We study the remote monitoring of two-state Markov sources over a shared wireless channel with destructive collisions. System performance is measured in terms of state estimation entropy (SEE) and state estimation error probability (SEEP), which quantify the receiver's uncertainty and decision error regarding the source state, respectively. We consider two transmission policies: a random strategy, where nodes access the channel independently of their state, and a reactive strategy, where transmissions occur only upon state changes. Our main contribution is a simple and explicit analytical characterization of the long-term average SEE and SEEP under both policies using a renewal–reward framework, alternative to the density evolution approach introduced in [1]. For random transmission, both metrics admit closed-form representations as expectations over the geometric steady-state age-of-information distribution. For reactive transmission, we show that estimation uncertainty and error accumulate exclusively through collision events, and derive their long-term averages via a collision-indexed Markov reward recursion.

Goal-oriented communication entails the timely transmission of updates related to a specific goal defined by the application. In a distributed setup with multiple sensors, each individual sensor knows its own observation and can determine its freshness, as measured by Age of Incorrect Information (AoII). This local knowledge is suited for distributed medium access, where the transmission strategies have to deal with collisions. We present Dynamic Epistemic Logic for Tracking Anomalies (DELTA), a medium access protocol that limits collisions and minimizes AoII in anomaly reporting over dense networks. Each sensor knows its own AoII, while it can compute the belief about the AoII for all other sensors,based on their Age of Information (AoI), which is inferred from the acknowledgments. This results in a goal-oriented approach based on dynamic epistemic logic emerging from public information. We analyze the resulting DELTA protocol both from a theoretical standpoint and with Monte Carlo simulations, showing that it is significantly more efficient and robust than classical random access, while outperforming state-of-the-art scheduled schemes by at least 30%, even with imperfect feedback.

Orthogonal time frequency space (OTFS) modulation has been proposed recently as a new waveform in the context of doubly-selective multi-path channels. This article proposes a novel pilot design that improves OTFS's spectral efficiency (SE) while reducing its peak-to-average power ratio (PAPR). Instead of adopting an embedded data-orthogonal pilot for channel estimation, our scheme relies on Chu sequences superimposed to data symbols. We optimize the construction by investigating the best energy split between pilot and data symbols. Two equalizers, and an iterative channel estimation and equalization procedure are considered. We present extensive numerical results of relevant performance metrics, including the normalized mean squared error of the estimator, bit error rate, PAPR and SE. Our results show that, while the embedded pilot scheme estimates the channel more accurately, our approach yields a better tradeoff by achieving much higher spectral efficiency and lower PAPR.

Age of Incorrect Information (AoII) is particularly relevant in systems where real time responses to anomalies are required, such as natural disaster alerts, cybersecurity warnings, or medical emergency notifications. Keeping system control with wrong information for too long can lead to inappropriate responses. In this paper, we study the Peak AoII (PAoII) for multisource status reporting by independent devices over a collision channel, following a zero-threshold ALOHA access where nodes observing an anomaly immediately start transmitting about it. If a collision occurs, nodes reduce the transmission probability to allow for a resolution. Finally, wrong or lost feedback messages may lead a node that successfully updated the destination to believe a collision happened. The PAoII for this scenario is computed in closed-form. We are eventually able to derive interesting results concerning the minimization of PAoII, which can be traded against the overall goodput and energy efficiency, but may push the system to the edge of congestion collapse.

The ability to collect via satellite status updates from vessels is a key enabler for a number of maritime applications. In these settings, maintaining an up to date perception of the state of a ship is paramount, yet challenging due to the large number of vessels in the satellite coverage. To tackle the problem, we study the impact of different transmission policies, capturing system performance in terms of age of incorrect information (AoII). Modelling channel contention as slotted ALOHA, we consider a benchmark inspired by the de-facto AIS/VDES transmission standard in which ships periodically report their state, and compare it to solutions that adapt the transmission probability to current ship-to-satellite channel conditions and to relevant changes in the ship state. By means of a Markovian analysis, we derive closed-form expressions for the average AoII, and discuss the performance in settings of representative of practical conditions. The potential of solutions that tie channel access to the evolution of the process to be tracked clearly emerges. The work aims at stimulating further research in this domain, having in mind future enhancements of ship communication standards.

