Scalable MAC protocol for D2D communication for future 5G networks

University of Technology Sydney. Faculty of Engineering and Information Technology.Due to the steep growth in mobile data traffic, it will be a challenge for 5G networks to ful-fill the requirement using limited resources in licensed spectrum. However, the joint deployment of smaller cells in the Macro-cell has attempted to overcome this issue. It is observed that users are adversely affected by limited resources in the licensed band. Due to the scarcity of resources in the licensed band, it is better to deploy a small cell operating at an unlicensed spectrum like WLAN. Establishing Device to Device communication (D2D) in the cooperative deployment of cellular networks and WLAN can accommodate the on growing user data demand by intelligently allocating the resources, hence, forming a centralized control in a distributive manner. This Thesis gives a detailed overview of all the LTE technologies operating in an unlicensed band which includes; LTE-U, LAA, LWA, and MuLTEfire. The technologies are compared with extensive simulation and further D2D communication is applied in these technologies to observe their behaviour. This Thesis also introduces a three-tier architecture for next generation 5G networks which can offload traffic from cellular networks to WLAN in a dense environment. It proposes a Scalable MAC Protocol (SC-MP) to efficiently allocate resources for Wi-Fi users with D2D communication. SC-MP will allocate WLAN resources to the normal users in a centralized and efficient manner based on a novel PCF strategy, which will develop a centralized control in a distributive manner. The SC-MP is compared to legacy DCF protocol defined in IEEE 802.11 through extensive simulation to evaluate the network performance. The key result is that SC-MP is able to improve the performance compared to DCF for metrics that include; network throughput, network capacity, and network delay. Furthermore, the thesis gives a detailed mathematical analysis of SC-MP using Markov modelling and semi-Markov modelling. Effective capacity is derived using three-state semi-Markov modelling for the proposed SC-MP. Analytical results are validated through the simulation results. In addition, an optimal queue scheduling and resource allocation problem with QoS guaranteed between the licensed and unlicensed band is formulated to minimize the bandwidth of licensed spectrum and maximize the aggregated effective capacity of a three-tier network. The results proved that the proposed SC-MP can perform better compared with the state of art

Design of LTE-Wi-Fi Aggregation with Multiple Wi-Fi APs for Heterogenous Network

The growth in mobile data traffic is forcing network operators to find ways to deliver higher bandwidth, better coverage, and better quality of service (QoS) at lower development costs. One method that can be used to meet this need is the aggregation technique. Aggregation techniques that run on several different technologies are called heterogeneous networks (HetNet). Recently, some advanced technologies have been proposed to aggregate different long-term evolution (LTE) carriers or different radio access technologies (RAT) to generate higher bandwidth. Many efforts have been made to improve the throughput of heterogeneous networks. One of the factors that affects the maximum LTE-WLAN aggregation (LWA) throughput is the Wi-Fi access point (AP) signal strength. Since the power of small cells is very low, the LWA range is not very large, so the LWA range needs to be increased. This paper proposes the solution that can be implemented by using multiple Wi-Fi Aps scheme. From the experiments, it found that LWA with multiple Wi-Fi APs has better signal strength than LWA with a single Wi-Fi AP. LWA with multiple Wi-Fi APs further increase the coverage of the network

Analytical Performance Evaluation of Cooperative and Multi-Radio Concepts in Emerging Wireless Networks

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A survey of multi-access edge computing in 5G and beyond : fundamentals, technology integration, and state-of-the-art

Driven by the emergence of new compute-intensive applications and the vision of the Internet of Things (IoT), it is foreseen that the emerging 5G network will face an unprecedented increase in traffic volume and computation demands. However, end users mostly have limited storage capacities and finite processing capabilities, thus how to run compute-intensive applications on resource-constrained users has recently become a natural concern. Mobile edge computing (MEC), a key technology in the emerging fifth generation (5G) network, can optimize mobile resources by hosting compute-intensive applications, process large data before sending to the cloud, provide the cloud-computing capabilities within the radio access network (RAN) in close proximity to mobile users, and offer context-aware services with the help of RAN information. Therefore, MEC enables a wide variety of applications, where the real-time response is strictly required, e.g., driverless vehicles, augmented reality, robotics, and immerse media. Indeed, the paradigm shift from 4G to 5G could become a reality with the advent of new technological concepts. The successful realization of MEC in the 5G network is still in its infancy and demands for constant efforts from both academic and industry communities. In this survey, we first provide a holistic overview of MEC technology and its potential use cases and applications. Then, we outline up-to-date researches on the integration of MEC with the new technologies that will be deployed in 5G and beyond. We also summarize testbeds and experimental evaluations, and open source activities, for edge computing. We further summarize lessons learned from state-of-the-art research works as well as discuss challenges and potential future directions for MEC research

PCF-based LTE Wi-Fi aggregation for coordinating and offloading the cellular traffic to D2D network

© 2018 IEEE. Device-to-device (D2D) communication is a promising technology towards 5G networks. D2D communication can offload traffic using licensed/unlicensed band by establishing a direct communication between two users without traversing the base station or core network. However, one of the major challenges of D2D communication is resource allocation and guaranteeing quality-of-service (QoS). In this paper, we establish an optimal queuing scheduling and resource allocation problem for three-tier heterogeneous network based on LTE Wi-Fi aggregation, to offload voice/multimedia traffic from licensed band to unlicensed band using scalable MAC protocol (SC-MP) under various static delay constraints. The access mechanism used for Wi-Fi in SC-MP is point coordination function, which further offloads the multimedia traffic using D2D communication in unlicensed band. Resource allocation and optimal joint queuing scheduling problems are formulated with diverse QoS guarantee between licensed and unlicensed band to minimize the bandwidth of licensed band. Furthermore, an iterative algorithm is proposed to express the nonconvex problem as a series of subproblems based on block coordinate descent and difference of two convex functions (D.C) program. We have simulated the proposed scheme using two scenarios: Voice traffic using licensed band and voice traffic using both licensed and unlicensed band, whereas multimedia traffic uses unlicensed band for both the scenarios. The simulation results show that both the schemes perform better than the existing scheme and scenario 2 outperforms scenario 1