of the error-correcting code is optimized. For this purpose, we develop an energy consumption model that focuses on simple HARQ (S-HARQ) and Chase combining (HARQ-CC) transmissions, which are studied under fast-fading and block-fading scenarios with Nakagami-$m$ fading. The retransmission statistics are analyzed, and expressions for the expected number of transmission trials are derived. Using this framework, it is shown that transmission schemes with high diversity gain are the most efficient choice for long range transmissions, which in our case correspond to HARQ-CC and codes with low code rate. On the other hand, schemes with good multiplexing capabilities are optimal for short link distances, which in our analysis correspond to S-HARQ and high code rates. It is also shown that HARQ-CC can effectively extend the transmission range of a low-power communication device. [ABSTRACT FROM PUBLISHER]

This paper proposes an iterative power allocation algorithm that maximizes the energy efficiency of a multiple-relay cooperative multiple antenna (MIMO) network. Energy efficiency is defined as the achievable spectral efficiency normalized by the total power consumption, which also accounts for the RF circuitry consumption, modeled in a wireless sensor network. Moreover, relay selection is performed using the distributed opportunistic selection protocol, while we derive closed-form expressions for outage probability and energy efficiency for a single antenna (SISO) and two MIMO scenarios: 1) based on antenna selection (AS) and 2) based on single value decomposition (SVD) beamforming. In order to evaluate the performance of the proposed algorithm, we compare it to an exhaustive search optimal power allocation method. Results show that the proposed algorithm performs very close to an exhaustive search approach and that, although MIMO SVD has the best outage performance, AS has the best energy efficiency for low and moderate source-destination distances and spectral efficiencies. [ABSTRACT FROM AUTHOR]

We evaluate the effective secrecy throughput of the multiple-input multiple-output multiple-antenna eavesdropper (MIMOME) wiretap channel with antenna selection at the legitimate transmitter. The optimal target secrecy rate that maximizes the effective secrecy throughput is obtained and confirmed by numerical results. Differently from previous works, we constrain the maximum allowed secrecy outage probability (SOP) and show that, the single-input single-output multi-antenna eavesdropper (SISOME) scheme recently proposed in the literature presents a much lower resilience to the decrease of the maximum allowed SOP than that obtained by MIMOME scheme. [ABSTRACT FROM PUBLISHER]

We assume a full-duplex (FD) cooperative network subject to hostile attacks and undergoing composite fading channels. We focus on two scenarios: a) the transmitter has full CSI, for which we derive closed-form expressions for the average secrecy rate; and b) the transmitter only knows the CSI of the legitimate nodes, for which we obtain closed-form expressions for the secrecy outage probability. We show that secure FD relaying is feasible, even under strong self-interference and in the presence of sophisticated multiple antenna eavesdropper. [ABSTRACT FROM AUTHOR]

Energy efficient underwater communications systems design is a crucial task, once battery replacement may be barely feasible in this scenario. As acoustic underwater channels are usually harsher than terrestrial wireless channels, decreasing the transmission distance through a multi-hop approach is very appealing. In this sense, in this paper, we analyze how much energy is required to successfully transfer an information bit over a multi-hop underwater acoustic network while considering the optimum number of hops, retransmissions, code rate, and signal-to-noise ratio. We also investigate the impact of delay constraints in the total energy consumption, by allowing limited or unlimited retransmissions. Our results show that great energy savings can be obtained when the above-mentioned parameters are jointly optimized for a given link distance. Moreover, even though the impact of multiple hops is more beneficial, allowing for a small number of retransmissions lead to important energy savings. Finally, we compare the obtained results with a terrestrial wireless communications case, showing that an adequate modeling of the underwater scenario is imperative for an energy efficient design, once the optimal number of hops for terrestrial wireless may considerably differ from that for underwater communications. [ABSTRACT FROM PUBLISHER]