Efficient remote monitoring of distributed sources is essential for many Internet of Things (IoT) applications. This work studies the uncertainty at the receiver when tracking two-state Markov sources over a slotted random access channel without feedback, using the conditional entropy as a performance indicator, and considering the last received value as current state estimate. We provide an analytical characterization of the metric, and evaluate three access strategies: (i) maximizing throughput, (ii) transmitting only on state changes, and (iii) minimizing uncertainty through optimized access probabilities. Our results reveal that throughput optimization does not always reduce uncertainty. Moreover, while reactive policies are optimal for symmetric sources, asymmetric processes benefit from mixed strategies allowing transmissions during state persistence.

Real-time applications in the Internet of things (IoT) commonly require to schedule status updates from remote sensors to minimize age of information (AoI), a metric that captures the freshness of received data. Oftentimes, this problem is tackled assuming that sensors operate over an indefinite time horizon and can decide when to transmit data leveraging the knowledge of the current AoI level at the receiver, even when the communication channel is unreliable. Such a modeling approach, however, neglects some key aspects of most practical IoT systems, where the frequency of status reporting is limited due to resource constraints, such as energy limitations, and tracking the outcome of the updates would require additional consumption of resources to acquire a feedback. In this paper, instead, we investigate the optimal schedule of updates over a finite time horizon for a resource-constrained sensor that is allowed to perform a limited number of updates. We discuss the role of the feedback from the receiver, and whether it is convenient to ask for it whenever this causes additional energy consumption and consequently allows the transmission of a lower number of updates. We analytically identify regions for the feedback cost and the reliability of the channel where making use of feedback may or may not be beneficial. Our study covers both thegenerate-at-willcase, in which a sensor can produce a fresh reading whenever it wants to communicate with the receiver, and anexogenoussetting, where the transmitter cannot decide when new status updates are produced. The results highlight some interesting trade-offs, providing useful design hints for the protocol operation of IoT remote sensing systems.

We investigate the age of information (AoI) in a scenario where energy-harvesting devices send status updates to a gateway following the slotted ALOHA protocol and receive no feedback. We let the devices adjust the transmission probabilities based on their current battery level. Using a Markovian approach, we derive analytically the average AoI. We further provide an approximate analysis for accurate and easy-to-compute approximations of both the average AoI and the age-violation probability (AVP), i.e., the probability that the AoI exceeds a given threshold. We also analyze the average throughput. Via numerical results, we investigate two baseline strategies: transmit a new update whenever possible to exploit every opportunity to reduce the AoI, and transmit only when sufficient energy is available to increase the chance of successful decoding. The two strategies are beneficial for low and high update-generation rates, respectively. We show that an optimized policy that balances the two strategies outperforms them significantly in terms of both AoI metrics and throughput. Finally, we show the benefit of decoding multiple packets in a slot using successive interference cancellation and adapting the transmission probability based on both the current battery level and the time elapsed since the last transmission.

Data freshness is extremely important for real-time applications and generally measured with age of information (AoI). Related studies typically assume that fresh data can be generated at any time. However, in industrial Internet of Things (IIoT) applications, such as alerting, monitoring, or task-oriented operations, data generation is often exogenous and occurs within a finite window. This motivates our analysis, where we investigate AoI-minimizing scheduling for status updates from an IIoT source that generates fresh data only at random intervals. We differentiate between infinite and finite horizons, with the latter being more aligned with IIoT tasks. For each scenario, we examine both agnostic (predefined and unchangeable) and source-aware scheduling, based on the probability of fresh data generation and the duty cycle. We provide a tight bound for source-aware scheduling in the infinite-horizon case and exact expressions for the other scenarios. We assess the increase in AoI from sporadic data generation, finding worst-case factors of 3 for agnostic scheduling and 2 for source-aware scheduling. However, these estimates are pessimistic when the data generation probability is at least an order of magnitude higher than the duty cycle. In such cases, the AoI increase is less than 20% for agnostic scheduling and almost negligible for source-aware scheduling.

