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Hirley Alves

Publications and source records attributed to Hirley Alves.

126 records · Page 7Linked to original sources

Ultra-Reliable Cooperative Short-Packet Communications with Wireless Energy Transfer

We analyze a cooperative wireless communication system with finite block length and finite battery energy, under quasi-static Rayleigh fading. Source and relay nodes are powered by a wireless energy transfer (WET) process, while using the harvested energy to feed their circuits, send pilot signals to estimate channels at receivers, and for wireless information transmission (WIT). Other power consumption sources beyond data transmission power are considered. The error probability is investigated under perfect/imperfect channel state information (CSI), while reaching accurate closed-form approximations in ideal direct communication system setups. We consider ultra-reliable communication (URC) scenarios under discussion for the next fifth-generation (5G) of wireless systems. The numerical results show the existence of an optimum pilot transmit power for channel estimation, which increases with the harvested energy. We also show the importance of cooperation, even taking into account the multiplexing loss, in order to meet the error and latency constraints of the URC systems.

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On the Performance of Ultra-Reliable Decode and Forward Relaying Under the Finite Blocklength

In this paper, we examine the performance of the decode-and-forward (DF) relaying protocols with finite blocklength (FB). We provide the overall outage probability of three distinct DF relaying protocols, where the channels are assumed to be quasi static Rayleigh fading. More importantly, we derive the closed form expressions of the outage probability in the three relaying scenarios. We illustrate protocols where the cooperative communications outperform the direct transmission (DT). In addition, we compare the operating efficiency of the cooperative schemes in the ultra-reliable (UR) region.

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On the Effective Capacity of MTC Networks in the Finite Blocklength Regime

This paper analyzes the effective capacity (EC) of delay constrained machine type communication (MTC) networks operating in the finite blocklength (FB) regime. First, we derive a closed-form mathematical approximation for the EC in Rayleigh block fading channels. We characterize the optimum error probability to maximize the concave EC function and study the effect of SINR variations for different delay constraints. Our analysis reveals that SINR variations have less impact on EC for strict delay constrained networks. We present an exemplary scenario for massive MTC access to analyze the interference effect proposing three methods to restore the EC for a certain node which are power control, graceful degradation of delay constraint and joint compensation. Joint compensation combines both power control and graceful degradation of delay constraint, where we perform maximization of an objective function whose parameters are determined according to delay and SINR priorities. Our results show that networks with stringent delay constraints favor power controlled compensation and compensation is generally performed at higher costs for shorter packets.

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Ultra-Reliable Short-Packet Communications with Wireless Energy Transfer

We analyze and optimize a wireless system with energy transfer in the downlink and information transfer in the uplink, under quasi-static Nakagami-m fading. We consider ultra-reliable communication scenarios representative of the fifth-generation of wireless systems, with strict error and latency requirements. The error probability and delay are investigated, and an approximation for the former is given and validated through simulations. The numerical results demonstrate that there are optimum numbers of channels uses for both energy and information transfer for a given message length.

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Ultra Reliable Short Message Relaying with Wireless Power Transfer

We consider a dual-hop wireless network where an energy constrained relay node first harvests energy through the received radio-frequency signal from the source, and then uses the harvested energy to forward the source's information to the destination node. The throughput and delay metrics are investigated for a decode-and-forward relaying mechanism at finite blocklength regime and delay-limited transmission mode. We consider ultra-reliable communication scenarios under discussion for the next fifth-generation of wireless systems, with error and latency constraints. The impact on these metrics of the blocklength, information bits, and relay position is investigated.

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Ultra Reliable Communication via Optimum Power Allocation for Type-I ARQ in Finite Block-Length

We analyze the performance of the type-I automatic repeat request (ARQ) protocol with ultra-reliability constraints. First, we show that achieving a very low packet outage probability by using an open loop setup is a difficult task. Thus, we introduce the ARQ protocol as a solution for achieving the required low outage probabilities for ultra reliable communication. For this protocol, we present an optimal power allocation scheme that would allow us to reach any outage probability target in the finite block-length regime. We formulate the power allocation problem as minimization of the average transmitted power under a given outage probability and maximum transmit power constraint. By utilizing the Karush-Kuhn-Tucker (KKT) conditions, we solve the optimal power allocation problem and provide a closed form solution. Next, we analyze the effect of implementing the ARQ protocol on the throughput. We show that by using the proposed power allocation scheme we can minimize the loss of throughput that is caused from the retransmissions. Furthermore, we analyze the effect of the feedback delay length in our scheme.

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Effects of Relay Selection Strategies on the Spectral Efficiency of Wireless Systems with Half- and Full-duplex Nodes

This work proposes an analytical framework to study how relay selection strategies perform in half- and full-duplex deployments by combining renewal theory and stochastic geometry. Specifically, we assume that the network nodes -- operating in either half- or full-duplex mode -- are scattered according to a two-dimensional homogeneous Poisson point process to compute the relay selection cost by using a semi-Markov process. Our results show: ($i$) fixed relay outperforms the reactive option in either cases, ($ii$) the performance of both reactive and fixed relay strategies depends on the self-interference attenuation in full-duplex scenarios, evincing when they outperform the half-duplex option, and ($iii$) the reactive relay selection suffers from selecting relays at hop basis, while the fixed relay selection benefits most from the full-duplex communication.

