For randomly distributed nodes sending packets to a central gateway using slotted Aloha with a constrained number of retransmissions over a wireless fading channel, we take an iterative approach to compute the total traffic density of packet transmissions and collision-induced retransmissions as a function of the node-gateway distance. From this, we compute the outage probability, throughput, and energy consumption. This method can be used to analyze and dimension Low-Power Wide-Area Networks (LPWANs). Applying it in LoRa illustrates design tradeoffs concerning outage probability, spreading factors, energy consumption, and cell size. It notably shows that permitting more retransmissions helps the nodes near the gateway but hurts distant ones.

The concept of pulse-coupled oscillators for self-organized synchronization has been applied to wireless systems. Putting theory into practice, however, faces certain obstacles, particularly in radio technologies that cannot implement pulses but use common messages for interactions between nodes. This raises the question of how to deal with interference between messages. We show that interference can disturb the synchronization process and propose low-complex, randomization-based techniques to address this issue. First, we demonstrate that randomly switching between two transmit power levels (without increasing the average power) can expedite synchronization. The high-power transmissions temporarily boost network connectivity with negligible impact on the average interference. Second, we reduce interference by blindly distributing the messages over the entire oscillator cycle. Instead of using a fixed oscillator phase at which the pulses are sent, each node chooses its own, randomly selected phase to send a synchronization message. This node-specific “fire phase” is contained in the message to permit others to compute the timing. Third, we suggest that such interference management can also be beneficial for other synchronization techniques and validate this claim using Glossy as an example. Our insights may contribute to feasible solutions for self-organized wireless synchronization. Further work is needed to gain a comprehensive understanding of the effects of randomization and to develop algorithms for the adaptability of local parameters.

HiPR+ is an approach for centimeter-accurate indoor localization. It combines distance estimation between ultra-wideband (UWB) transceivers and location estimation using an extended Kalman filter (EKF). The performance is tested with experiments on hardware platforms from Decawave. The distance estimation of HiPR+ achieves an order of magnitude better precision and a multiple improvement in accuracy compared to the company's native solution while it only takes only a fraction the time needed for range computation. We evaluate the 3D localization capabilities with two least-squares approaches and an EKF. A median accuracy below one centimeter can be attained using the proposed ranging error compensations in combination with the EKF-based~positioning.

Teleoperation of an unmanned aerial vehicle (UAV) is a challenging mobile application with real-time control from a first-person view. It poses stringent latency requirements for both video and control traffic. This paper studies the video quality and latencies for UAV teleoperation over LTE using ns3 simulations. A key ingredient is the latency budget model. We observe that the latency of the video is higher and more sensitive to mobility than that of the control traffic. The latency is influenced by the traffic variation caused by the variable bit rate of the streaming application. High mobility tends to increase latency and lead to more outliers, being problematic in real-time control.

We derive the probability distribution of the link outage duration at a typical receiver in a wireless network with Poisson distributed interferers sending messages with slotted random access over a Rayleigh fading channel. This result is used to analyze the performance of random linear network coding, showing that there is an optimum code rate and that interference correlation affects the decoding probability and throughput.

This article takes an analytical approach to investigate the temporal dynamics of interference in wireless networks. We propose a framework to calculate the autocorrelation of interference in Poisson networks and derive closed-form expressions for the case of Nakagami fading. The framework takes three correlation sources into account: the location of interferers, the wireless channel, and the data traffic. We introduce the interference coherence time-in analogy to the well-established channel coherence time-and show how its basic qualitative behavior depends on the source of correlation. The insights gained can be useful in the design of medium access control and retransmission protocols.

A thorough understanding of the temporal dynamics of interference in wireless networks is crucial for the design of communication protocols, scheduling, and interference management. This article applies stochastic geometry to investigate the interference dynamics in a network of nodes that use carrier sense multiple access (CSMA). This type of network is approximated by a Matérn hard-core point process of type II with Nakagami fading. We derive and analyze expressions for the variance, covariance, and correlation of the interference power at an arbitrary location. Results show that even though the commonly used Poisson approximation to CSMA may have the same average interference as the Matérn model, the interference dynamics behaves significantly different. In this way, this study reveals a pitfall in the modeling of wireless systems and contributes to the theory of interference calculus.

We propose a communication scheme with relays to improve the reliability of a Long Range (LoRa) sensor network with duty-cycle limitations. The relays overhear the sensors' transmissions and forward them to a gateway. Simulations show that relaying is very beneficial, even though the nodes are not coordinated and duty cycling limits the number of sensor measurements that can be forwarded. In our setup, a single relay can halve the measurement loss rate and eight relays provide a gain of up to two orders of magnitude. Further improvements are achieved by including a few past measurements in each frame.

We present a distance estimation technique based on ultra-wideband time-of-arrival measurements and assess it with IEEE 802.15.4-2011 devices by Decawave. Experiments show that our technique is about 30 times faster than Decawave's out-of-the-box solution, which can be exploited to improve the precision by one order of magnitude.