We evaluate a modification of irregular repetition slotted ALOHA (IRSA) involving intermediate decoding and early transmission termination by some nodes, upon their decoding success. This is meant to avoid unnecessary transmissions, thereby reducing energy consumption. We expect this to be particularly useful at low loads, where most transmissions can be avoided as they do not often result in a collision and are therefore redundant. To validate this proposal, we observe that most of the literature related to IRSA considers an asymptotic heavily loaded regime; thus, we also present a model of energy consumption and success probability for frames of limited length and low offered loads. Thanks to our analysis, also confirmed by simulation, we are able to show that the proposed technique is able to reduce IRSA energy consumption by minimizing transmissions, while preserving performance gains over standard ALOHA. For example, we are able to get a 33% energy saving at offered loads around 10% without affecting throughput.

The rapid growth of loT applications in which a large number of devices need to deliver information to a central monitor in a timely fashion has focused attention on the age of information performance of random access protocols. This paper provides the first study of one such strategy, Frame Asynchronous Coded Slotted ALOHA (FA-CSA) Through de-tailed network simulations, we compare its performance to a benchmark in the field, namely Irregular Repetition Slotted ALOHA (IRSA). The results show that FA-CSA achieves fresher information on average compared to IRSA, especially at low to moderate channel loads. Additionally, the study sheds light on the implications of asynchrony in access protocols, particularly in the context of loT applications with strict information freshness requirements.

In the context of Vehicle-to-Everything (V2X) networks, semantic metrics such as the Age of Information (AoI) have emerged as alternatives to conventional performance metrics. This has prompted a re-evaluation of well-established channel access protocols such as Semi-Persistent Scheduling (SPS) and Carrier-Sense Multiple Access with Collision Avoidance (CSMA/CA) from the perspective of these newly-introduced metrics. In parallel to this trend, new protocols such as Irregular Repetition Slotted ALOHA (IRSA) are proposed for application in V2X communication. In this paper, we investigate the AoI performance of IRSA in the context of V2X communication, by using SPS as a benchmark. The provided comparison indicates that, while SPS can achieve higher throughput than IRSA, IRSA results in a notably lower mean AoI and reduced age violation probability in certain operation regimes. These observations are of particular relevance to safety-related applications for autonomous driving, where the channel access protocols are required to support the broadcast of Cooperative Awareness Messages (CAMs) carrying time-sensitive status updates.

We focus on a system in which a set of two-state Markov sources report status update to a common receiver over a shared wireless channel. Inspired by practical IoT networks, we consider three variations of ALOHA as medium access protocol: i) a random approach in which a source transmits regardless of its status, ii) a reactive scheme in which updates are sent only when a source changes state, and iii) a hybrid solution which blends the two possibilities. We consider different criteria to capture the ability of the receiver to maintain an accurate perception of the tracked processes: average age of incorrect information (AoII), probability of missed detection (i.e., of not detecting a source transition), and average duration of intervals over which the receiver lingers with erroneous knowledge. We provide closed form analytical expressions for all the metrics, highlighting non-trivial trade-offs and providing useful protocol design hints.

Several actuation choices in the Internet of things (IoT) require state information to be up-to-date. In this context, the choice between local processing and offloading to a more powerful remote server can have a significant impact on data freshness. Local processing is indeed typically less reliable due to limited computing power and may require multiple attempts, which can result in data becoming stale. Conversely, remote (i.e., edge/cloud) processing can be more reliable, yet entail longer response times due to data transmission to an external server, possibly performing processor sharing with other tasks. The optimal balance depends on the specific system conditions, especially on the congestion at the remote server, and is in general non-trivial. We explore this tradeoff through a mathematical model, and argue about the derivation of a freshness-efficient local vs. remote split of requests, providing insights on the role played by reliability and latency in selecting the optimal strategy.

We examine the age of information (AoI) of a status update system that incorporates energy harvesting and uses the slotted ALOHA protocol. We derive analytically the average AoI and the probability that the AoI exceeds a given threshold. Via numerical results, we investigate two strategies to minimize the age of information (AoI): transmitting a new update whenever possible to exploit every chance to reduce the AoI, and transmitting only when sufficient energy is available to increase the chance of successful delivery. The two strategies are beneficial for low and high update generation rates, respectively. However, an optimized approach that balances the two strategies outperforms them significantly in terms of both AoI and throughput.

