Search

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]

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]

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]

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]

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]