During the last decade, the average mobile wireless data usage per person has tremendously increased. An even faster growth of the traffic demand is expected for the incoming years, due to several factors such as the increasing global population, the spread of the Internet of things (IoT), and the development of advanced technologies that require a higher amount of data. While mobile communication technologies have rapidly evolved to meet this need in the most usual situations, it is expected that the sixth generation (6G) of mobile connectivity will be the first one paying considerable attention to under-connected environments such as low-income, remote, or disaster-struck regions. Many specialized researchers and entrepreneurs are trying to design and implement alternative network architectures specifically meant for enhancing the performances of the current telecommunication (telecom) infrastructure. In particular, the use of aerial base stations (ABSs) has received considerable attention due to the main advantages of easy deployability and low-cost that are typical of unmanned aerial vehicles (UAVs), which are available in several fashions depending on the application; moreover, UAVs are also eligible to carry reflective intelligent surfaces (RISs), which represent a promising technology that allows to reflect signals towards specific directions. Another possibility that we have investigated consists in integrating the transceivers inside or atop existing rural wind turbine (WT) towers, in order to increase the coverage radius while avoiding the cost of building a separate telecom infrastructure. A powerful mathematical tool for evaluating the performance metrics of either terrestrial, aerial, or vertical heterogeneous wireless networks is stochastic geometry (SG), since it can be used to model the locations of the base stations (BSs) according to tractable spatial distributions (with either a fixed or a random cardinality) in order to imitate the typical deployments of the nodes made in realistic scenarios; in particular, in this work we focus on rural and post-disaster situations. SG makes use of point processes to model networks' topologies. The developed spatial models, in turn, allow us to analyze the quality of service (QoS) experienced by the typical user served by the proposed networks. To this extent, we creatively and efficiently studied our inhomogeneous systems by making use of what we call the indicator method, meaning that we do not subdivide the ground plane in multiple homogeneous sub-regions, but we use indicator functions to provide general expressions that are valid over the entire ground plane. To prove the effectiveness of the novel architectures, insightful comparisons with the conventional ones are presented.

No / In the telecommunication networks the introduction of Next Generation Wireless Networks (NGWN) has been described as the most significant change in wireless communication. The convergence of different access networks in NGWN allows generalized mobility, consistency and ubiquitous provision of services to mobile users. The general target of NGWN is to transport different types of information like voice, data, and other media like video in packets form like IP. The NGWNs offer significant savings in costs to the operators along with new and interesting services to the consumers. Major challenges in NGWN are efficient resource utilization, maintaining service quality, reliability and the security. This paper proposes a solution for seamless load aware Radio Access Technology (RAT) selection based on interworking of different RATs in NGWN. In this paper novel load balancing algorithms have been proposed which have been simulated on the target network architecture for TCP data services. The IEEE 802.21 Media Independent Handover (MIH) is utilized in load balancing specifically for mobility management, which enable low handover latency by reducing the target network detection time. The proposed method considers the network type, signal strength, data rate and network load as primary decision parameters for RAT selection process and consists of two different algorithms, one located in the mobile terminal and the other at the network side. The network architecture, the proposed load balancing framework and RAT selection algorithms were simulated using NS2. Different attributes like load distribution in the wireless networks and average throughput to evaluate the effects of load balancing in considered scenarios.

No / The ever increasing user QoS demands and emergence of new user applications make job of network operators and manufacturers more challenging for efficiently optimisation and managing radio resources in radio the radio resources pools of different wireless networks. A group of strategies or mechanisms which are collectively responsible for efficient utilisation of radio resources available within the Radio Access Technologies (RAT) are termed as Radio Resource Management (RRM). The traditional RRM strategies are implemented independently in each RAT, as each RRM strategy considers attributes of a particular access technology. Therefore traditional RRM strategies are not suitable for heterogeneous wireless networks. Common Radio Resource Management (CRRM) or joint radio resource management (JRRM) strategies are proposed for coordinating radio resource management between multiple RATs in an improved manner. In this paper a fuzzy algorithm based CRRM strategy is presented to efficiently utilise the available radio resources in heterogeneous wireless networks. The proposed CRRM strategy balances the load in heterogeneous wireless networks and avoids the unwanted congestion situation. The results such as load distribution, packet drop rate and average throughput at mobile nodes are used to demonstrate the benefits of load balancing in heterogeneous wireless networks using proposed strategy.