<p>This paper deals with performance measurements in 802.11g Wireless Multi-Hop Net- </p><p>works at different locations. After an introduction to 802.11g Wireless LANs and </p><p>Wireless Multi-Hop Networks, the testing environment consisting of hardware, soft- </p><p>ware, configuration, and three different locations is described. Before test series for the </p><p>actual measurements are defined, carried out reference tests provide reference perfor- </p><p>mance data and prove that the used hardware is suitable for testing Wireless Multi-Hop </p><p>Networks. Then the results of the measurements are discussed which show the influ- </p><p>ence of multiple hops on throughput and latency for single and multi channel Multi-Hop </p><p>Networks in indoor, outdoor, and urban environment. Finally, an outlook to further </p><p>tests and improvements of Wireless Multi-Hop Networks is given.</p>

This paper deals with performance measurements in 802.11g Wireless Multi-Hop Net- works at different locations. After an introduction to 802.11g Wireless LANs and Wireless Multi-Hop Networks, the testing environment consisting of hardware, soft- ware, configuration, and three different locations is described. Before test series for the actual measurements are defined, carried out reference tests provide reference perfor- mance data and prove that the used hardware is suitable for testing Wireless Multi-Hop Networks. Then the results of the measurements are discussed which show the influ- ence of multiple hops on throughput and latency for single and multi channel Multi-Hop Networks in indoor, outdoor, and urban environment. Finally, an outlook to further tests and improvements of Wireless Multi-Hop Networks is given.

No description available.

With the growth of multimedia services, it is essential to find new transmission schemes to support higher data rates in wireless networks. In this thesis, we study networks in which the Channel State Information (CSI) is only available at the destination. We focus on the analysis of three different network setups. For each case, we propose a transmission scheme which maximizes the average performance of the network. The first scenario, which is studied in Chapter 2, is a multi-hop network in which the channel gain of each hop changes quasi-statically from one transmission block to the other. Our main motivation to study this network is the recent advances in deployment of relay nodes in wireless networks (e.g., LTE-A and IEEE 802.16j). In this setup, we assume that all nodes are equipped with a single antenna and the relay nodes are not capable of data buffering over multiple transmission blocks. The proposed transmission scheme is based on infinite-layer coding at all nodes (the source and all relays) in conjunction with the Decode-and-Forward DF relaying. The objective is to maximize the statistical average of the received rate per channel use at the destination. To find the optimal parameters of this code, we first formulate the problem for a two-hop scenario and describe the code design algorithm for this two-hop setting. The optimality of infinite-layer DF coding is also discussed for the case of two-hop networks. The result is then generalized to multi-hop scenarios. To show the superiority of the proposed scheme, we also evaluate the achievable average received rate of infinite-layer DF coding and compare it with the performance of previously known schemes. The second scenario, studied in Chapter 3, is a single-hop network in which both nodes are equipped with multiple antennas, while the channel gain changes quasi-statically and the CSI is not available at the source. The main reason for selecting this network setup is to study the transmission of video signals (compressed using a scalable video coding technique, e.g., SVC H.264/AVC) over a Multiple-Input Multiple-Output (MIMO) link. In this setup, although scalable video coding techniques compress the video signal into layers with different importance (for video reconstruction), the source cannot adapt the number of transmitted layers to the capacity of the channel (since it does not have the CSI in each time slot). An alternative approach is to always transmit all layers of the compressed video signal, but use unequal error protection for different layers. With this motivation, we focus on the design of multilayer codes for a MIMO link in which the destination is only able to perform successive decoding (not joint-decoding). In this chapter, we introduce a design rule for construction of multilayer codes for MIMO systems. We also propose a algorithm that uses this design rule to determine the parameters of the multilayer code. The performance analysis of the proposed scheme is also discussed in this chapter. In the two previous scenarios, the ambiguity of the source regarding the channel state comes from the fact that the channel gains randomly change in each transmission block and there is no feedback to notify the source about the current state of the channel. Apart from these, there are some scenarios in which the channel state is unknown at the source, even though the channel gain is fixed and the source knows its value. The third scenario of this thesis presents an example of such network setups. More precisely, in Chapter 4, we study a multiple access network with K users and one Access Point (AP), where all nodes are equipped with multiple antennas. To access the network, each user independently decides whether to transmit in a time slot or not (no coordination between users). Considering a two-user random access network, we first derive the optimal value of network average Degrees of Freedom (DoF) (introduced in Section 4.1). Generalizing the result to multiuser networks, we propose an upper-bound for the network average DoF of a K-user random access network. This upper-bound is then analyzed for different network configurations to identify the network classes in which the proposed upper-bound is tight. It is also shown that simple single-stream data transmission achieves the upper-bound in most network settings. However, for some network configurations, we need to apply multi-stream data transmission in conjunction with interference alignment to reach the upper-bound. Some illustrative examples are also presented in this chapter.