We analyze a boarding solution for a transport system in which the number of passengers allowed to enter a transport cabin is automatically controlled. Expressions characterizing the stochastic properties of the passenger queue length, waiting time, and cabin capacity are derived using queuing theory for a transport line with deterministic arrivals of cabins and Poisson arrivals of passengers. The expected cabin capacity and stability threshold for each station are derived for a general passenger arrival distribution. The results show that a significant reduction of the waiting time at a given station is only possible at the cost of making the stability of one of the preceding stations worse than that of the given station. Studies with real passenger arrivals are necessary to draw firm conclusions.

In this paper, an interference-aware path planning scheme for a network of cellular-connected unmanned aerial vehicles (UAVs) is proposed. In particular, each UAV aims at achieving a tradeoff between maximizing energy efficiency and minimizing both wireless latency and the interference caused on the ground network along its path. The problem is cast as a dynamic game among UAVs. To solve this game, a deep reinforcement learning algorithm, based on echo state network (ESN) cells, is proposed. The introduced deep ESN architecture is trained to allow each UAV to map each observation of the network state to an action, with the goal of minimizing a sequence of time-dependent utility functions. Each UAV uses the ESN to learn its optimal path, transmission power, and cell association vector at different locations along its path. The proposed algorithm is shown to reach a subgame perfect Nash equilibrium upon convergence. Moreover, an upper bound and a lower bound for the altitude of the UAVs are derived thus reducing the computational complexity of the proposed algorithm. The simulation results show that the proposed scheme achieves better wireless latency per UAV and rate per ground user (UE) while requiring a number of steps that are comparable to a heuristic baseline that considers moving via the shortest distance toward the corresponding destinations. The results also show that the optimal altitude of the UAVs varies based on the ground network density and the UE data rate requirements and plays a vital role in minimizing the interference level on the ground UEs as well as the wireless transmission delay of the UAV.

In this paper, an interference-aware path planning scheme for a network of cellular-connected unmanned aerial vehicles (UAVs) is proposed. In particular, each UAV acts as a cellular user equipment (UE) and aims at achieving a tradeoff between maximizing energy efficiency and minimizing both wireless latency and the interference caused on the ground network along its path. The problem is cast as a dynamic game among UAVs. To solve this game, a deep reinforcement learning algorithm, based on echo state network (ESN) cells, is proposed. The introduced deep ESN architecture is trained to allow each UAV to map each observation of the network state to an action, with the goal of minimizing a sequence of time-dependent utility functions. Each UAV uses ESN to learn its optimal path, transmission power, and cell association vector at different locations along its path. The proposed algorithm is shown to reach a subgame perfect Nash equilibrium upon convergence. Simulation results show that the proposed scheme achieves better wireless latency per UAV and rate per ground UE while requiring a number of steps that is comparable to a heuristic baseline that considers moving via the shortest distance towards the corresponding destinations.

We propose a multi-objective optimization algorithm to allocate tasks and plan paths for a team of UAVs. The UAVs must find a target in a bounded area and then continuously communicate the target information to the ground personnel. Our genetic algorithm approach aims to minimize the mission completion time, which includes the time to find the target (area coverage) and the time to setup a communication path (network connectivity). We evaluate strategies using a data mule, a relay chain, and a novel hybrid approach to communicate with the ground personnel. The algorithm can be tuned to prioritize coverage or connectivity, depending on the mission demands. Simulation results show reduced overall mission completion times (up to 65%), with more improvement as the UAV density increases.

We compare five policies for teams of mobile robots to share a limited number of charging points while exploring a structured, unknown environment. Since it is infeasible to precompute an optimized schedule due to a limited time horizon, an energy-aware planner is used for adaptively deciding when and where to recharge. The coordination between robots is based on market economy giving them the flexibility to incorporate multiple objectives into a single cost function. The presented policies are evaluated through simulations with different robot team sizes on different maps. We measure the exploration gain in explored area and the exploration cost in traveled distance over time. We compare the market-based approach to a simple first-come, first-served approach. Results demonstrate the applicability for multi-robot exploration and show the strengths and weaknesses of each policy.

Our research investigates the concept of interference prediction as an unprecedented approach for interference management and medium access in wireless networks. This paper is a first step in this direction: it proposes and evaluates a simple interference prediction technique that is based on low-complexity learning. Nodes predict the interference situation they expect to experience in the near future and select the most favorable time slot to start the transmission of a multislot message. The performance gain is evaluated in a small-scale fading environment in terms of link outage and delay against random slot selection. Simulation results show that interference prediction is a promising building block for wireless systems. Additional studies are needed to explore advanced techniques and assess their feasibility.

There is a strong demand in the aviation industry to replace cables in airplanes by wireless connectivity to gain flexibility and reduce weight. Such in-plane wireless communications must be reliable and robust against interference. As part of our activities in this domain, we present a proof-of-concept for an ultra-wideband (UWB) sensor network deployed in a mockup of a small passenger cabin of a commercial aircraft with a few passengers and report experimental results on the packet loss rate with off-the-shelf IEEE~802.15.4-2011 compliant UWB transceivers. It is shown that a combination of spatial and temporal diversity can significantly lower the packet loss rate of different link types without degrading throughput.

This article compares measures for quantifying the level of inhomogeneity of a given spatial point pattern. Comparisons are based on two main metrics: first, we evaluate the performance of the measures on both certain stochastic point processes and on very specific point patterns designed to expose potential weaknesses of the inhomogeneity measures. Second, we evaluate the computational complexity of the measures. Results show that choosing a measure is a tradeoff between accurate assessment of inhomogeneity and computational complexity. The only exception is the proposed extended wrap-around measure , which is performing well in terms of both metrics.