We study a system in which terminals monitoring two-state Markov sources communicate towards a common receiver over a slotted ALOHA random access channel. We analyze the system performance in terms of state estimation entropy (SEE), which measures the uncertainty at the receiver about the sources’ state. Two channel access strategies are studied, one that is influenced by the source behaviour and one that is independent of it. By means of density evolution analysis, we show that the former can yield a remarkable reduction of the SEE.

Enabling real-time communication in Industrial Internet of Things (IIoT) networks is crucial to support autonomous, self-organized and re-configurable industrial automation for Industry 4.0 and the forthcoming Industry 5.0. In this paper, we consider a SIC-assisted real-time IIoT network, in which sensor nodes generate reports according to an event-generation probability that is specific for the monitored phenomena. The reports are delivered over a block-fading channel to a common Access Point (AP) in slotted ALOHA fashion, which leverages the imbalances in the received powers among the contending users and applies successive interference cancellation (SIC) to decode user packets from the collisions. We provide an extensive analytical treatment of the setup, deriving the Age of Information (AoI), throughput and deadline violation probability, when the AP has access to both the perfect as well as the imperfect channel-state information. We show that adopting SIC improves all the performance parameters with respect to the standard slotted ALOHA, as well as to an age-dependent access method. The analytical results agree with the simulation based ones, demonstrating that investing in the SIC capability at the receiver enables this simple access method to support timely and efficient information delivery in IIoT networks.

In this paper, we investigate the design and analysis of a novel hybrid optical wireless communication (OWC)/radio frequency (RF) solution suitable for massive machine-type communications (mMTC). We consider a two-tier network architecture where a massive collection of indoor OWC-based small cells, each consisting of low-cost Internet of Things (IoT) devices and an OWC access point, are connected to the network infrastructure via an outdoor low-power wide-area network (LP WAN). Both indoor OWC and outdoor LP WAN tiers of the mMTC system deploy the Slotted ALOHA (SA) random access protocol. For the proposed hybrid OWC/RF IoT system, we are interested in the error probability in the finite block-length regime, i.e., the probability that a short block-length data packet originating from an OWC-based IoT device is delivered at its nearest LP WAN base station. Based on the derived error probability expression, we present numerical results that indicate important insights into the design of an SA-based hybrid OWC/RF IoT system.

We study the dynamic behavior of frameless ALOHA, both in terms of throughput and age of information (AoI). In particular, differently from previous studies, our analysis accounts for the fact that the number of terminals contending the channel may vary over time, as a function of the duration of the previous contention period. The stability of the protocol is analyzed via a drift analysis, which allows us to determine the presence of stable and unstable equilibrium points. We also provide an exact characterization of the AoI performance, through which we determine the impact of some key protocol parameters, such as the maximum length of the contention period, on the average AoI. Specifically, we show that configurations of parameters that maximize the throughput may result in a degradation of the AoI performance.

We focus on a slotted ALOHA system without feedback, in which nodes transmit time-stamped updates to a common gateway. Departing from the classical generate-at-will model, we assume that each transmitter may not always have fresh information to deliver, and tackle the fundamental question of whether sending stale packets can be beneficial from an age-of-information standpoint. Leaning on a signal-flow-graph analysis of Markov processes the study reveals that, when packets can be lost due to channel impairments, retransmissions can indeed lower AoI for low generation rates of new information, although at a cost in terms of throughput.

Scheduling updates from remote sensors is a key task for the internet of things (IoT). In this context, the mathematical concept of age of information is often used to capture the freshness of received data. This is, in turn, relevant to optimize the frequency of the exchanges, especially for resource constrained (e.g., energy-limited) sensors. Most investigations on the subject assume that the transmitter can leverage knowledge of the age of information at the receiver side to decide when to send data, even when the communication channel is unreliable. In reality, tracking the outcome of the updates would require additional consumption of resources to acquire a feedback. We investigate the optimal schedule of updates over a finite time horizon for a resource-constrained sensor that is allowed to perform a limited number of updates, as typical of IoT devices. We discuss the role of the feedback from the receiver, and whether it is convenient to ask for it whenever this causes additional energy consumption and consequently allows the transmission of a lower number of updates. We analytically identify regions for the feedback cost and the reliability of the channel where making use of feedback may or may not be beneficial.