In this paper we investigate the physical layer security in a cooperative scenario where the source and the eavesdropper are equipped with multiple antennas, while the relay and the destination are single-antenna devices. We consider that no channel state information (CSI) is available at the transmitter, besides the index of the selected transmit antenna. Closed-form expressions for the secrecy outage probability of the selective decode-and-forward (SDF) and incremental decode-and-forward (IDF) schemes are derived. In addition, we also conduct an asymptotic analysis to get further insights on the performance of each scheme, which predicts a performance floor inherent to the scenario without CSI at the transmitter. Moreover, we also analyze the schemes in terms of the secrecy throughput, which shows that the performance floor that appear in the outage analysis only affects the secrecy throughput if the floor is too high, as is the case of the non-cooperative transmission. Our analysis show that IDF can considerably outperform the SDF and the non-cooperative transmission both in terms of secrecy outage probability and secrecy throughput. [ABSTRACT FROM PUBLISHER]

In this paper we analyze the efficiency of cellular network designs, by taking into account the co-channel interference among cells, different amounts of available bandwidths, and frequency reuse. A realistic power consumption model is considered for the energy efficiency analysis, and for the economic analysis it is employed a model in which the total cost is composed by three factors: spectrum license, energy and infrastructure costs. Our results show that different conclusions can be obtained according to the focus of the network design: energy efficiency or total costs. Assuming an economic point of view, the most cost efficient solutions can be obtained when the number of base stations and the available bandwidth are the factors to be balanced, as the infrastructure cost and the spectrum license costs correspond to the most relevant fraction of the total costs. However, considering the energy efficiency anlysis, it can be more beneficial to employ a higher system bandwidth and balance the number of base stations and the reuse of frequencies in order to minimize the required transmit power. [ABSTRACT FROM PUBLISHER]

We investigate the energy efficiency-spectral efficiency (EE-SE) trade-off of transmit antenna selection/maximum ratio combining (TAS) scheme. A realistic power consumption model (PCM) is considered, and it is shown that using TAS can provide significant energy savings when compared to multiple-input multiple-output (MIMO) in the low to medium SE region, regardless the number of antennas, as well as outperform transmit beamforming scheme (MRT) for the entire SE range. For a fixed number of receive antennas, our results also show that the EE gain of TAS over MIMO becomes even greater as the number of transmit antennas increases. The optimal value of SE that maximizes the EE is obtained analytically, and confirmed by numerical results. Moreover, the influence of receiver correlation is also evaluated and it is shown that considering a non-realistic PCM can lead to mistakes when comparing TAS and MIMO. [ABSTRACT FROM AUTHOR]

The effective deployment of Internet of Things (IoT) applications such as smart cities, smart farming and smart transport systems must ensure the network robustness, scalability and longevity. Therefore, guaranteeing the successful delivery of information and extending the lifetime of the nodes that make up a wireless sensor network (WSN) are two essential aspects for IoT applications. This work evaluates the performance of a cooperative WSN by adopting two multiantenna schemes: antenna selection (AS) and beamforming transmission using the singular value decomposition (SVD) technique. In addition, cooperation is established according to an ON–OFF probability, so that the RF receiving circuits of the relays are activated in a probabilistic way, aiming at reducing the energy consumption of the sensors, extending their useful lifetime. Our main goal is to increase the amount of information effectively transmitted by the network, keeping an outage probability constraint. The results show that, when both techniques are used, there is a significant gain in the amount of information effectively transmitted by the network, with emphasis on the AS scheme at short transmission distances. By increasing the number of antennas, it was found that a lower ON–OFF probability is required, i.e., a trade-off is established between the nodes' hardware complexity and their need for cooperation. [ABSTRACT FROM AUTHOR]

