Abstract-In this paper, we analyze the outage probability and diversity order of opportunistic relay selection in a scenario based on decode and forward and where the available channel state information (CSI) is outdated. The study is conducted analytically by obtaining a closed-form expression for the outage probability, which is dened as the probability that the instantaneous capacity is below a target value. We derive high-SNR approximations for the outage probability. By doing so, we demonstrate that the diversity order of the system is reduced to 1 when CSI is outdated, being this behavior independent of the level of CSI accuracy. A physical explanation for this extreme loss of diversity is provided along with numerical results to support the analytical study.

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In this letter, we explore the combined use of spatial and multi-user diversity in a cellular system where channel state information is subject to delays in the feedback channel. First, we analytically derive the probability and cumulative density functions of the post-scheduling signal-to-noise ratio (SNR) for both a Single-Input Single-Output (SISO) and an Orthogonal Space-Time Block Coding (OSTBC) transmission schemes. Then, we obtain the closed-form expressions of the corresponding average system capacities. By evaluating those expressions, we analytically show that the OSTBC scheme is far less sensitive to delays in the feedback channel.

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In the last decade, the interest in Indoor Location Based Services (ILBS) has increased stimulating the development of Indoor Positioning Systems (IPS). In particular, ILBS look for positioning systems that can be applied anywhere in the world for millions of users, that is, there is a need for developing IPS for mass market applications. Those systems must provide accurate position estimations with minimum infrastructure cost and easy scalability to different environments. This survey overviews the current state of the art of IPSs and classifies them in terms of the infrastructure and methodology employed. Finally, each group is reviewed analysing its advantages and disadvantages and its applicability to mass market applications.

Wastewater treatment plants (WWTPs) form an industry whose main goal is to reduce water’s pollutant products, which are harmful to the environment at high concentrations. In addition, regulations are applied by administrations to limit pollutant concentrations in effluent. In this context, control strategies have been adopted by WWTPs to avoid violating these limits; however, some violations still occur. For that reason, this work proposes the deployment of an artificial neural network (ANN)-based soft sensor in which a Long-Short Term Memory (LSTM) network is used to generate predictions of nitrogen-derived components, specifically ammonium ( S N H ) and total nitrogen ( S N t o t ). S N t o t is a limiting nutrient and can therefore cause eutrophication, while nitrogen in the S N H form is toxic to aquatic life. These parameters are used by control strategies to allow actions to be taken in advance and only when violations are predicted. Since predictions complement control strategies, the evaluation of the ANN-based soft sensor was carried out using the Benchmark Simulation Model N.2. (BSM2) and three different control strategies (from low to high control complexity). Results show that our proposed method is able to predict nitrogen-derived products with good accuracy: the probability of detecting violations of BSM2’s limits is 86%–94%. Moreover, the prediction accuracy can be improved by calibrating the soft sensor; for example, perfect prediction of all future violations can be achieved at the expense of increasing the false positive rate.

Abstract-Orthogonal random beamforming (ORB) constitutes a mean to exploit spatial multiplexing and multi-user diversity (MUD) gains in multi-antenna broadcast channels. To do so, as many random beamformers as transmit antennas (M ) are generated and on each beam the user experiencing the most favorable channel conditions is scheduled. Whereas for a large number of users the sum-rate of ORB exhibits an identical growth rate as that of dirty paper coding, performance in sparse networks (or in networks with an uneven spatial distribution of users) is known to be severely impaired. To circumvent that, in this paper we modify the scheduling process in ORB in order to select a subset out of the M available beams. We propose several beam selection algorithms and assess their performance in terms of sum-rate and aggregated throughput (i.e., rate achieved with practical modulation and coding schemes), along with an analysis of their computational complexity. Since ORB schemes require partial channel state information (CSI) to be fed back to the transmitter, we finally investigate the impact of CSI quantization on system performance. More specifically, we prove that most of the MUD can be still exploited with very few quantization bits and we derive a beam selection approach trading-off system performance vs. feedback channel requirements.Index Terms-Orthogonal Random Beamforming (ORB), beam selection, sparse networks, opportunistic scheduling, Multiuser Diversity (MUD), broadcast channel, feedback quantization.

An open issue still to be addressed in low‐power lossy networks (LLNs) is how the application requirements, the available transport services, the network layer routes, and the data link‐layer resources are mapped efficiently. This can be explained by the fact that, in most LLNs, link‐layer resources cannot be easily managed; this results in a best effort IP layer, and traffic engineering performed solely through flow control at the transport layer. The new IEEE802.15.4e standard defines a link‐layer mechanism by which motes in the network synchronise and communicate by following a schedule. Each slot in that schedule can be seen as an atomic link‐layer resource, which can be allocated to any arbitrary link in the network. The schedule can be built to match the bandwidth, latency and power requirements of each mote in the network. Managing that schedule is performed centrally in IEEE802.15.4e networks today. This paper explores a solution to achieve the same goal in a distributed manner. Specifically, we argue that this problem is very similar to traffic engineering on today's Internet. We show how multiprotocol label switching can be mapped to LLNs to manage the network's schedule. By using the completely fair distributed scheduler, we show by simulation how this novel link‐layer resource allocation scheme yields a proper distribution of end‐to‐end delays among the motes and an average throughput that achieves the 70% of the maximum possible throughput in the worst conditions tested. Copyright © 2013 John Wiley & Sons, Ltd.