Multicast outing protocols and architectures in mobile ad-hoc wireless networks

The basic philosophy of personal communication services is to provide user-to-user, location independent communication services. The emerging group communication wireless applications, such as multipoint data dissemination and multiparty conferencing tools have made the design and development of efficient multicast techniques in mobile ad-hoc networking environments a necessity and not just a desire. Multicast protocols in mobile adhoc networks have been an area of active research for the past few years. In this dissertation, protocols and architectures for supporting multicast services are proposed, analyzed and evaluated in mobile ad-hoc wireless networks. In the first chapter, the activities and recent advances are summarized in this work-in-progress area by identifying the main issues and challenges that multicast protocols are facing in mobile ad-hoc networking environments and by surveying several existing multicasting protocols. a classification of the current multicast protocols is presented, the functionality of the individual existing protocols is discussed, and a qualitative comparison of their characteristics is provided according to several distinct features and performance parameters. In the second chapter, a novel mobility-based clustering strategy that facilitates the support of multicast routing and mobility management is presented in mobile ad-hoc networks. In the proposed structure, mobile nodes are organized into nonoverlapping clusters which have adaptive variable-sizes according to their respective mobility. The mobility-based clustering (MBC) approach which is proposed uses combination of both physical and logical partitions of the network (i.e. geographic proximity and functional relation between nodes, such as mobility pattern etc.). In the third chapter, an entropy-based modeling framework for supporting and evaluating the stability is proposed in mobile ad-hoc wireless networks. The basic motivations of the proposed modeling approach stem from the commonality observed in the location uncertainty in mobile ad-hoc wireless networks and the concept of entropy. In the fourth chapter, a Mobility-based Hybrid Multicast Routing (MHMR) protocol suitable for mobile ad-hoc networks is proposed. The MHMR uses the MBC algorithm as the underlying structure. The main features that the proposed protocol introduces are the following: a) mobility based clustering and group based hierarchical structure, in order to effectively support the stability and scalability, b) group based (limited) mesh structure and forwarding tree concepts, in order to support the robustness of the mesh topologies which provides limited redundancy and the efficiency of tree forwarding simultaneously, and c) combination of proactive and reactive concepts which provide the low route acquisition delay of proactive techniques and the low overhead of reactive methods. In the fifth chapter, an architecture for supporting geomulticast services with high message delivery accuracy is presented in mobile ad-hoc wireless networks. Geomulticast is a specialized location-dependent multicasting technique, where messages are multicast to some specific user groups within a specific zone. An analytical framework which is used to evaluate the various geomulticast architectures and protocols is also developed and presented. The last chapter concludes the dissertation

Hybrid User Pairing for Spectral and Energy Efficiencies in Multiuser MISO-NOMA Networks with SWIPT

In this paper, we propose a novel hybrid user pairing (HUP) scheme in multiuser multiple-input single-output nonorthogonal multiple access networks with simultaneous wireless information and power transfer. In this system, two information users with distinct channel conditions are optimally paired while energy users perform energy harvesting (EH) under non-linearity of the EH circuits. We consider the problem of jointly optimizing user pairing and power allocation to maximize the overall spectral efficiency (SE) and energy efficiency (EE) subject to userspecific quality-of-service and harvested power requirements. A new paradigm for the EE-EH trade-off is then proposed to achieve a good balance of network power consumption. Such design problems are formulated as the maximization of nonconcave functions subject to the class of mixed-integer non-convex constraints, which are very challenging to solve optimally. To address these challenges, we first relax binary pairing variables to be continuous and transform the design problems into equivalent non-convex ones, but with more tractable forms. We then develop low-complexity iterative algorithms to improve the objectives and converge to a local optimum by means of the inner approximation framework. Simulation results show the convergence of proposed algorithms and the SE and EE improvements of the proposed HUP scheme over state-of-the-art designs. In addition, the effects of key parameters such as the number of antennas and dynamic power at the BS, target data rates, and energy threshold, on the system performance are evaluated to show the effectiveness of the proposed schemes in balancing resource utilization