No description available.

With the growth of multimedia services, it is essential to find new transmission schemes to support higher data rates in wireless networks. In this thesis, we study networks in which the Channel State Information (CSI) is only available at the destination. We focus on the analysis of three different network setups. For each case, we propose a transmission scheme which maximizes the average performance of the network. The first scenario, which is studied in Chapter 2, is a multi-hop network in which the channel gain of each hop changes quasi-statically from one transmission block to the other. Our main motivation to study this network is the recent advances in deployment of relay nodes in wireless networks (e.g., LTE-A and IEEE 802.16j). In this setup, we assume that all nodes are equipped with a single antenna and the relay nodes are not capable of data buffering over multiple transmission blocks. The proposed transmission scheme is based on infinite-layer coding at all nodes (the source and all relays) in conjunction with the Decode-and-Forward DF relaying. The objective is to maximize the statistical average of the received rate per channel use at the destination. To find the optimal parameters of this code, we first formulate the problem for a two-hop scenario and describe the code design algorithm for this two-hop setting. The optimality of infinite-layer DF coding is also discussed for the case of two-hop networks. The result is then generalized to multi-hop scenarios. To show the superiority of the proposed scheme, we also evaluate the achievable average received rate of infinite-layer DF coding and compare it with the performance of previously known schemes. The second scenario, studied in Chapter 3, is a single-hop network in which both nodes are equipped with multiple antennas, while the channel gain changes quasi-statically and the CSI is not available at the source. The main reason for selecting this network setup is to study the transmission of video signals (compressed using a scalable video coding technique, e.g., SVC H.264/AVC) over a Multiple-Input Multiple-Output (MIMO) link. In this setup, although scalable video coding techniques compress the video signal into layers with different importance (for video reconstruction), the source cannot adapt the number of transmitted layers to the capacity of the channel (since it does not have the CSI in each time slot). An alternative approach is to always transmit all layers of the compressed video signal, but use unequal error protection for different layers. With this motivation, we focus on the design of multilayer codes for a MIMO link in which the destination is only able to perform successive decoding (not joint-decoding). In this chapter, we introduce a design rule for construction of multilayer codes for MIMO systems. We also propose a algorithm that uses this design rule to determine the parameters of the multilayer code. The performance analysis of the proposed scheme is also discussed in this chapter. In the two previous scenarios, the ambiguity of the source regarding the channel state comes from the fact that the channel gains randomly change in each transmission block and there is no feedback to notify the source about the current state of the channel. Apart from these, there are some scenarios in which the channel state is unknown at the source, even though the channel gain is fixed and the source knows its value. The third scenario of this thesis presents an example of such network setups. More precisely, in Chapter 4, we study a multiple access network with K users and one Access Point (AP), where all nodes are equipped with multiple antennas. To access the network, each user independently decides whether to transmit in a time slot or not (no coordination between users). Considering a two-user random access network, we first derive the optimal value of network average Degrees of Freedom (DoF) (introduced in Section 4.1). Generalizing the result to multiuser networks, we propose an upper-bound for the network average DoF of a K-user random access network. This upper-bound is then analyzed for different network configurations to identify the network classes in which the proposed upper-bound is tight. It is also shown that simple single-stream data transmission achieves the upper-bound in most network settings. However, for some network configurations, we need to apply multi-stream data transmission in conjunction with interference alignment to reach the upper-bound. Some illustrative examples are also presented in this chapter.