A time synchronization technique for networked devices with low-precision oscillators and low computational power is proposed and evaluated. We apply a dynamic stochastic model inserted into a Kalman filter formulation to track the clock evolution of oscillators and achieve synchrony to a central time reference. Indoor and outdoor experiments performed with commercially available wireless sensor platforms over several days serve as a proof of concept and show the synchronization accuracy under stable and varying temperature conditions.

Multicast video streaming over IEEE 802.11 is unreliable due to the lack of feedback from receivers. High data rates and variable link conditions require feedback from the receivers for link estimation to improve reliability and rate adaptation accordingly. In this paper, we validate on a test platform an application-layer rate-adaptive video multicast streaming framework using an 802.11 ad-hoc network applicable for mobile senders and receivers. Experimental results serve as a proof of concept and show the performance in terms of goodput, delay, packet loss, and received video quality.

This work explores the benefits in terms of energy efficiency that can be provided by device-to- device (D2D) communications in cellular systems. Analyzing a large cellular network using stochastic geometry, considering Nakagami fading and realistic system parameters, we explore the reduction that can be achieved in network power consumption, and the impact this reduction has on the performance of cellular users. When the network is not fully loaded, switching some cellular users into D2D mode results in a significant reduction of the network power consumption while the overall network throughput is maintained. Furthermore, it is observed that the impact of the reduction in the inter-cell interference arising from switching cellular users to D2D mode surpasses that from the new non- orthogonal transmissions. This translates into a slight improvement in the users' rates. Both analytical and simulation results are provided.

The convergence and precision of synchronization algorithms based on the theory of pulse-coupled oscillators is evaluated on programmable radios. Measurements in different wireless topologies show that such algorithms reach precisions in the low microsecond range. Based on the observation that phase rate deviation among radios is a limiting factor for the achievable precision, we propose a distributed algorithm for automatic phase rate equalization and show by experiments that an improved precision below one microsecond is possible in the given setups. It is also experimentally demonstrated that the stochastic nature of coupling is a key ingredient for convergence to synchrony. The proposed scheme can be applied in wireless systems for distributed synchronization of transmission slots, or sleep cycles.

We propose and prove a theorem that allows the calculation of a class of functionals on Poisson point processes that have the form of expected values of sum-products of functions. In proving the theorem, we present a variant of the Campbell-Mecke theorem from stochastic geometry. We proceed to apply our result in the calculation of expected values involving interference in wireless Poisson networks. Based on this, we derive outage probabilities for transmissions in a Poisson network with Nakagami fading. Our results extend the stochastic geometry toolbox used for the mathematical analysis of interference-limited wireless networks.

The commercial availability of small unmanned aerial vehicles (UAVs) opens new horizons for applications in disaster response, search and rescue, event monitoring, and delivery of goods. An important building block is the wireless communication between UAVs and to base stations. Design of such a wireless network may vary vastly from existing networks due to aerial network characteristics such as high mobility of UAVs in 3D space. This paper presents experimental performance results with commercially available UAVs. First, we show throughput results for IEEE 802.11ac in a UAV setting. Second, we demonstrate that IEEE 802.11n can have much higher throughput over longer ranges than reported in [1] and [2]. Third, we analyze the fairness in a multi-sender aerial network. Fourth, we test a real-world coverage scenario with two mobile UAVs sending to a single receiver. Performance analysis considers the rate adaptation mechanism in both indoor and outdoor line-of-sight scenarios.

Device-to-device (D2D) communications is a promising candidate for increasing the throughput of cellular systems towards 5G. Its current consideration for inclusion in LTE-A is attracting a lot of research interest, including work on mode selection, bandwidth allocation, and power control. Some consider the uplink for D2D operation while others focus on operation over the downlink. It is still unclear, however, which link is preferable for D2D operation. This paper addresses this issue focusing on the outage performance of D2D receivers. We use stochastic geometry tools for our analysis, considering realistic system parameters and Nakagami fading. We find that the interference from the cellular system on the downlink, which is correlated over consecutive time slots, favors underlay D2D operation, resulting in a lower outage probability for the D2D transmissions.

Through real-world measurements we evaluate the impact of multihop-aware cooperative relaying on end-to-end route performance in wireless multi-hop networks. In an experiment with 50 devices in an industrial environment cooperative relaying increases the end-to-end transmission reliability for multi-hop links to nearly 100% while reducing the average packet delay. We suggest how to include relay selection in the route discovery process of ad hoc routing protocols such as Ad hoc On-Demand Distance Vector (AODV) and Dynamic Source Routing (DSR) and perform two experiments. In the first experiment we discuss route discovery strategies focusing on small delay benefiting from reliable data link transmissions using cooperative relays. In the second experiment we compare reliability and delay for five different transmission powers with and without cooperative relaying.

This article evaluates convergence rates of binary majority consensus algorithms in networks with different types of disturbances and studies the potential capacity of randomization to foster convergence. Simulation results show that (a) additive noise, topology randomness, and stochastic message loss may improve the convergence rate; (b) presence of faulty nodes degrades the convergence rate; and (c) explicit randomization of consensus algorithms can be exploited to improve the convergence rate. Watts-Strogatz and Waxman graphs are used as underlying network topologies. A consensus algorithm is proposed that exchanges state information with dynamically randomly selected neighbors and, through this randomization, achieves almost sure convergence in some scenarios.