Terrestrial and satellite communication networks often rely on two-hop wireless architectures with an access channel followed by backhaul links. Examples include cloud-radio access networks (C-RAN) and low-Earth orbit (LEO) satellite systems. Furthermore, communication services characterized by the coexistence of heterogeneous requirements are emerging as key use cases. This article studies the performance of critical service (CS) and non-CS (NCS) for Internet-of-Things (IoT) systems sharing a grant-free channel consisting of radio access and backhaul segments. On the radio access segment, IoT devices send packets to a set of noncooperative access points (APs) using slotted ALOHA (SA). The APs then forward correctly received messages to a base station over a shared wireless backhaul segment adopting SA. We study first a simplified erasure channel model, which is well suited for satellite applications. Then, in order to account for terrestrial scenarios, the impact of fading is considered. Among the main conclusions, we show that orthogonal interservice resource allocation is generally preferred for NCS devices, while nonorthogonal protocols can improve the throughput and packet success rate of CS devices for both terrestrial and satellite scenarios.

Caching at the edge of wireless networks is a key technology to reduce traffic in the backhaul link. However, a concentrated amount of requests during peak-periods may cause the outage of the system, meaning that the network is not able to serve the whole set of demands. The outage probability is a fundamental metric to take into account during the network design. In this paper, we derive the analytical expression of the outage probability as a function of the total amount of users requests, library size, requests distribution, cache size and capacity constraints on the backhaul resources. In particular, we focus on a scenario where end-users have no direct connection to the master node which holds the complete library of content that can be requested. A general formulation of the outage is derived and studied for two relevant caching schemes, i.e. the random caching scheme and the most popular caching schemes. The exact closed form expressions presented in this paper provide useful insights on how requests, memory and resources can be balanced when the parameters of a cache-enabled network have to designed.

Age of information (AoI) is gaining attention as a valuable performance metric for many IoT systems, in which a large number of devices report time-stamped updates to a central gateway. This is the case, for instance, of remote sensing, monitoring, or tracking, with broad applications in the industrial, vehicular, and environmental domain. In these settings, AoI provides insights that are complementary to those offered by throughput or latency, capturing the ability of the system to maintain an up-to-date view of the status of each transmitting device. From this standpoint, while a good understanding of the metric has been reached for point-to-point links, relatively little attention has been devoted to the impact that link layer solutions employed in IoT systems may have on AoI. In particular, no result is available for modern random access protocols, which have recently emerged as promising solutions to support massive machine-type communications. To start addressing this gap we provide in this paper the first study of the AoI of a scheme in this family, namely irregular repetition slotted ALOHA (IRSA). By means of a Markovian analysis, we track the AoI evolution at the gateway, prove that the process is ergodic, and derive a compact closed form expression for its stationary distribution. Leaning on this, we compute exact formulations for the average AoI and the age violation probability. The study reveals non-trivial design trade-offs for IRSA and highlights the key role played by the protocol operating frame size. Moreover, a comparison with the performance of a simpler slotted ALOHA strategy highlights a remarkable potential for modern random access schemes in terms of information freshness.

Wireless random access protocols are attracting a revived research interest as a simple yet effective solution for machine-type communications. In the quest to improve reliability and spectral efficiency of such schemes, the use of multiple receivers has recently emerged as a promising option. We study the potential of this approach considering a population of users that transmit data packets following a simple slotted ALOHA policy to a set of uncoordinated relays (phase-1). These, in turn, independently forward - part of - what decoded towards a collecting sink (phase-2). For an on-off fading channel model, we provide exact expressions for phase-1 throughput and packet loss rate for an arbitrary number of relays, characterising the benefits of multi-receiver schemes. Moreover, a lower bound on the minimum amount of phase-2 resources needed to deliver all information collected at the relays is provided. The bound is proven to be achievable via random linear coding when no constraints in terms of latency are set, with an overhead that approaches zero with the inverse of the packet length. We complement our study discussing a family of simple forwarding policies that require no packet-level coding, and optimising their performance based on the amount of available phase-2 resources. The behaviour of both random linear coding and simplified policies is also characterised when receivers are equipped with finite buffers, revealing non-trivial tradeoffs.