<p dir="ltr">The advancement of terrestrial networks has improved communication services for users in densely-populated areas, outpacing improvements in rural regions. The projected surge in connected devices in upcoming networks entails that the lack of rural and remote connectivity is limiting emerging applications like digital agriculture and intelligent transportation. Thus, expanding rural and remote wireless connectivity requires addressing the limitations of existing terrestrial infrastructure. In this work, we explore two emerging solutions aimed at enhancing wireless connectivity in rural and remote regions. The first approach considers non-terrestrial networks as an alternative to existing terrestrial technology. Specifically, a vertically-integrated, multi-layered architecture involving unmanned aerial vehicles, high-altitude platforms, and satellites serves as complementary elements, offering diverse pathloss, delay, data rates, and network backbone proximity. We address issues such as multi-hop performance degradation, node mobility, placement, and power distribution to optimize network design. The second approach focuses on wireless-powered communication networks, particularly backscatter communications, to overcome challenges associated with the timely data collection of emerging rural applications such as precision agriculture. We utilize ambient orthogonal frequency division multiplexing (OFDM) signals from cellular base stations to facilitate low-power, low-cost, and real-time data collection while eliminating the need for dedicated radio-frequency emitters. Non-coherent detection and modulation schemes are employed to obviate the necessity for accurate channel state information at the power-limited sensors and reader devices. Moreover, we introduce techniques for simultaneous sensor multiplexing by leveraging OFDM signal structure. Our approaches demonstrate substantial improvements in communication performance, offering versatile, scalable, and cost-effective solutions for rural and remote areas.</p>

Important sujet de recherche dans les télécommunications contemporaines, les réseaux de capteurs sont des réseaux sans fil constitués de plusieurs nœuds pouvant communiquer entre eux. Chaque capteur est autonome et possède une durée de vie limitée, liée à la taille de sa batterie. Dans ce contexte, l’énergie est une ressource critique qui peut être économisée en minimisant le nombre de paquets émis. De part la nature du médium radio, les données transmises subissent des pertes du canal. La fiabilisation de données dans ce contexte n’est pas simple et devient d’autant plus problématique lorsque la taille de réseau augmente. C’est dans ce contexte que s’inscrit cette thèse qui vise à fournir une technique de fiabilisation des transmissions dans un réseau de capteur. Pour cela, nous proposons de mettre en oeuvre un mécanisme de transmission qui exploite le code fontaine. Ce code est sans rendement et les symboles de redondance sont générés à la volée. Il permet de fiabiliser la transmission avec l’utilisation d’un canal de retour limité. Le code fontaine permet d’alléger le mécanisme de contrôle des transmissions tout en assurant un lien complètement fiable, ce qui permet de réduire la latence et la consommation énergétique d’une transmission. Afin d’optimiser la performance globale du réseau, nous étudions également dans cette thèse le cas où les nœuds sont autorisés à coopérer pour le relayage multi-sauts de paquets destinés à des nœuds distants. Nous montrons dans cette thèse que la technique de codage réseau permet d’introduire de la diversité d’information et ainsi d’améliorer la performance globale de transmissions multi-sauts mono-chemin. Ce résultat a été étendu à la transmission coopérative pour laquelle nous avons à la fois pu exploiter la diversité d’information et la diversité spatiale. / This thesis is dedicated to the deployment of fountain codes and network coding in a wireless sensor network (WSN). A WSN is composed of sensor nodes with restricted capacities : memory, energy and computational power. The nodes are usually randomly scattered across the monitored area and the environment may vary. In the presence of fading, outage and node failures, fountain codes are a promising solution to guaranty reliability and improve transmission robustness. The benefits of fountain codes are explored based on an event-driven WSNet simulator considering realistic implementation based on standard IEEE802.15.4. Fountain codes are rateless and capable of adapting their rate to the channel on the fly using a limited feedback channel. In this thesis, we highlight the benefits brought by fountain code in terms of energy consumption and transmission delay. In addition to the traditional transmission with fountain code, we propose in this thesis to study the network coding transmission scheme where nodes are allowed to process the information before forwarding it to their neighbors. By this means, we can say that packet diversity is exploited as each individual packet is unique and contains different representations of binary data. Redundancy is thus optimized since repetitions are avoided and replaced with diversified information. This can further lead to an overall improved performance in cooperative communication where nodes are allowed to assist in relaying packets from the source the destination. We highlight in this thesis the benefits of fountain code combined to network coding and show that it leads to a reduction in transmission delay and energy consumption. The latter is vital to the life duration of any wireless sensor network.