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Storage Management in Modern Electricity Power Grids

This letter introduces a method to manage energy storage in electricity grids. Starting from the stochastic characterization of electricity generation and demand, we propose an equation that relates the storage level for every time-step as a function of its previous state and the realized surplus/deficit of electricity. Therefrom, we can obtain the probability that, in the next time-step: (i) there is a generation surplus that cannot be stored, or (ii) there is a demand need that cannot be supplied by the available storage. We expect this simple procedure can be used as the basis of electricity self-management algorithms in micro-level (e.g. individual households) or in meso-level (e.g. groups of houses).

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Decision Error Probability in a Two-stage Communication Network for Smart Grids with Imperfect Data Links

This paper analyzes a scenario where the distribution system operator needs to estimate whether the average power demand in a given period is above a predetermined threshold using an 1-bit memoryless scheme. Specifically, individual smart-meters periodically monitor the average power demand of their respective households to inform the system operator if it is above a predetermined level using only a 1-bit signal. The communication link between the meters and the operator occurs in two hops and is modeled as binary symmetric channels. The first hop connects individual smart meters to their corresponding aggregator, while the second connects different aggregators to the system operator. A decision about the power demand also happens in two stages based on the received information bit. We consider here three decision rules: AND, OR and MAJORITY. Our analytical results indicate the circumstances (i.e. how frequent the meters experience the consumption above the defined threshold) and the design setting (i.e. decision rules) that a low error probability can be attained. We illustrate our approach with numerical results from actual daily consumption from 12 households and 3 aggregators.

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Average Error Probability in Wireless Sensor Networks with Imperfect Sensing and Communication for Different Decision Rules

This paper presents a framework to evaluate the probability that a decision error event occurs in wireless sensor networks, including sensing and communication errors. We consider a scenario where sensors need to identify whether a given event has occurred based on its periodic, noisy, observations of a given signal. Such information about the signal needs to be sent to a fusion center that decides about the actual state at that specific observation time. The communication links -- single- or multi-hop -- are modeled as binary symmetric channels, which may have different error probabilities. The decision at the fusion center is based on OR, AND, K-OUT-OF-N and MAJORITY Boolean operations on the received signals associated to individual sensor observations. We derive closed-form equations for the average decision error probability as a function of the system parameters (e.g. number of sensors and hops) and the input signal characterization. Our analyses show the best decision rule is closely related to the frequency that the observed events occur and the number of sensors. In our numerical example, we show that the AND rule outperforms MAJORITY if such an event is rare and there is only a handful number of sensors. Conversely, if there is a large number of sensors or more evenly distributed event occurrences, the MAJORITY is the best choice. We further show that, while the error probability using the MAJORITY rule asymptotically goes to 0 with increasing number of sensors, it is also more susceptible to higher channel error probabilities.

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Maximizing the Link Throughput between Smart-meters and Aggregators as Secondary Users under Power and Outage Constraints

This paper assesses the communication link from smart meters to aggregators as (unlicensed) secondary users that transmit their data over the (licensed) primary uplink channel. The proposed scenario assumes: (i) meters' and aggregators' positions are fixed so highly directional antennas are employed, (ii) secondary users transmit with limited power in relation to the primary, (iii) meters' transmissions are coordinated to avoid packet collisions, and (iv) the secondary links' robustness is guaranteed by an outage constraint. Under these assumptions, the interference caused by secondary users in both primary (base-stations) and other secondary users can be neglected. As unlicensed users, however, meter-aggregator links do experience interference from the mobile users of the primary network, whose positions and traffic activity are unknown. To cope with this uncertainty, we model the mobile users spatial distribution as a Poisson point process. We then derive a closed-form solution for the maximum achievable throughput with respect to a reference secondary link subject to transmit power and outage constraints. Our numerical results illustrate the effects of such constraints on the optimal throughput, evincing that more frequent outage events improve the system performance in the scenario under study. We also show that relatively high outage probabilities have little effect on the reconstruction of the average power demand curve that is transmitted from the smart-meter to the aggregator.

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Throughput Maximization in Multi-Hop Wireless Networks under Secrecy Constraint

This paper analyzes the throughput of industrial communication networks under a secrecy constraint. The proposed scenario is composed by sensors that measure some relevant information of the plant that is first processed by aggregator node and then sent to the control unit. The sensor measurements, their communication with the aggregetor and the information processing are all assumed perfect. To reach the control unit, the message may travel through relay nodes, forming a multi-hop, wireless link. At every hop, eavesdropper nodes attempt to acquire the messages transmitted through the legitimate link. The communication design problem posed here is how to maximize the multi-hop throughput from the aggregator to the control unit by finding the best combination of relay positions (i.e. hop length: short or long) and coding rates (i.e. high or low spectral efficiency) so that the secrecy constraint is satisfied. Using a stochastic-geometry approach, we show that the optimal choice of coding rate depends only on the path- loss exponent and is normally high while greater number of shorter hops are preferable to smaller number of longer hops. For the scenarios of interest, we prove that the optimal throughput subject to the secrecy constraint achieves the unconstrained optimal performance if a feasible solution exists.