Flanking traditional metrics such as throughput and reliability, age of information (AoI) is emerging as a fundamental tool to capture the performance of IoT systems. In this context, we focus on a setup in which a large number of nodes attempt delivery of time-stamped updates to a common destination over a shared channel, and investigate the ability of different grant-free access strategies to maintain fresh information at the receiver. Specifically, we derive for the first time an exact closed-form expression of the average AoI achieved by irregular repetition slotted ALOHA (IRSA), and compare its performance to that of a slotted ALOHA approach. Our analysis reveals the potential of modern random access schemes, and pinpoints some fundamental trade-offs, providing useful hints for proper system design.

In this paper, we study the coexistence of critical and non-critical Internet of Things (IoT) services on a grant-free channel consisting of radio access and backhaul segments. On the radio access segment, IoT devices send packets to access points (APs) over an erasure collision channel using the slotted ALOHA protocol. Then, the APs forward correctly received messages to a base station (BS) over a shared wireless backhaul segment, modeled as an erasure collision channel. The APs hence play the role of uncoordinated relays that provide space diversity and may reduce performance losses caused by collisions. Both non-orthogonal and inter-service orthogonal resource sharing are considered and compared. Throughput and reliability metrics are analyzed, and numerical results are provided to assess the performance trade-offs between critical and non-critical IoT services.

Asynchronous random access protocols have become attractive for several satellite applications of interest, reducing the complexity at the transmitter side while granting good performance. These schemes typically follow two paradigms, using either (i) spread spectrum techniques or (ii) replication of the transmitted packets to achieve time diversity. In both cases, the receiver employs successive interference cancellation to resolve collisions. In this paper we offer a comparison of the two approaches in a narrowband scenario, discussing the relevant use case of the upcoming ITU VDES standard for maritime communications.

Recent technological advancements are making the use of compact, low-cost, low-power mm-wave radars viable for providing environmental awareness in a number of applications, ranging from automotive to indoor mapping and radio resource optimisation. These emerging use-cases pave the road towards networks in which a large number of radar and broadband communications devices coexist, sharing a common spectrum band in a possibly uncoordinated fashion. Although a clear understanding of how mutual interference influences radar and communications performance is key to proper system design, the core tradeoffs that arise in such scenarios are still largely unexplored. In this paper, we provide results that help bridge this gap, obtained by means of an analytical model and extensive simulations. To capture the fundamental interactions between the two systems, we study mm-wave networks where pulsed radars coexist with communications devices that access the channel following an ALOHA policy. We investigate the effect of key parameters on the performance of the coexisting systems, including the network density, fraction of radar and communication nodes in the network, antenna directivity, and packet length. We quantify the effect of mutual interference in the coexistence scenario on radar detection and communication network throughput, highlighting some non-trivial interplays and deriving useful design tradeoffs.

In-band full-duplex is emerging as a promising solution to enhance throughput in wireless networks. Allowing nodes to simultaneously send and receive data over the same bandwidth can potentially double the system capacity, and a good degree of maturity has been reached for physical layer design, with practical demonstrations in simple topologies. However, the true potential of full-duplex at a system level is yet to be fully understood. In this paper, we introduce an analytical framework based on stochastic geometry that captures the behavior of large full-duplex networks implementing an asynchronous random access policy based on Aloha. Via exact expressions, we discuss the key tradeoffs that characterize these systems, exploring among the rest the role of transmission duration, imperfect self-interference cancellation, and fraction of full-duplex nodes in the network. We also provide protocol design principles, and our comparison with slotted systems sheds light on the performance loss induced by the lack of synchronism.