We investigate the statistics of the number of time slots T that it takes a packet to travel through a chain of wireless relays. Derivations are performed assuming an interference model for which interference possesses spatiotemporal dependency properties. When using this model, results are harder to arrive at analytically, but they are more realistic than the ones obtained in many related works that are based on independent interference models. First, we present a method for calculating the distribution of T. As the required computations are extensive, we also obtain simple expressions for the expected value E[T] and variance Var[T]. Finally, we calculate the asymptotic limit of the average speed of the packet. Our numerical results show that spatiotemporal dependence has a significant impact on the statistics of the travel time T. In particular, we show that, with respect to the independent interference case, E[T] and Var[T] increase, whereas the packet speed decreases.

Protocols for neighbor cardinality estimation can be used by a node in an ad hoc or sensor network to obtain a fast approximation of the number of nodes in its radio range. While the performance of such estimators was studied via simulations and mathematical analysis, we show here for the first time a proof-of-concept and performance test with an implementation on low-power wireless sensor devices. We illustrate the challenges of implementing the recently proposed Multi-feedback estimator (MFE) on Z1 devices. Experimental results show that - with certain computational improvements - MFE can perform faster than simple neighbor counting for scenarios with many nodes or relaxed accuracy requirements.

Small-scale multicopters operating as autonomous teams in the air are envisioned for aerial monitoring and transport of goods in a variety of applications, including disaster management and environmental monitoring. For such applications to become reality, a high-throughput wireless network is needed. This paper presents experimental performance results with commercially available quadrocopters communicating via IEEE 802.11a. In particular, we compare the infrastructure and mesh modes of 802.11 for one-hop and two-hop communications, thus analyzing network layer versus MAC layer relaying. Results illustrate that changes are required in the mesh mode to support applications demanding high throughput with low jitter.

Strict reliability and delay requirements of factory monitoring and control applications pose challenges for wireless communications in dynamic and cluttered industrial environments. To reduce outage in such fading-rich areas, cooperative relays can be used to overhear source-destination transmissions and forward data packets that a source fails to deliver. This paper presents the results of an experimental study of selective cooperative relaying protocols that are implemented in off-the-shelf IEEE 802.15.4-compatible devices and evaluated in an industrial production plant. Three practical relay update schemes, which define when a new relay selection is triggered, are investigated: 1) periodic; 2) adaptive; and 3) reactive relay selections. The results show that all relaying protocols outperform conventional time diversity retransmissions in delivery ratio and number of retransmissions for packet delivery. Reactive selection provides the best overall delivery ratio of nearly 99% over the tested network. There is a tradeoff, however, between achievable delivery ratio and required selection overhead. This tradeoff depends on protocol and network parameters, and is studied via protocol emulation using empirical channel values.

We specify and evaluate a protocol for cooperative relay communications in wireless networks targeted for low-budget and energy-constrained off-the-shelf hardware. The protocol located at the Medium Access Control (MAC) layer integrates radio resource reservation, relay selection, and packet flow. Performance is evaluated with different parameters, such as node density, channel coherence time, and data packet size. Higher network-wide reliability and throughput compared to noncooperative protocols can be achieved in dense networks and unreliable channels. At the same time, throughput does not degrade in sparse networks or good channel conditions.

Increasing availability of autonomous small-size aerial vehicles leads to a variety of applications for aerial exploration and surveillance, transport, and other domains. Many of these applications rely on networks between aerial nodes, that will have high mobility dynamics with vehicles moving in all directions in 3D space and positioning in different orientations, leading to restrictions on network connectivity. In this paper, we propose a simple antenna extension to 802.11 devices to be used on aerial nodes. Path loss and small-scale fading characteristics of air-to-ground links are analyzed using signal strength samples obtained via real-world measurements at 5 GHz. Finally, network performance in terms of throughput and number of retransmissions are presented. Results show that a throughput of 12Mbps can be achieved at distances in the order of 300m.

With the introduction of multi-robot systems for exploration the question then arises, whether coordination among robots in such systems is required. We propose a model based on Markov processes to evaluate the need for coordination in multi-robot systems during the exploration of unknown environments and determine possible gains achievable through coordination. The model is illustrated by exploration of an indoor office environment. We qualitatively identify characteristics of environments which make coordination necessary and allow to quantitatively include them in the model. The expected gain through coordination highly depends on the environment. We further investigate the impact of team sizes. In favorable environments explicit coordination is not needed at the cost of increased team sizes. This helps to raise understanding of factors having an impact on coordination functions and making it possible to approximate a possible gain through coordination.

We show by means of stochastic geometry that interference dynamics has a strong impact on the performance of cooperative relaying. For both conventional and multi-hop-aware cooperative relaying we show that the packet delivery probability significantly changes with the dependence of interference among the links. Depending on the scenario under consideration, this change could be either an increase or decrease of the packet delivery probability. Especially for multi-hop-aware cooperative relaying, the performance gain is heavily reduced when interference possesses high temporal and spatial dependence.

