Distributed radio resource management in LTE-advanced networks with type 1 relay

Long Term Evolution (LTE)-Advanced is proposed as a candidate of the 4th generation (4G) mobile telecommunication systems. As an evolved version of LTE, LTE- Advanced is also based on Orthogonal Frequency Division Multiplexing (OFDM) and in addition, it adopts some emerging technologies, such as relaying. Type I relay nodes, de_ned in LTE-Advanced standards, can control their cells with their own reference signals and have Radio Resource Management (RRM) functionalities. The rationale of RRM is to decide which resources are allocated to which users for optimising performance metrics, such as throughput, fairness, power consumption and Quality of Service (QoS). The RRM techniques in LTE-Advanced networks, including route selection, resource partitioning and resource scheduling, are facing new challenges brought by Type 1 relay nodes and increasingly becoming research focuses in recent years. The research work presented in this thesis has made the following contributions. A service-aware adaptive bidirectional optimisation route selection strategy is proposed to consider both uplink optimisation and downlink optimisation according to service type. The load between di_erent serving nodes, including eNBs and relay nodes, are rebalanced under the _xed resource partitioning. The simulation results show that larger uplink throughputs and bidirectional throughputs can be achieved, compared with existing route selection strategies. A distributed two-hop proportional fair resource allocation scheme is proposed in order to provide better two-hop end-to-end proportional fairness for all the User Equipments (UEs), especially for the relay UEs. The resource partitioning is based on the cases of none Frequency Reuse (FR) pattern, full FR pattern and partial FR patterns. The resource scheduling in access links and backhaul links are considered jointly. A proportional fair joint route selection and resource partitioning algorithm isproposed to obtain an improved solution to the two-hop Adaptive Partial Frequency Reusing (APFR) problem with one relay node per cell. In addition, two special situations of APFR, full FR and no FR, are utilised to narrow the iterative search range of the proposed algorithm and reduce its complexity

Green Cellular Networks: A Survey, Some Research Issues and Challenges

Energy efficiency in cellular networks is a growing concern for cellular operators to not only maintain profitability, but also to reduce the overall environment effects. This emerging trend of achieving energy efficiency in cellular networks is motivating the standardization authorities and network operators to continuously explore future technologies in order to bring improvements in the entire network infrastructure. In this article, we present a brief survey of methods to improve the power efficiency of cellular networks, explore some research issues and challenges and suggest some techniques to enable an energy efficient or "green" cellular network. Since base stations consume a maximum portion of the total energy used in a cellular system, we will first provide a comprehensive survey on techniques to obtain energy savings in base stations. Next, we discuss how heterogeneous network deployment based on micro, pico and femto-cells can be used to achieve this goal. Since cognitive radio and cooperative relaying are undisputed future technologies in this regard, we propose a research vision to make these technologies more energy efficient. Lastly, we explore some broader perspectives in realizing a "green" cellular network technologyComment: 16 pages, 5 figures, 2 table

Spectrum Leasing as an Incentive towards Uplink Macrocell and Femtocell Cooperation

The concept of femtocell access points underlaying existing communication infrastructure has recently emerged as a key technology that can significantly improve the coverage and performance of next-generation wireless networks. In this paper, we propose a framework for macrocell-femtocell cooperation under a closed access policy, in which a femtocell user may act as a relay for macrocell users. In return, each cooperative macrocell user grants the femtocell user a fraction of its superframe. We formulate a coalitional game with macrocell and femtocell users being the players, which can take individual and distributed decisions on whether to cooperate or not, while maximizing a utility function that captures the cooperative gains, in terms of throughput and delay.We show that the network can selforganize into a partition composed of disjoint coalitions which constitutes the recursive core of the game representing a key solution concept for coalition formation games in partition form. Simulation results show that the proposed coalition formation algorithm yields significant gains in terms of average rate per macrocell user, reaching up to 239%, relative to the non-cooperative case. Moreover, the proposed approach shows an improvement in terms of femtocell users' rate of up to 21% when compared to the traditional closed access policy.Comment: 29 pages, 11 figures, accepted at the IEEE JSAC on Femtocell Network

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

On the optimal operation of wireless networks

With the ever increasing mobile traffic in wireless networks, radio frequency spectrum is becoming limited and overcrowded. To address the radio frequency spectrum scarcity problem, researchers proposed advanced radio technology-Cognitive Radio to make use of the uncommonly used and under-utilized licensed bands to improve overall spectrum efficiency. Mobile service providers also deploy small base stations on the streets, into shopping center and users\u27 households in order to improve spectrum efficiency per area. In this thesis, we study cooperation schemes in cognitive radio networks as well as heterogeneous networks to reuse the existing radio frequency spectrum intelligently and improve network throughput and spectrum efficiency, reduce network power consumption and provide network failure protection capability. In the first work of the thesis, we study a multicast routing problem in Cognitive Ratio Networks (CRNs). In this work, all Secondary Users (SUs) are assumed not self interested and they are willing to provide relay service for source SUs. We propose a new network modeling method, where we model CRNs using a Multi-rate Multilayer Hyper-Graph (MMHG). Given a multicast session of the MMHG, our goal is to find the multicast routing trees that minimize the worst case end-to-end delay, maximize the multicast rate and minimize the number of transmission links used in the multicast tree. We apply two metaheuristic algorithms (Multi-Objective Ant Colony System optimization algorithm (MOACS) and Archived Multi-Objective Simulated Annealing Optimization Algorithm (AMOSA)) in solving the problem. We also study the scheduling problem of multicast routing trees obtained from the MMHG model. In the second work of the thesis, we study the cell outage compensation function of the self-healing mechanism using network cooperation scheme. In a heterogeneous network environment with densely deployed Femto Base Stations (FBSs), we propose a network cooperation scheme for FBSs using Coordinated Multi-Point (CoMP) transmission and reception with joint processing technique. Different clustering methods are studied to improve the performance of the network cooperation scheme. In the final work of the thesis, we study the user cooperative multi-path routing solution for wireless Users Equipment (UEs)\u27 streaming application using auction theory. We assume that UEs use multi-path transport layer service, and establish two paths for streaming events, one path goes through its cellular link, another path is established using a Wi-Fi connection with a neighbor UE. We study user coordinated multi-path routing solution with two different energy cost functions (LCF and EAC) and design user cooperative real-time optimization and failure protection operations for the streaming application. To stimulate UEs to participate into the user cooperation operation, we design a credit system enabled with auction mechanism. Simulation results in this thesis show that optimal cooperation operations among network devices to reuse the existing spectrum wisely are able to improve network performance considerably. Our proposed network modeling approach in CRN helps reduce the complicated multicast routing problem to a simple graph problem, and the proposed algorithms can find most of the optimal multicast routing trees in a short amount of time. In the second and third works, our proposed network cooperation and user cooperation approaches are shown to provide better UEs\u27 throughput compared to non-cooperation schemes. The network cooperation approach using CoMP provides failure compensation capability by preventing the system sum rate loss from having the same speed of radio resource loss, and this is done without using additional radio resources and will not have a significant adverse effect on the performance of other UEs. The user cooperation approach shows great advantage in improving service rate, improving streaming event success rate and reducing energy consumption compared to non-cooperation solution