Short-Packet Communications in Multi-Hop WPINs: Performance Analysis and Deep Learning Design

In this paper, we study short-packet communications (SPCs) in multi-hop wireless-powered Internet-of-Things networks (WPINs), where IoT devices transmit short packets to multiple destination nodes by harvesting energy from multiple power beacons. To improve system block error rate (BLER) and throughput, we propose a best relay-best user (bR-bU) selection scheme with an accumulated energy harvesting mechanism. Closed-form expressions for the BLER and throughput of the proposed scheme over Rayleigh fading channels are derived and the respective asymptotic analysis is also carried out. To support real-time settings, we design a deep neural network (DNN) framework to predict the system throughput under different channel settings. Numerical results demonstrate that the proposed bR-bU selection scheme outperforms several baseline ones in terms of the BLER and throughput, showing to be an efficient strategy for multi-hop SPCs. The resulting DNN can estimate accurately the throughput with low execution time. The effects of message size on reliability and latency are also evaluated and discussed

A Location-Based Algorithm for Supporting Multicast Routing in Mobile Ad-Hoc Networks

Part 13: UMASInternational audienceIn this paper, we propose a location-based algorithm for supporting multicast routing in mobile ad-hoc networks. Instead of having routing paths in advanced to forward data packets from source node to multicast receivers, this algorithm let each node which receives data packets independently, adaptively determines the routing paths to forward data packets based on the information of its neighbor nodes. Before forwarding data packets, mobile node checks and uses one of its neighbor nodes as the next hop. Therefore, the availability of routing segments is ensured, providing high performance even in high mobility environment. The performance of this algorithm for multicast routing is validated via simulation using OPNET

Exploiting Opportunistic Scheduling for Physical-Layer Security in Multitwo User NOMA Networks

In this paper, we address the opportunistic scheduling in multitwo user NOMA system consisting of one base station, multinear user, multifar user, and one eavesdropper. To improve the secrecy performance, we propose the users selection scheme, called best-secure-near-user best-secure-far-user (BSNBSF) scheme. The BSNBSF scheme aims to select the best near-far user pair, whose data transmission is the most robust against the overhearing of an eavesdropper. In order to facilitate the performance analysis of the BSNBSF scheme in terms of secrecy outage performance, we derive the exact closed-form expression for secrecy outage probability (SOP) of the selected near user and the tight approximated closed-form expression for SOP of the selected far user, respectively. Additionally, we propose the descent-based search method to find the optimal values of the power allocation coefficients that can minimize the total secrecy outage probability (TSOP). The developed analyses are corroborated through Monte Carlo simulation. Comparisons with the random-near-user random-far-user (RNRF) scheme are performed and show that the proposed scheme significantly improves the secrecy performance

Cooperative Spectrum Sensing Schemes with the Interference Constraint in Cognitive Radio Networks

In this paper, we propose cooperative spectrum sensing schemes, called decode-and-forward cooperative spectrum sensing (DF-CSS) scheme and amplify-and-forward cooperative spectrum sensing (AF-CSS) scheme, in cognitive radio networks. The main goals and features of the proposed cooperative spectrum sensing schemes are as follows: first, we solve the problem of high demand for bandwidth in a soft decision scheme using in our proposed schemes. Furthermore, the impact of transmission power of relaying users which is determined by the interference constraint on sensing performance of cooperative spectrum sensing schemes is also investigated. Second, we analyze the sensing performance of our proposed cooperative spectrum sensing schemes in terms of detection probability and interference probability, respectively. We take into account the interference caused by secondary user (SU) to primary user (PU) in the case that the transmission power of the relaying users exceeds a predefined interference constraint assigned by the primary user. The simulation results show that in cooperative spectrum sensing schemes the total sensing performance depends not only on the interference tolerance level, but also on the relay protocols used. We also prove that high transmission power of relaying users increases the interference between the secondary networks and the primary network