Several communication protocols and applications require a node to know how many neighboring nodes exhibiting a certain attribute it has. Conventionally, such neighbor information is obtained by explicit message exchange between nodes, which is reliable but inefficient in densely connected networks in terms of overhead and delay. An alternative approach is to perform an estimation of the neighbor cardinality using probabilistic methods. This paper pursues such an approach by proposing neighbor cardinality estimators that require no coordination among polled nodes but are based on a simple random access scheme with busy tones, where the number of empty slots is exploited to infer about the neighbor cardinality. We compare three estimators with different levels of adaptability and feedback from the query node and discuss their suitability for IEEE 802.11 and low power sensors. Performance is studied in terms of estimation accuracy and delay.

Cooperative relaying is a communication technique that has been shown to improve link reliability between communicating entities. Most results in this area are obtained either analytically or via simulations. Rather few real-world experiments are conducted to backup theoretical results. This paper intends to go a step in this direction of applied research. We study the performance of cooperative relaying for industrial applications based on real-world measurements. These link-level measurements are conducted employing low-cost, off-the-shelf IEEE 802.15.4 devices in a factory characterized by a harsh and cluttered environment. Using the measured data, we emulate a simple cooperative relaying protocol to investigate the performance in terms of outage and packet delivery ratio and study parameters suitable for relay selection.

Solutions for time synchronization based on coupled oscillators operate in a self-organizing and adaptive manner and can be applied to various types of dynamic networks. The basic idea was inspired by swarms of fireflies, whose flashing dynamics shows an emergent behavior. This article introduces such a synchronization technique whose main components are “inhibitory coupling” and “self-adjustment.” Based on this new technique, a number of contributions are made. First, we prove that inhibitory coupling can lead to perfect synchrony independent of initial conditions for delay-free environments and homogeneous oscillators. Second, relaxing the assumptions to systems with delays and different phase rates, we prove that such systems synchronize up to a certain precision bound. We derive this bound assuming inhomogeneous delays and show by simulations that it gives a good estimate in strongly-coupled systems. Third, we show that inhibitory coupling with self-adjustment quickly leads to synchrony with a precision comparable to that of excitatory coupling. Fourth, we analyze the robustness against faulty members performing incorrect coupling. While the specific precision-loss encountered by such disturbances depends on system parameters, the system always regains synchrony for the investigated scenarios.

The temporal correlation of interference is a key performance factor of several technologies and protocols for wireless communications. A comprehensive understanding of interference correlation is especially important in the design of diversity schemes, whose performance can severely degrade in case of highly correlated interference. Taking into account three sources of correlation—node locations, channel, and traffic—and using common modeling assumptions—random homogeneous node positions, Rayleigh block fading, and slotted ALOHA traffic—we derive closed-form expressions and calculation rules for the correlation coefficient of the overall interference power received at a certain point in space. Plots give an intuitive understanding as to how model parameters influence the interference correlation.

Cooperative diversity employs relays to assist source-destination transmissions and has shown to improve link outage probability in multipath fading environments. In this paper, we model relay selection as a semi-Markov process to analyze the impact of relay selection overhead on throughput, delay, and jitter in a simple scenario. Results show that the selection overhead can significantly reduce benefits of reactive relay selection if data frames are small or only few nodes overhear data. In such scenarios, relaying with a preassigned relay can be more beneficial.

We investigate the impact of time diversity and space-time diversity schemes on the traffic capacity of large-scale wireless networks with low-cost radios. Especially, we analyze the tradeoff between relaying gain and increased interference due to additional traffic. The results of a simulation-based study imply that cooperative relaying with selection combining shows benefits for low interference scenarios. For high traffic, however, higher-order modulation schemes outperform the investigated cooperative relaying scenario due to lower interference.

Incremental relaying is a communication technique enabling cooperative diversity in wireless networks. The relay forwards a correctly decoded packet only after getting the feedback that the destination failed to receive the data directly from the source. We model an incremental relaying protocol as a time-discrete finite-state Markov process and analyze its throughput performance in time-correlated radio channels with Rayleigh fading. We also determine two boundary cases: fully correlated and fully uncorrelated fading channel. The analysis shows that the throughput gains of incremental relaying to conventional Automatic Repeat-reQuest retransmission strongly depend on the channel correlation, relay position, and source-to-destination fading margin.

In performance evaluations of communication and computer networks the underlying topology is sometimes modeled as a random graph. To avoid unwanted side effects, some researchers force the simulated topologies to be connected. Consequently, the resulting distribution of the node degrees does then no longer correspond to that of the underlying random graph model. Being not aware of this change in the degree distribution might result in a simulation pitfall. This paper addresses the question as to how serious this pitfall might be. We analyze the node degree distribution in connected random networks, deriving an approximation for large networks and an upper bound for networks of arbitrary order. The tightness of these expressions is evaluated by simulation. The analysis of the distribution for large networks is extended to k-connected graphs. Results show that specific restricted binomial distributions match the actual degree distribution better than the random graph degree distribution does. Nevertheless, the pitfall of not being aware of the change in the distribution seems not to be a serious mistake in typical setups with large networks.