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Enhanced Transmit Antenna Selection Scheme for Secure Throughput Maximization Without CSI at the Transmitter and its Applications on Smart Grids

This paper addresses the establishment of secure communication links between smart-meters (Alice) and an aggregator (Bob) in the presence of an eavesdropper (Eve). The proposed scenario assumes: (i) MIMOME wiretap channel; (ii) transmit antenna selection at the Alice; (iii) no channel state information at the transmitter; (iv) fixed Wyner codes; and (v) guarantee of secure throughput by both quality of service and secrecy outage constraints. We propose a simple protocol to enhance security via transmit antenna selection, and then assess its performance in closed-form by means of secrecy outage and successful transmission probabilities. We assume these probabilities are our constraints and then maximize the secure throughput, establishing a security-reliability trade-off for the proposed scenario. Our numerical results illustrate the effect of this trade-off on the secure throughput as well as on the number of antennas at Alice, Bob and Eve. Interestingly, a small sacrifice in reliability allows secrecy enhancement in terms of secure bps/Hz. We apply this idea in our smart grid application to exemplify that, although Eve may acquire some samples of the average power demand of a household, it is not enough to properly reconstruct such curve.

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Contention-based Geographic Forwarding Strategies for Wireless Sensors Networks

This paper studies combined relay selection and opportunistic geographic routing strategies for autonomous wireless sensor networks where transmissions occur over multiple hops. The proposed solution is built upon three constituent parts: (i) relay selection algorithm, (ii) contention resolution mechanism, and (iii) geographic forwarding strategy. Using probability generating function and spatial point process as the theoretic background, we propose an auction-based algorithm for selecting the relay node that relies on the network topology as side-information. Our results show that geographic solutions that iteratively exploit the local knowledge of the topology to ponder the algorithm operation outperforms established random approaches.

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On the Performance of Secure Full-Duplex Relaying under Composite Fading Channels

We assume a full-duplex (FD) cooperative network subject to hostile attacks and undergoing composite fading channels. We focus on two scenarios: \textit{a)} the transmitter has full CSI, for which we derive closed-form expressions for the \textit{average secrecy rate}; and \textit{b)} the transmitter only knows the CSI of the legitimate nodes, for which we obtain closed-form expressions for the \textit{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.

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On the Secrecy of Interference-Limited Networks under Composite Fading Channels

This paper deals with the secrecy capacity of the radio channel in interference-limited regime. We assume that interferers are uniformly scattered over the network area according to a Point Poisson Process and the channel model consists of path-loss, log-normal shadowing and Nakagami-m fading. Both the probability of non-zero secrecy capacity and the secrecy outage probability are then derived in closed-form expressions using tools of stochastic geometry and higher-order statistics. Our numerical results show how the secrecy metrics are affected by the disposition of the desired receiver, the eavesdropper and the legitimate transmitter.

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Throughput Analysis of Cognitive Wireless Networks with Poisson Distributed Nodes Based on Location Information

This paper provides a statistical characterization of the individual achievable rates in bits/s/Hz and the spatial throughput of bipolar Poisson wireless networks in bits/s/Hz/m$^2$. We assume that all transmitters have a cognitive ability to know the distance to their receiver's closest interferers so they can individually tune their coding rates to avoid outage events for each spatial realization. Considering that the closest interferer approximates the aggregate interference of all transmitters treated as noise, we derive closed-form expressions for the probability density function of the achievable rates under two decoding rules: treating interference as noise, and jointly detecting the strongest interfering signals treating the others as noise. Based on these rules and the bipolar model, we approximate the expected maximum spatial throughput, showing the best performance of the latter decoding rule. These results are also compared to the reference scenario where the transmitters do not have cognitive ability, coding their messages at predetermined rates that are chosen to optimize the expected spatial throughput -- regardless of particular realizations -- which yields outages. We prove that, when the same decoding rule and network density are considered, the cognitive spatial throughput always outperforms the other option.

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On the Fly Self-Organized Base Station Placement

In this paper, we address the deployment of base stations (BSs) in a one-dimensional network in which the users are randomly distributed.In order to take into account the users' distribution to optimally place the BSs we optimize the uplink MMSE sum rate. Moreover, given a massive number of antennas at the BSs we propose a novel random matrix theory-based technique so as to obtain tight approximations for the MMSE sum rate in the uplink. We investigate a cooperative (CP) scenario where the BSs jointly decode the messages and a non-cooperative (NCP) scheme in which the BS can only decode its own users. Our results show that the CP strategy considerably outperforms the NCP case. Moreover, we show that there exists a trade off in the BS deployment regarding the position of each BS. Thus, through location games we can optimize the position of each BS in order to maximize the system performance.

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