Recent advances in Random Access (RA), improving throughput and loss rates, make the usage of such technique particularly interesting to complement Demand Assigned Multiple Access (DAMA) channels for the return link of satellite systems. In this paper, a novel approach for the integration of the two access strategies aimed at transmission delay optimization is presented. An algorithm for DAMA and RA delay estimation is presented, and its accuracy shown by simulations. Furthermore, the benefits of the proposed integration concept are demonstrated with significant gains in delay and throughput in moderate to high load operating regions.

Cooperative techniques have been shown to significantly improve the performance of wireless networks. Despite being a mature technology in single communication link scenarios, their implementation in wider, and practical, networks poses several challenges which have not been fully identified and understood so far. In this paper, the implementation of cooperative communications in non-centralized ad hoc networks with sensing-based channel access is extensively discussed. Both analysis and simulation are employed to provide a clear understanding of the mutual influence between the link layer contention mechanism and relaying protocols. Results show that sensing-based channel access significantly hampers the effectiveness of cooperation by biasing the spatial distribution of available relays, and by inducing a level of spatial and temporal correlation of interference that diminishes the diversity improvement on which cooperative gains are founded. Moreover, the efficiency reduction entailed by several practical protocol issues related to carrier sense multiple access which are typically neglected in the literature is thoroughly investigated.

Cooperative Network-Coded Hybrid ARQ (Coop-NC HARQ) has recently been proposed as a smart way to improve Decode & Forward (D&F) relaying. According to this idea, cooperators send HARQ redundancy on behalf of a source coded together with a data packet intended for the destination they are helping and taken from their own queue. This paper applies for the first time such a technique in ad hoc networks with Multi-User Detection (MUD) capabilities, allowing several terminals to simultaneously act as relays. In this context, we introduce a novel communication paradigm that leverages network-coded retransmissions to allow more efficient data exchanges among all terminals involved in a cooperative process, enabling inter-relay communications as well. Simulation results show that the proposed solution offers important gains over D&F as well as Coop-NC HARQ in both single- and multi-hop networks in terms of throughput and energy consumption.

We present a novel power-efficient wireless sensor network for continuously monitoring and analyzing seismic vibrations with sensor nodes and forwarding the retrieved information with low-cost relay nodes to backend applications. The applied vibration sensing algorithms are derived from the DIN 4150-3 standard. All nodes in the network are battery-powered and equipped with an IEEE 802.15.4 compatible radio transceiver. The nodes communicate with each other by executing a novel power-efficient protocol stack, which provides all network functions required by the vibration-sensing application and uses a publish/subscribe messaging protocol for communicating between the network nodes and the backend applications. Results obtained in certification and field tests show that the proposed vibration-sensing solution is standard-compliant, and that the wireless vibration sensor network (WVSN) exhibits excellent performance in terms of packet delivery rate, latency, and power efficiency.

This paper explores the relationship between cooperation and two very different medium access strategies: CSMA (epitomized by IEEE 802.11 DCF) and one instance of TDMA (represented by IEEE 802.15.3). By cooperation we mean basic decode-and-forward relaying as well as more advanced forms thereof based on network coding. The essential features that make each system more or less suitable to support the potentially high performance gains of hybrid ARQ are analyzed and studied by means of extensive simulations. The discussion carried out in this paper shows that centralized systems are able to reap far higher gains from a cooperative paradigm than their distributed counterparts, and investigates in depth the reasons that lead to such different behaviors, prompting also some interesting insights for proper design of advanced hybrid ARQ protocols.

Past research has shown that Carrier Sense Multiple Access (CSMA) is not a particularly favorable environment for cooperative networks. This observation suggests that other medium access schemes, like scheduled TDMA, may enable cooperation to yield more substantial improvements over conventional techniques. From this point of view, a hybrid cooperative-network coding protocol (called Phoenix, and so far only proposed for CSMA) has been adapted for Personal Area Network communications. The improvements brought by cooperative-NC techniques in this setting have roughly doubled with respect to the CSMA scenario, with gains of over 20% with respect to standard cooperative systems.