Decentralized synchronization requires cooperation among network participants so that all nodes agree on a common reference timing. What happens if one node does not follow local synchronization rules and randomly transmits? This paper studies the resilience of two classes of decentralized slot synchronization against random disturbances, and quantifies the impact of the random behavior. It is shown that the coupling strength is a key factor for resilience, and that the synchronization approach based on the theory of coupled oscillators generally behaves better and is more robust than the approach that updates clocks based on the average neighboring timings.

This paper proposes a probabilistic technique that enables a node to estimate the number of its neighbors that fulfill certain criteria. The technique does not require any a priori information about the network topology. Based on a query from the estimating node, the neighbors send busy tones in a sequence of time slots. Evaluating the fraction of empty slots, the querying node can infer about its neighborhood. Mathematical analysis and numerical simulations show how the estimation success and accuracy depend on the available time period. Applications of the method can be found, for example, in RFID systems and medium access protocols.

A simple cooperative diversity technique is applied to point-to-multipoint communication in wireless medium suffering from Rayleigh block fading. Such a concept is especially interesting if low-cost radios, which have no advanced capabilities for fading mitigation, are used. This paper analyzes the communication reliability in terms of outage and delivery ratio, and compares cooperative and non-cooperative schemes. Results from a simple setup show that already few preselected relays can lead to performance gains. A potential application field is link-layer broadcast in a network of energy-constrained embedded devices.

In this paper, we propose a belief-based movement approach for a network of unmanned vehicles, which is deployed to cover a given area. The spatial and temporal coverage performance of the belief-based approach is compared with legacy movement models such as random walk, random direction as well as a random sweeping model for several scenarios. Our results highlight the trade-off between how fast and how well an area can be covered and show that the proposed approach can outperform the other methods that are tested.

This paper presents a biologically inspired approach for distributed slot synchronization in wireless networks. This is facilitated by modifying and extending a synchronization model based on the theory of pulse-coupled oscillators. The proposed Meshed Emergent Firefly Synchronization (MEMFIS) multiplexes synchronization words with data packets and adapts local clocks upon the reception of synchronization words from neighboring nodes. In this way, a dedicated synchronization phase is mitigated, as a network-wide slot structure emerges seamlessly over time as nodes exchange data packets. Simulation results demonstrate that synchronization is accomplished regardless of the arbitrary initial situation. There is no need for the selection of master nodes, as all nodes cooperate in a completely self-organized manner to achieve slot synchrony. Moreover, the algorithm is shown to scale with the number of nodes, works in meshed networks, and is robust against interference and collisions in dense networks.

Cooperative relaying methods can improve wireless links, but introduce overhead due to relay selection and resource reservation compared to non-cooperative transmission. In order to be competitive, a cooperative relaying protocol must avoid or compensate for this overhead. In this paper, we present a MAC protocol for relay selection and cooperative communication as an extension to CSMA/CA which addresses resource reservation, relay selection, and cooperative transmission while keeping the overhead in terms of time and energy low. We discuss the efficiency of this protocol for packet error rate, throughput, and message delay in a multi-hop network. Simulation results show that the protocol performs similar and without noticeable overhead compared to standard CSMA/CA for good SNR while it is able to significantly improve throughput and reliability at larger distances.

Cooperative relaying is a communication technique in wireless networks where neighboring nodes assist communication pairs to mitigate the negative effects of multi-path fading. The resulting performance strongly depends on the selected relays. Although a cooperative relay provides benefits to a given source-destination pair, overall network performance might be degraded due to the increased level of interference. So far almost all relay selection mechanisms consider mainly channel conditions to the potential relays. In this paper we propose a contention-based relay selection mechanism that can take into account also spatial efficiency of potential relays. For that the degree as well as relative position of the nodes are used for selection. With the proposed method a high successful relay selection probability can be achieved, while significantly reducing the amount of additional spatial resources blocked by the cooperative relay.

This paper studies probabilistic information dissemination in random networks. Consider the following scenario: A node intends to deliver a message to all other nodes in the network ("flooding"). It first transmits the message to all its neighboring nodes. Each node forwards a received message with some network-wide probability pf. A natural question arises: which forwarding probability pfshould each node use such that a flooded message is obtained by all nodes with high probability? In other words, what is the minimum pfto achieve a high global outreach probability? We first present a generic approach to estimate the probability for achieving global outreach. This approach is then employed in Erdos Renyi random graphs, where we derive an upper and a lower bound for the global outreach probability for given random network and flooding parameters. The analysis is complemented with simulation results showing the tightness of both bounds. As a final result, we take a system design perspective to show a number of parameter vectors leading to global outreach.

We address the drawbacks of cooperative relaying regarding its spectral inefficiency and its channel over reservation compared to direct transmissions. We propose to exploit routing information in cooperative relaying to reduce these disadvantages. In this paper we present a complete system design of multi-hop-aware cooperative relaying and investigate different relay selection policies for it. Performance tests indicate that it significantly outperforms hop-by-hop cooperative relaying in terms of throughput.

Consider n nodes competing for access on a channel using slotted ALOHA. Our aim is to maximize the probability Phi that the first message within s slots does not collide. We derive an expression for the transmit probabilities in each slot, maximizing Phi. As opposed to previous work, the expression is non-recursive, thus easier to calculate and more convenient for practical implementations. Furthermore, we address the problem that, in practical applications, the number of competing nodes n is likely to be unknown and has to be estimated by each node. We study the sensitivity of channel access scheme with respect to deviations from the actual n via simulations. It is shown that overestimation of n is a better strategy than underestimation.