Energy-efficiency is crucial for modern radio-frequency (RF) receivers dedicated to Internet of Things applications. Energy-efficiency enhancements could be achieved by lowering the power consumption of integrated circuits, using antenna diversity or even with an association of both strategies. This paper compares two wideband RF front-end architectures, based on conventional low-noise amplifiers (LNA) and low-noise transconductance amplifiers (LNTA) with N-path filters, operating with three transmission schemes: single antenna, antenna selection and singular value decomposition beamforming. Our results show that the energy-efficiency behavior varies depending on the required communication link conditions, distance between nodes and metrics from the front-end receivers. For short-range scenarios, LNA presents the best performance in terms of energy-efficiency mainly due to its very low power consumption. With the increasing of the communication distance, the very low noise figure provided by N-path LNTA-based architectures outperforms the power consumption issue, yielding higher energy-efficiency for all transmission schemes. In addition, the selected front-end architecture depends on the number of active antennas at the receiver. Hence, we can observe that low noise figure is more important with a few active antennas at the receiver, while low power consumption becomes more important when the number of active RF chains at the receiver increases. [ABSTRACT FROM AUTHOR]

We evaluate the effective secrecy throughput (EST) of multiple-input-multiple-output relay-assisted free-space optical communication, where legitimate nodes (Alice, Relays, and Bob) communicate in the presence of multiple Eavesdroppers (Eves) under two different weather conditions, namely clear weather with weak turbulence and light fog with strong turbulence. We consider multiple paths between Alice and Bob, each composed of multiple relays, which are capable of operating under: (i) adaptive scheme with selective relaying, where Alice possesses instantaneous channel state information (CSI) of the legitimate channels and selects the optimum path to Bob; (ii) fixed-rate scheme with all-active relaying, where instantaneous CSI is not available and the information is transmitted through all paths. Our results indicate that both schemes benefit from multiple hops, while the use of multiple paths benefits only the adaptive scheme. Furthermore, we also show that the effects of the weather conditions become more relevant with the increase of the distance between Alice and Bob, and that such deterioration in performance can be decreased through the use of relaying nodes. [ABSTRACT FROM AUTHOR]

Wireless Sensors Networks (WSNs) are an essential element of the Internet of Things (IoT), and are the main producers of big data. Collecting a huge amount of data produced by a resource-constrained network is a very difficult task, presenting several challenges. Big data gathering involves not only periodic data sensing, but also the forwarding of queries and commands to the network. Conventional network protocols present unfeasible strategies for large-scale networks and may not be directly applicable to IoT environments. Information-Centric Networking is a revolutionary paradigm that can overcome such big data gathering challenges. In this work, we propose a soft-state information-centric protocol, ICENET (Information Centric protocol for sEnsor NETworks), for big data gathering in large-scale WSNs. ICENET can efficiently propagate user queries in a wireless network by using a soft-state recovery mechanism for lossy links. The scalability of our solution is evaluated in different network scenarios. Results show that the proposed protocol presents approximately 84% less overhead and a higher data delivery rate than the CoAP (Constrained Application Protocol), which is a popular protocol for IoT environments. [ABSTRACT FROM AUTHOR]

Presents corrections made to the paper, ?Energy Efficiency-Spectral Efficiency Trade-Off of Transmit Antenna Selection? (Rayel, O.K., et al; IEEE Trans. Commun., vol. 62, no. 12, pp. 4293?4303, Dec. 2014). [ABSTRACT FROM PUBLISHER]

Millimeter-wave (mmWave) radars attain high resolution without compromising privacy while being unaffected by environmental factors such as rain, dust, and fog. This study explores the challenges of using mmWave radars for the simultaneous detection of people and small animals, a critical concern in applications like indoor wireless energy transfer systems. This work proposes innovative methodologies for enhancing detection accuracy and overcoming the inherent difficulties posed by differences in target size and volume. In particular, we explore two distinct positioning scenarios that involve up to four mmWave radars in an indoor environment to detect and track both humans and small animals. We compare the outcomes achieved through the implementation of three distinct data-fusion methods. It was shown that using a single radar without the application of a tracking algorithm resulted in a sensitivity of 46.1%. However, this sensitivity significantly increased to 97.10% upon utilizing four radars using with the optimal fusion method and tracking. This improvement highlights the effectiveness of employing multiple radars together with data fusion techniques, significantly enhancing sensitivity and reliability in target detection.