Resource Optimization in Multi-Tier HetNets Exploiting Multi-Slope Path Loss Model

Current resource allocation techniques in cellular networks are largely based on single-slope path loss model, which falls short in accurately capturing the effect of physical environment. The phenomenon of densification makes cell patterns more irregular; therefore, the multi-slope path loss model is more realistic to approximate the increased variations in the links and interferences. In this paper, we investigate the impacts of multi-slope path loss models, where different link distances are characterized by different path loss exponents. We propose a framework for joint user association, power and subcarrier allocation on the downlink of a heterogeneous network (HetNet). The proposed scheme is formulated as a weighted sum rate maximization problem, ensuring the users' quality-of-service requirements, namely users' minimum rate, and the base stations' (BSs) maximum transmission power. We then compare the performance of the proposed approach under different path loss models with demonstrate the effectiveness of dual-slope path loss model in comparison to the single-slope path loss model. Simulation results show that the dual-slope model leads to significant improvement in network's performance in comparison to the standard single-slope model by accurately approximating the path loss exponent dependence on the link distance. Moreover, it improves the user offloading from macrocell BS to small cells by connecting the users to nearby BSs with minimal attenuation. It has been shown that the path loss exponents significantly influence the user association lying across the critical radius in the case of the dual-slope path loss model

An Overview of Mobility Management Mechanisms and the Related Challenges in 5G Networks and Beyond, Journal of Telecommunications and Information Technology, 2023, nr 2

Ensuring a seamless connection with various types of mobile user equipment (UE) items is one of the more significant challenges facing different generations of wireless systems. However, enabling the high-band spectrum – such as the millimeter wave (mmWave) band – is also one of the important factors of 5G networks, as it enables them to deal with increasing demand and ensures high coverage. Therefore, the deployment of new (small) cells with a short range and operating within the mmWave band is required in order to assist the macro cells which are responsible for operating long-range radio connections. The deployment of small cells results in a new network structure, known as heterogeneous networks (HetNets). As a result, the number of passthrough cells using the handover (HO) process will be dramatically increased. Mobility management (MM) in such a massive network will become crucial, especially when it comes to mobile users traveling at very high speeds. Current MM solutions will be ineffective, as they will not be able to provide the required reliability, flexibility, and scalability.Thus, smart algorithms and techniques are required in future networks. Also, machine learning (ML) techniques are perfectly capable of supporting the latest 5G technologies that are expected to deliver high data rates to upcoming use cases and services, such as massive machine type communications (mMTC), enhanced mobile broadband (eMBB), and ultra-reliable low latency communications (uRLLC). This paper aims to review the MM approaches used in 5G HetNets and describes the deployment of AI mechanisms and techniques in ″connected mode″ MM schemes. Furthermore, this paper addresses the related challenges and suggests potential solutions for 5G networks and beyond

Intelligent Resource Allocation in 5G Multi-Radio Heterogeneous Networks

The fast-moving evolution of wireless networks, which started less than three decades ago, has resulted in worldwide connectivity and influenced the development of a global market in all related areas. However, in recent years, the growing user traffic demands have led to the saturation of licensed and unlicensed frequency bands regarding capacity and load-over-time. On the physical layer the used spectrum efficiency is already close to Shannon’s limit; however the traffic demand continues to grow, forcing mobile network operators and equipment manufacturers to evaluate more effective strategies of the wireless medium access.One of these strategies, called cell densification, implies there are a growing number of serving entities, with the appropriate reduction of the per-cell coverage area. However, if implemented blindly, this approach will lead to a significant growth in the average interference level and overhead control signaling, which are both required to allow sufficient user mobility. Furthermore, the interference is also affected by the increasing variety of radio access technologies (RATs) and applications, often deployed without the necessary level of cooperation with technologies that are already in place.To overcome these problems today’s telecommunication standardization groups are trying to collaborate. That is why the recent agenda of the fifth generation wireless networks (5G) includes not only the development schedules for the particular technologies but also implies there should be an expansion of the appropriate interconnection techniques. In this thesis, we describe and evaluate the concept of heterogeneous networks (HetNets), which involve the cooperation between several RATs.In the introductory part, we discuss the set of the problems, related to HetNets, and review the HetNet development process. Moreover, we show the evolution of existing and potential segments of the multi-RAT 5G network, together with the most promising applications, which could be used in future HetNets.Further, in the thesis, we describe the set of key representative scenarios, including three-tier WiFi-LTE multi-RAT deployment, MTC-enabled LTE, and the mmWave-based network. For each of these scenarios, we define a set of unsolved issues and appropriate solutions. For the WiFi-LTE multi-RAT scenario, we develop the framework, enabling intelligent and flexible resource allocation between the involved RATs. For MTC-enabled LTE, we study the effect of massive MTC deployments on the performance of LTE random access procedure and propose some basic methods to improve its efficiency. Finally, for the mmWave scenario, we study the effects of connectivity strategies, human body blockage and antenna array configuration on the overall network performance. Next, we develop a set of validated analytical and simulation-based techniques which allow us to evaluate the performance of proposed solutions. At the end of the introductory part a set of HetNet-related demo activities is demonstrated