Simulation results of wireless networks heavily depend on the spatial distribution of its nodes. Even though the initial distribution may match the expectations of the researcher, its properties may get lost due to the applied mobility model after a few seconds. This paper analyzes the effects of three well-known mobility models on the inhomogeneity of the spatial distribution. Furthermore, the effects of penetrable borders of the simulation area on the node distribution are analyzed. Due to the encountered deviations, we propose and analyze the inhomogeneous random waypoint (IRWP) model. It maintains a desired inhomogeneity level in the long run and generates random clusters with respect to shape, size, position, and member nodes.

The concept of cooperative relaying promises gains in robustness and energy-efficiency in wireless networks. Although protocols for cooperative relay selection were proposed recently, their analysis was made without consideration of the energy required for receiving. Such an analysis is unfair, as relaying requires more receptions than direct source-destination transmission. We consider this lack of analysis and propose two refinements of cooperative relaying. Using ldquorelay selection on demand,rdquo relays are only selected if required by the destination. Using ldquoearly retreat,rdquo each potential relay assesses the channel state and decides whether to participate in the relay selection process or not. Simulation results show that these enhancements reduce the overall energy consumption significantly.

Considering n nodes performing random access using ALOHA with s slots, we study the probability that there occurs a non-colliding message in the first non-empty slot. If each node transmits with probability p in each slot and the number of slots is sufficiently large, a non-colliding first message occurs with probability Phi = 1-np/2 for large n and small np. If the number of slots is limited, the probability Phi is lower but can be maximized choosing an optimal p. To maximize Phi further, nodes can apply a slot-dependent transmit probability pi with i = 1, ..., s. It is shown that a ldquoslow start strategy,rdquo in which piis low for low i and increases with increasing i, is beneficial. Our main contribution is an equation for the pivalues that maximize Phi. We analyze how a higher probability of a non-colliding first message comes at the price of an increased delay of such a message. Besides being of interest for the theory of random access, the results are practically applicable to node selection protocols, such as relay selection in cooperative wireless networks.

The spatial distribution of nodes in wireless networks has important impact on network performance properties, such as capacity and connectivity. Although random sample models based on a uniform distribution are widely used in the research community, they are inappropriate for scenarios with clustered, inhomogeneous node distribution. This paper proposes a well-defined measure for the level of inhomogeneity of a node distribution. It is based on the local deviation of the actual value of the density of nodes from its expected value. Desired properties of the measure are defined and mathematically proven to be fulfilled. The inhomogeneity measure is also compared to human perception of inhomogeneity gained via an online survey. The results reveal that the measure well fits human perception, although there are notable deviations if linear operations are applied.

Most analysis and simulation of wireless systems assumes that the nodes are randomly located, sampled from a uniform distribution. Although in many real-world scenarios the nodes are non-uniformly distributed, the research community lacks a common approach to generate such inhomogeneities. This paper intends to go a step in this direction. We present an algorithm to create a random inhomogeneous node distribution based on a simple neighborhood-dependent thinning of a homogeneous Poisson process. We derive some useful stochastic properties of the resulting distribution (in particular the probability density of the nearest neighbor distance) and offer a reference implementation. Our goal is to enable fellow researchers to easily use inhomogeneous distributions with well-defined stochastic properties.

This paper presents an end-to-end reservation protocol for quality-of-service (QoS) support in the medium access control layer of wireless multihop mesh networks. It reserves periodically repeating time slots for QoS-demanding applications, while retaining the distributed coordination function (DCF) for best effort applications. The key features of the new protocol, called "distributed end-to-end allocation of time slots for real-time traffic (DARE), are distributed setup, interference protection, and scheduling of real-time data packets, as well as the repair of broken reservations and the release of unused reservations. A simulation-based performance study compares the delay and throughput of DARE with those of DCF and the priority-based enhanced distributed channel access (EDCA) used in IEEE 802.11e. In contrast to DCF and EDCA, DARE has a low, nonvarying delay and a constant throughput for each reserved flow

This paper analyzes the impact of beamforming antennas on the topological connectivity of multihop wireless networks. As a metric for the connectivity of the network, we use the percentage P(path) of nodes that are connected via a multihop path. We show that simple randomized beamforming - i.e., each node adjusts its main beam into a randomly chosen direction for transmission and reception - significantly improves P(path) compared to networks with omnidirectional antennas employing the same power and sensitivity. The study is performed using accurate, analytical antenna models for uniform linear and circular antenna arrays. Already small arrays with four antenna elements give high gains of P(path). These gains are achieved although the nodes' average number of neighbors does not necessarily increase.

We show that randomized beamforming is a simple yet efficient communication strategy in wireless multihop networks if no neighbor location information is at hand. Already small antenna arrays reduce the hop distance between nodes and speed up the flooding of messages. This result is obtained in different scenarios, using accurate models for circular antenna arrays and a line-of-sight link model between randomly placed nodes.

