Performance Analysis Of Multicast In Random Wireless Networks

With the development of wireless communication technology,multicast is becom-ing more predominant in many realistic communication situations.At the same time,the emergence of more complicated application devices and large diversity of service types impose a stringent demand on the quality of multicast transmission.Hence,this thesis investigates multicast performance in different scenarios of random wireless net-works,from both temporal and spatial perspectives.Specifically,this thesis focuses on the analysis of three fundamental metrics,i.e.,capacity,delay(in temporal aspect)and connectivity(in spatial aspect),and the design of corresponding routing scheduling schemes.The impact of critical network parameters on multicast performance is al-so discussed.The major contributions and novelty of this thesis are summarized as follows:First,we address the issue of multicast scaling in multi-channle multi-radio(M-CMR)networks,since MCMR can effectively avoid interference by letting users switch among channels during their transmission.Specifically,we conduct our research under the case where a total fixed bandwidth W is equally divided into multiple sub-channels.We solve the problem by firstly foeusing on static network as the startpoint and then turning to mobile scenario for further investigation.In a static network,we characterize how multicast capacity is affected by the number of destinations of each multicast ses-sion and the ratio of channels to interfaces.Then we consider a mobile MCMR network and derive the capacity upper bound as well as the corresponding delay.The capacity-achieving routing scheduling schemes are also proposed in both networks.Our results demonstrate that capacity loss exhibits in static MCMR networks.In contrast,mobility is manifested to improve multicast capacity in MCMR networks,where a major capac-ity bottleneck,i.e.,connectivity constraint in static networks can be effectively broken.Moreover,with the property of spectrum reuse in MCMR scenarios,multicast delay can be largely reduced in mobile networks without introducing redundancy.And the delay can be smaller than the one that is not achievable in traditional single channel networks even with a large number of redundancies.Second,we investigate throughput and delay of converge-cast,where each of the nodes in the network acts as a destination with multiple randomly chosen sources.Adopting Multi-Input-Multi-Output(MIMO)technology,we devise two different many-to-one cooperative schemes for convergecast in both static and mobile networks,re-spectively.In static networks,our scheme highly utilizes hierarchical cooperation MIMO transmission.With the originally interfering signals turned into interference-resistant ones,the scheme overcomes the bottleneck of converge-cast performance in traditional ad hoc network.It helps to achieve an near-optimal aggregate throughput in order sense.In the mobile ad hoc case,our scheme features joint transmission from multiple nodes to multiple receivers.Under optimal network division,the achievable per-node throughput can be nearly bounded by constant along with a largely reduced delay.The proposed schemes based on convergecast are also extendable to other types of traffic patterns such as unicast,multicast and broadcast,and can unify the corre-sponding results obtained.Third,we study the percolation degree of the secondary users to achieve k-percolation in large scale cognitive radio(CR)networks,where two overlapping structures,called primary and secondary networks coexist.The former one consists of primary nodes who are licensed spectrum users while the latter one comprises unauthorized users that have to use the licensed spectrum opportunistically.We put forward the conception of the percolation degree,which is defined as the number of nearest neighbors for each secondary user when there are at least k vertex-disjoint paths existing between any two secondary relays in the percolated cluster.To ensure k connectivity in the percolated cluster,each secondary user must be connected to more neighbors,and the percola-tion degree of the secondary network yields a function of the primary node density.We specify the relationship into three regimes regarding the topology variation of the cognitive network.A closed-form expression of the percolation degree under differ-ent primary node densities is presented.The expression characterizes the connectivity strength in the secondary percolated cluster.The result can also provide useful in-sights on connectivity behavior in wireless multicast networks when CR technology is adopted.Last,we consider the problem of optimally determining source-destination con-nectivity in random networks.We start our investigation in classical ER random graph,where an edge exists between two arbitrary nodes with equal probability p,indepen-dently of each other.The focus is to find out if a given pair of nodes,a source S and a destination D,in the graph are connected by a path.We propose an optimal algo-rithm that aims to minimize the total expected number of steps.The optimal algorithm follows several rules during edge checking.At each step it examines the condensation multigraph formed by contracting each known connected component to a super single node,and then checks an edge that is simultaneously on a shortest S-D path as well as in a minimum S-D cut.Among such edges,it chooses that which leads to the most opportunities for connection.Interestingly,for an ER graph with n nodes,the optimal strategy does not depend on p or n,even though the whole graph itself exhibits a sharp transition from disconnectivity to connectivity around the critical value of p=lnn/n.The proposed algorithm can also be extended to some graphs with slight more general structures.