In this thesis we deal with the application of Network Coding to guarantee the Quality of Service (QoS) for wireless multi-hop networks. Since the medium is shared, wireless networks suffer from the negative interference impact on the bandwidth. It is thus interesting to propose a Network Coding based approach that takes into account this interference during the routing process. In this context, we first propose an algorithm minimizing the interference impact for unicast flows while respecting their required bandwidth. Then, we combine it with Network Coding to increase the number of admitted flows and with Topology Control to still improve the interference management. We show by simulation the benefit of combining the three fields: Network Coding, interference consideration and Topology Control. We also deal with delay management for multicast flows and use the Generation-Based Network Coding (GBNC) that combines the packets per blocks. Most of the works on GBNC consider a fixed generation size. Because of the network state variations, the delay of decoding and recovering a block of packets can vary accordingly degrading the QoS. To solve this problem, we propose a network-and content-aware method that adjusts the generation size dynamically to respect a certain decoding delay. We also enhance it to overcome the issue of acknowledgement loss. We then propose to apply our approach in a Home Area Network for Live TV and video streaming. Our solution provides QoS and Quality of Experience for the end user with no additional equipment. Finally, we focus on a more theoretical work in which we present a new Butterfly-based network for multi-source multi-destination flows. We characterize the source node buffer size using the queuing theory and show that it matches the simulation results.