A method is presented for efficiently and reliably routing data packets from a static information source to a mobile sink through a multi-hop wireless sensor network. While the source and all sensor nodes are located at fixed and known positions, the mobile sink estimates and tracks its location, speed, and acceleration with a Kalman filter. To reliably and timely route data packets, the source predicts the location of the mobile sink. The prediction is updated by receiving messages from the mobile sink, containing its current location, speed, and acceleration. These messages are sent only if the Euclidean norm of the error between the predicted state and the state estimated by the Kalman filter exceeds a pre-defined threshold. The control messages and the data packets are forwarded in a multi-hop fashion through the network using geographic routing. Simulation results demonstrate that the proposed scheme outperforms conventional routing protocols in terms of packet transfer reliability, latency, and energy efficiency.

In this paper, we propose a novel dynamic routing strategy called tunnel routing that enables efficient and resilient data forwarding from sensors to a destination in wireless sensor networks. Instead of establishing a single static path, tunnel routing identifies a set of trusted sensor nodes that form a tunnel between the source and the destination. Terminals in the tunnel cooperate with each other to reliably route data and to defend against compromised nodes that may maliciously drop or re-direct packets. To achieve this, not only do sensor terminals forward data, but also they act as support nodes, providing on-demand retransmissions in order to combat channel fading, and initializing multi-path data forwarding towards the destination in case they detect a misbehavior of a forwarding node. Simulation results demonstrate the advantages of the proposed scheme.

In this paper, we investigate the effectiveness of cooperative techniques in non-infrastructured ad hoc networks based on carrier sense access control. We point out, via analysis and detailed network simulations, that CSMA biases some fundamental statistics of geographical positioning of terminals available for cooperation. Not only may relay nodes refrain from cooperating due to the carrier sense mechanism, but also the spatial correlation of interference in the network is likely to compress potential cooperators within an area in the proximity of the source. Furthermore, our discussion highlights how issues that affect carrier sense based medium access strategies, such as hidden terminals, reduce the effectiveness of relaying strategies when implemented in large non-centralized networks. The combination of the aforementioned factors is shown to significantly diminish the performance gain granted by cooperative schemes widely studied in the literature from a theoretical perspective.

This paper introduces a novel MAC protocol for wireless networks, called Phoenix, that employs ideas from network coding to enhance decode and forward cooperation. A relay is allowed to code data of its own together with a corrupted packet during a retransmission at no additional cost in bandwidth. Therefore, while in conventional cooperative protocols a node becomes a relay only to assist other terminals, with our proposal a cooperator can also serve its own traffic. We evaluate Phoenix's performance by means of a theoretical model and extensive simulation campaigns. We show that Phoenix is especially beneficial in multihop settings and interesting gains over benchmark protocols can be achieved.

Geographic routing is a promising solution for data forwarding in power-constrained ad-hoc networks. Such protocols are especially attractive for wireless sensor networks as they can be operated without a central control and are scalable to an arbitrary number of nodes. In this work, we present a class of geographic routing algorithms that enhance energy-efficiency by means of a cross-layer design that incorporates PHY/MAC functions such as on-demand cooperative relaying and leapfrogging. The performance of these protocols is evaluated by means of OMNET++ simulations. Significant improvements are shown in terms of packet delivery ratio, latency and connectivity for different network topologies.

In this paper, we investigate how to apply MIMO_NC in order to increase the efficiency of cooperative communications. MIMO_NC is a recent strategy to combine, in an integrated system, MIMO detection techniques and network coding. MIMO_NC is robust to channel errors, as it can exploit the spatial diversity provided by multiple transmissions of the same information, and throughput effective as it is based on network coding. In this paper we design a cooperative MAC protocol based on MIMO_NC which can outperform classical cooperative schemes. We also prove its effectiveness by means of analytical modelling and simulations in different network configurations.

We propose the novel concept of cooperation for deafness prevention in directional antenna ad hoc networks, along with a low-complexity multiuser detector specialised for these systems. We call a generic MAC protocol that uses these techniques a cooperative-MAC (CMAC) and we define an upper and a lower bound on the performance of this class of protocols. Several simulations compare these bounds against the circular RTS/CTS protocol (CRCM), which is one of the finest deafness- suppression systems proposed so far, and show that our combined techniques achieve significant gains over CRCM in terms of throughput and energy consumption.