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Mobile Ad hoc Networks “MANETs”
The expansion of wireless networks introduces new needs and challenges for academicals and industrials. In the last decades wireless terminals proliferate putting wireless networks in a central place of our societies. The demand in applications is diversifying, to respond to these requirements researchers continuously innovate by providing new solutions to outperform the available technologies. Mobile Ad hoc Networks “MANETs” were developed to overcome the limits of the classical cellular networks requiring high infrastructure. In this section we review the different techniques developed or applied to MANETs. We first study the partitioning of the mobile nodes into subgroups referred as clusters. We then review the different routing schemes enabling to construct links between the cluster nodes. Finally we introduce the mobility model envisaged in this thesis.
d-hops Compound Metric Based Clustering “KCMBC”
As Max-Min algorithm described above, this algorithm generates clusters in which each node is situated at most at d-hops from the cluster head. For the cluster formation, KCMBC uses the same approach than the Max-Min algorithm which converges in 2d rounds of packet exchanges at each node. However, authors remark that the Max-Min strategy for the CHs election produces more clusters than needed and is not well adapted to dynamic environment. Moreover, the algorithm neglects the nodes connectivity criteria during the cluster head election. Thus, KCMBC proposes to take into account the mobility and the connectivity of nodes in its process.Indeed this algorithm introduces a mobility metric: the average link expiration. The nodes with highest average link expiration ensure a stability of the network topology and thus are more likely to be elected cluster heads. Periodical Hello packets containing the node position are broadcasted to the neighborhood with a time interval of S. Each node adjusts dynamically the time interval in order to not overhead the network. In a first stage, nodes with a mobility metric Ti above a certain threshold TALT are selected candidates to the cluster head election. Afterwards, the candidates set up their compound metric CPi = (Di; Ti; i), where Di is the number of 1-hop neighbors of node i, and other nodes set CP = (0; 0; 0). Then each node broadcasts their compound metric and selects the largest on received, this step is similar to Max-Min Floodmax. The rest of the process is the same than Max-Min with a WINNER value corresponding to the compound metric. Nodes position xi(t) at time t are considered and their respective velocity vector vi(t) calculated by their neighbors. It is assumed that the euclidean distance between a nodes pair i and j is less than a certain coverage radius. The algorithm employs a distance based converge-cast which consist in attaching the number of hops to the corresponding WINNER in the messages exchanged during the two flooding processes. Nodes stocks this number of hops and the SENDER node, afterwards nodes broadcast to its d-neighborhood the number of hops and its CH id. KCMBC was developed for dynamic environment applications a cluster maintenance process is provided.
Routing Protocols
Routing or path discovery protocols are essential to build communications among the network mobile nodes. These protocols aim to establish an efficient communication path between a pair of nodes without causing overhead and bandwidth wastage. Critical criteria are considered in the design of these schemes: the links have to be reliable and support the targeted QoS, routes discovered must be robust, optimal and loop free and the protocol must be simple and easily implementable. Added to the criteria enumerated above, routing protocols for MANETs should meet new challenges brought by their highly dynamic nature resulting in frequent and unpredictable topology changes. Thus, the design of routing protocols MANETs specific are widely considered in the literature. Three types of protocols can be highlighted, reactive, proactive and hybrid protocols. The first group discovers routes between a pair of nodes on demand from the sender node. In the second group, nodes maintain route tables to the other nodes of the network and the last one has some elements from both reactive and proactive protocols. In the following we describe three ad hoc routing protocols and compare their performances in a maritime environment.
Table of contents :
Acknowledgements
List of publications
Acronyms
List of figures
List of tables
French Detailed Summary
1 Introduction
1 Motivations
2 Contributions
3 Thesis outline
2 Technical and Mathematical Frameworks
1 Introduction
2 Mobile Ad hoc Networks “MANETs”
2.1 Traditional Clustering Algorithms
2.2 Routing Protocols
2.3 Mobility Models
3 Hybrid Satellite-MANET equipments
3.1 Long Term Evolution “LTE”
3.2 Satellite component
4 Maritime wireless channel and Cellular networks
4.1 Maritime Propagation: ITU-R recommendation path loss model
4.2 Random channel variation
5 Information Theory Principles
5.1 Single Input Single Output schemes
5.2 Multiple Input Multiple Output schemes
6 Poisson Point Processes “PPPs”
6.1 Stochastic geometry
6.2 Useful theorems
6.3 Marked Poisson Point Process
7 Basics from Graph Theory
7.1 Similarity graphs
7.2 Laplacian graph
7.3 Dijkstra’s algorithm
8 Conclusion
3 Topology Design of Hybrid Satellite – MANET
1 Introduction
2 Naval fleet Clustering
2.1 Hierarchical MANET Clustering “HMC”
2.2 Typical cluster average size estimation
2.3 Coverage radii in a centralized network
2.4 Coverage radii in a distributed network
2.5 Intra-cluster coverage radius
3 Multi-hop end-to-end communications
3.1 Typical distribution of hops through the nearest neighbors
3.2 Multi-hop routing protocols
3.3 Hybrid stations strategy
4 Numerical results
4.1 Simulation parameters
4.2 Coverage radii
4.3 Delays to shipmaster distribution
4.4 Multi-hop end-to-end communications ICDF
4.5 Probability distribution function of end-to-end delays
4.6 End-to-end delays with USATs probability density function
5 Conclusion
4 Centralized Network Resource Outage & Dimensioning
1 Introduction
2 Fundamental Assumptions
3 Analytical model definition
3.1 Radio resource outage probability
3.2 Outage probability upper-bound
3.3 Average spectral efficiency & Dimensioning
4 Resource Outage in different antenna configurations
4.1 SISO communication schemes
4.2 MIMO communications with diversity gain
4.3 MIMO communications with multiplexing gain
5 Impact of maritime propagation fluctuation on the dimensioning
5.1 Maritime propagation fluctuation
5.2 Variation of the required RBs number
5.3 Focus on the SISO configuration
6 Analytical model validation
6.1 System parameters
6.2 Single QoS users class target capacity
6.3 Multiple QoS users class target capacity
6.4 Numerical results for the impact of the maritime propagation on SISO scheme
7 Conclusion
Appendices
4.A Derivation of the area Aj expression with SISO scheme
4.B Derivation of the area Aj expression with diversity gain MIMO scheme
4.C Derivation of the area Aj expression with multiplexing gain MIMO scheme .
4.D Derivatives of the area Aj expression in a SISO scheme
5 Distributed Network Resource Outage in a MANET with Aloha MAC
1 Introduction
2 Background
2.1 Slotted Aloha MAC Protocols
3 Radio resource outage in the bipolar receiver model
3.1 Target rate and required number of RBs
3.2 Individual resource outage probability
3.3 Non-empty sub-medium resource outage probability
4 Coverage events
4.1 Typical individual coverage probability
4.2 Typical sub-medium coverage probability
4.3 Dimensioning in the bipolar receiver model
4.4 Parameters
4.5 Extension to the INR model
5 Typical coverage Probability for different transmission modes
5.1 SISO communications schemes
5.2 Single-layer MIMO communication with diversity gain
5.3 MIMO communication with full multiplexing gain
5.4 Optimal low SINR outage with full CSIT and MIMO MRC
6 Numerical results
6.1 Bipolar receiver model
6.2 INR receiver model
7 Conclusion
Appendices
5.A Proof of Lemma 5.1
5.B Proof of Lemma 5.2
6 Conclusion
1 Contributions
2 Perspectives
Bibliography