Delay is known to be a critical performance metric for various real-world routing applications including multimedia communication and freight delivery. Provisioning delay-minimal (or at least delay-bounded) routing services for all traffic of an application is highly important. As a basic paradigm of networking, multi-path routing has been proven to be able to obtain lower delay performance than the single-path routing, since traffic congestions can be avoided. However, to our best knowledge, (i) many of existing delay-aware multi-path routing studies only consider the aggregate traffic delay. Considering that even the solution achieving the optimal aggregate traffic delay has a possibly unbounded delay performance for certain individual traffic unit, those studies may be insufficient in practice; besides, (ii) most existing studies which optimize or bound delays of all traffic are best-effort, where the achieved solutions have no theoretical performance guarantee. In this dissertation, we study four delay-aware multi-path routing problems, with the delay performances of all traffic taken into account. Three of them are in communication and one of them is in transportation. Note that our study differ from all related ones as we are the first to study the four fundamental problems to our best knowledge. Although we prove that our studied problems are all NP-hard, we design approximation algorithms with theoretical performance guarantee for solving each of them. To be specific, we claim the following contributions. Minimize maximum delay and average delay. First, we consider a single-unicast setting where in a multi-hop network a sender requires to use multiple paths to stream a flow at a fixed rate to a receiver. Two important delay metrics are the average sender-to-receiver delay and the maximum sender-to-receiver delay. Existing results say that the two delay metrics of a flow cannot be both within bounded-ratio gaps to the optimal. In comparison, we design three different flow solutions, each of which can minimize the two delay metrics simultaneously within a $(1/epsilon)$-ratio gap to the optimal, at a cost of only delivering $(1-epsilon)$-fraction of the flow, for any user-defined $epsilonin(0,1)$. The gap $(1/epsilon)$ is proven to be at least near-tight, and we further show that our solutions can be extended to the multiple-unicast setting. Minimize Age-of-Information (AoI). Second, we consider a single-unicast setting where in a multi-hop network a sender requires to use multiple paths to periodically send a batch of data to a receiver. We study a newly proposed delay-sensitive networking performance metric, AoI, defined as the elapsed time since the generation of the last received data. We consider the problem of minimizing AoI subject to throughput requirements, which we prove is NP-hard. We note that our AoI problem differs from existing ones in that we are the first to consider the batch generation of data and multi-path communication. We develop both an optimal algorithm with a pseudo-polynomial time complexity and an approximation framework with a polynomial time complexity. Our framework can build upon any polynomial-time $alpha$-approximation algorithm of the maximum delay minimization problem, to construct an $(alpha+c)$-approximate solution for minimizing AoI. Here $c$ is a constant dependent on throughput requirements. Maximize network utility. Third, we consider a multiple-unicast setting where in a multi-hop network there exist many network users. Each user requires a sender to use multiple paths to stream a flow to a receiver, incurring an utility that is a function of the experienced maximum delay or the achieved throughput. Our objective is to maximize the aggregate utility of all users under throughput requirements and maximum delay constraints. We observe that it is NP-complete either to construct an optimal solution under relaxed maximum delay constraints or relaxed throughput requirements, or to figure out a feasible solution with all constraints satisfied. Hence it is non-trivial even to obtain approximate solutions satisfying relaxed constraints in a polynomial time. We develop a polynomial-time approximation algorithm. Our algorithm obtains solutions with constant approximation ratios under realistic conditions, at the cost of violating constraints by up to constant-ratios. Minimize fuel consumption for a heavy truck to timely fulfill multiple transportation tasks. Finally, we consider a common truck operation scenario where a truck is driving in a national highway network to fulfill multiple transportation tasks in order. We study an NP-hard timely eco-routing problem of minimizing total fuel consumption under task pickup and delivery time window constraints. We note that optimizing task execution times is a new challenging design space for saving fuel in our multi-task setting, and it differentiates our study from existing ones under the single-task setting. We design a fast and efficient heuristic. We characterize conditions under which the solution of our heuristic must be optimal, and further prove its optimality gap in case the conditions are not met. We simulate a heavy-duty truck driving across the US national highway system, and empirically observe that the fuel consumption achieved by our heuristic can be $22%$ less than that achieved by the fastest-/shortest- path baselines. Furthermore, the fuel saving of our heuristic as compared to the baselines is robust to the number of tasks. / Doctor of Philosophy / We consider a network modeled as a directed graph, where it takes time for data to traverse each link in the network. It models many critical applications both in the communication area and in the transportation field. For example, both the European education network and the US national highway network can be modeled as directed graphs. We consider a scenario where a source node is required to send multiple (a set of) data packets to a destination node through the network as fast as possible, possibly using multiple source-to-destination paths. In this dissertation we study four problems all of which try to figure out routing solutions to send the set of data packets, with an objective of minimizing experienced travel time or subject to travel time constraints. Although all of our four problems are NP-hard, we design approximation algorithms to solve them and obtain solutions with theoretically bounded gaps as compared to the optimal. The first three problems are in the communication area, and the last problem is in the transportation field. We claim the following specific contributions. Minimize maximum delay and average delay. First, we consider the setting of simultaneously minimizing the average travel time and the worst (largest) travel time of sending the set of data packets from source to destination. Existing results say that the two metrics of travel time cannot be minimized to be both within bounded-ratio gaps to the optimal. As a comparison, we design three different routing solutions, each of which can minimize the two metrics of travel time simultaneously within a constant bounded ratio-gap to the optimal, but at a cost of only delivering a portion of the data. Minimize Age-of-Information (AoI). Second, we consider the problem of minimizing a newly proposed travel-time-sensitive performance metric, i.e., AoI, which is the elapsed time since the generation of the last received data. Our AoI study differs from existing ones in that we are the first to consider a set of data and multi-path routing. We develop both an optimal algorithm with a pseudo-polynomial time complexity and an approximation framework with a polynomial time complexity. Maximize network utility. Third, we consider a more general setting with multiple source destination pairs. Each source incurs a utility that is a function of the experienced travel time or the achieved throughput to send data to its destination. Our objective is to maximize the aggregate utility under throughput requirements and travel time constraints. We develop a polynomial-time approximation algorithm, at the cost of violating constraints by up to constant-ratios. It is non-trivial to design such algorithms, as we prove that it is NPcomplete either to construct an optimal solution under relaxed delay constraints or relaxed throughput requirements, or to figure out a feasible solution with all constraints satisfied. Minimize fuel consumption for a heavy truck to timely fulfill multiple transportation tasks. Finally, we consider a truck and multiple transportation tasks in order, where each task requires the truck to pick up cargoes at a source timely, and deliver them to a destination timely. The need of coordinating task execution times is a new challenging design space for saving fuel in our multi-task setting, and it differentiates our study from existing ones under the single-task setting. We design an efficient heuristic. We characterize conditions under which the solution of our heuristic must be optimal, and further prove its performance gap as compared to the optimal in case the conditions are not met.