Given is a wireless multihop network whose nodes are randomly distributed according to a homogeneous Poisson point process of density /spl rho/ (in nodes per unit area). The network employs Basagni's distributed mobility-adaptive clustering (DMAC) algorithm to achieve a self-organizing network structure. We show that the cluster density, i.e., the expected number of cluster- heads per unit area, is /spl rho//sub c/= /spl rho//spl divide/(1+/spl mu//spl divide/2), where /spl mu/ denotes the expected number of neighbors of a node. Consequently, a clusterhead is expected to incorporate half of its neighboring nodes into its cluster. This result also holds in a scenario with mobile nodes and serves as a bound for inhomogeneous spatial node distributions.

This paper presents a framework for the calculation of stochastic connectivity properties of wireless multihop networks. Assuming that n nodes, each node with transmission range r0, are distributed according to some spatial probability density function, we study the level of connectivity of the resulting network topology from three viewpoints. First, we analyze the number of neighbors of a given node. Second, we study the probability that there is a communication path between two given nodes. Third, we investigate the probability that the entire network is connected, i.e. each node can communicate with every other node via a multihop path. For the last-mentioned issue, we compute a tight approximation for the critical (r0,n) pairs that are required to keep the network connected with a probability close to one. In fact, the problem is solved for the general case of a k-connected network, accounting for the robustness against node failures. These issues are studied for uniformly distributed nodes (with and without ‘border effects’), Gaussian distributed nodes, and nodes that move according to the commonly used random waypoint mobility model. The results are of practical value for the design and simulation of wireless sensor and mobile ad hoc networks.

This paper investigates the connectivity of wireless multihop networks in a log--normal shadow fading environment. Assuming a spatial Poisson distribution of the network nodes, we derive (a) a closed--form expression for the probability that a node is isolated and (b) a tight bound for the minimum node density that is needed to obtain an almost surely connected subnetwork on a given area. Both results find application in the design and simulation of wireless sensor and ad hoc networks.

Abstract: The random waypoint model is a frequently used mobility model for simulation–based studies of wireless ad hoc networks. This paper inves-tigates the spatial node distribution that results from using this model. We show and interpret simulation results on a square and circular system area, derive an analytical expression of the expected node distribution in one di-mension, and give an approximation for the two–dimensional case. Finally, the concept of attraction areas and a modified random waypoint model, the random borderpoint model, is analyzed by simulation. 1

This paper investigates two fundamental characteristics of a wireless multi -hop network: its minimum node degree and its k--connectivity. Both topology attributes depend on the spatial distribution of the nodes and their transmission range. Using typical modeling assumptions :--- :a random uniform distribution of the nodes and a simple link model :--- :we derive an analytical expression that enables the determination of the required range r0 that creates, for a given node density ρ, an almost surely k--connected network. Equivalently, if the maximum r0 of the nodes is given, we can find out how many nodes are needed to cover a certain area with a k--connected network. We also investigate these questions by various simulations and thereby verify our analytical expressions. Finally, the impact of mobility is discussed.The results of this paper are of practical value for researchers in this area, e.g., if they set the parameters in a network--level simulation of a mobile ad hoc network or if they design a wireless sensor network.

The random waypoint model is a commonly used mobility model for simulations of wireless communication networks. In this paper, we present analytical derivations of some fundamental stochastic properties of this model with respect to: (a) the length and duration of a movement epoch, (b) the chosen direction angle at the beginning of a movement epoch, and (c) the cell change rate of the random waypoint mobility model when used within the context of cellular networks. Our results and methods can be used to compare the random waypoint model with other mobility models. The results on the movement epoch duration as well as on the cell change rate enable us to make a statement about the 'degree of mobility' of a certain simulation scenario. The direction distribution explains in an analytical manner the effect that nodes tend to move back to the middle of the system area.

Adaptive distributed clustering algorithms and respective protocols are used in wireless ad hoc networks to dynamically organize all nodes into groups and hierarchites. In this paper, we investigate the Distributed Mobility-Adaptive Clustering (DMAC) algorithm proposed in [6]. In particular, we evaluate how the cluster stability (i.e., the number of clusterhead elections, cluster changes per time step, and cluster lifetime) is influenced by the speed, the choice of the weight, and the failure rate of nodes. We performed simulations in a scenario with an enhanced random mobility model and in a realistic campus scenario that includes hot spots and streets

This paper presents an enhanced random mobility model for simulation-based studies of wireless networks. Our approach makes the movement trace of individual mobile stations more realistic than common approaches for random movement.After giving a survey of mobility models found in the literature, we give a detailed mathematical formulation of our model and outline its advantages. The movement concept is based on random processes for speed and direction control in which the new values are correlated to previous ones. Upon a speed change event, a new target speed is chosen, and an acceleration is set to achieve this target speed. The principles for a direction change are similar. Moreover, we propose two extensions for modeling typical movement patterns of vehicles. Finally, we consider strategies for the nodes' border behavior (i.e., what happens when nodes move out of the simulation area) and point out a pitfall that occurs when using a bounded simulation area.

Based on the two-dimensional (2-D) weight distribution of tail-biting codes we give guidelines on how to choose tail biting component codes that are especially suited for parallel concatenated coding schemes. Employing these guidelines, we tabulate tail-biting codes of different rate, length, and complexity. The performance of parallel concatenated block codes (PCBCs) using iterative (turbo) decoding is evaluated by simulation and bounds are calculated in order to study their asymptotic performance.