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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]

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]

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]

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]

We consider the use of spatial diversity to improve the performance of analog joint source-channel coding in wireless fading channels. The communication system analyzed in this paper consists of discrete-time all-analog-processing joint source-channel coding where Maximum Likelihood (ML) and Minimum Mean Square Error (MMSE) detection are employed. By assuming a fast-fading Rayleigh channel, we show that MMSE performs much better than ML at high Channel Signal-to-Noise Ratios (CSNR) in single-antenna wireless systems. However, such performance gap can be significantly reduced by using multiple receive antennas, thus making low complexity ML decoding very attractive in the case of receive diversity. Moreover, we show that the analog scheme can be considerably robust to imperfect channel estimation. In addition, as an alternative to multiple antennas, we also consider spatial diversity through cooperative communications, and show that the application of the Amplify-and-Forward (AF) protocol with single antenna nodes leads to similar results than when two antennas are available at the receiver and Maximal Ratio Combining (MRC) is applied. Finally, we show that the MMSE implementation of the analog scheme performs very close to the unconstrained capacity of digital schemes using scalar quantization, while its complexity is much lower than that of capacity-approaching digital systems. [ABSTRACT FROM PUBLISHER]

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]

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]

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]

We compare the energy efficiency of some transmission schemes in wireless sensor networks. By constraining the system to end-to-end throughput requirements, we assume that the nodes in multi-hop and cooperative schemes operate at a spectral efficiency which is twice that of the single-hop transmission. By taking into account the energy consumption of the RF circuitry, we show that cooperation may be considerably more energy efficient than non-cooperative schemes even in small transmission ranges, specially if a feedback channel is available. [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]

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]

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]

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]