Fast and Efficient Radio Resource Allocation in Dynamic Ultra-Dense Heterogeneous Networks

Ultra-dense network (UDN) is considered as a promising technology in 5G wireless networks. In an UDN network, dynamic traffic patterns can lead to a high computational complexity and an excessive communications overhead with traditional resource allocation schemes. In this paper, a new resource allocation scheme presenting a low computational overhead and a low subband handoff rate in a dynamic ultra-dense heterogeneous network is presented. The scheme first defines a new interference estimation method that constructs network interference state map, based on which a radio resource allocation scheme is proposed. The resource allocation problem is a MAX-K cut problem and can be solved through a graph- theoretical approach. System level simulations reveal that the proposed scheme decreases the subband handoff rate by 30% with less than 3.2% network throughput degradation

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

Cooperative control of relay based cellular networks

PhDThe increasing popularity of wireless communications and the higher data requirements of new types of service lead to higher demands on wireless networks. Relay based cellular networks have been seen as an effective way to meet users’ increased data rate requirements while still retaining the benefits of a cellular structure. However, maximizing the probability of providing service and spectrum efficiency are still major challenges for network operators and engineers because of the heterogeneous traffic demands, hard-to-predict user movements and complex traffic models. In a mobile network, load balancing is recognised as an efficient way to increase the utilization of limited frequency spectrum at reasonable costs. Cooperative control based on geographic load balancing is employed to provide flexibility for relay based cellular networks and to respond to changes in the environment. According to the potential capability of existing antenna systems, adaptive radio frequency domain control in the physical layer is explored to provide coverage at the right place at the right time. This thesis proposes several effective and efficient approaches to improve spectrum efficiency using network wide optimization to coordinate the coverage offered by different network components according to the antenna models and relay station capability. The approaches include tilting of antenna sectors, changing the power of omni-directional antennas, and changing the assignment of relay stations to different base stations. Experiments show that the proposed approaches offer significant improvements and robustness in heterogeneous traffic scenarios and when the propagation environment changes. The issue of predicting the consequence of cooperative decisions regarding antenna configurations when applied in a realistic environment is described, and a coverage prediction model is proposed. The consequences of applying changes to the antenna configuration on handovers are analysed in detail. The performance evaluations are based on a system level simulator in the context of Mobile WiMAX technology, but the concepts apply more generally

Energy efficiency with quality of service constraints in heterogenous networks

The Fifth Generation (5G) cellular network is a new technology that is driven by the demand of high data usage, large number of wireless devices and better Quality of Service (QoS). An important challenge for 5G is the energy consumption which is causing the wireless communication networks to be one of the main contributors of the global worming. Thus, energy efficiency becomes an important aspect in designing the wireless communication networks. In this thesis, we study different approaches for Energy Efficient (EE) operation of Small Base Stations (SBSs) in Heterogenous wireless Networks (HetNets). First, we focus on enhancing energy efficiency in heterogenous networks, where Macro BSs (MBSs) and SBSs co-exist, by presenting a sleeping strategy. In the sleeping strategy SBSs serving few or no users are turned off and their users and resources are offloaded to neighboring SBSs. However, adapting the sleeping strategy will affect the lifetime of the electronics of the SBSs, due to the frequent change of power level between turning ON and OFF the SBS. Therefore, in order to maximize energy savings, we formulate an optimization problem that provides an optimal user association and SBSs sleeping strategy for the entire network, while minimizing the total numbers of the switching of SBSs ON and OFF. Furthermore, an other approach consider is the deactivated SBSs are equipped with two power sources, a harvested energy (HE) source and a grid power source, where first the SBS will use its available HE to serve the associated users. Then, the SBS will request any shortage of its energy from other active or deactivated SBSs which have surplus of HE. Finally, if there is still shortage in energy, the SBS will use the power drawn from the grid. However, since the formulated problem is a Mixed Integer NonLinear Problem (MINLP), Generalized Bender Decomposition (GBD) is proposed to decompose the problem into two subproblems. Moreover, a new heuristic approach is proposed to provide a computational efficient algorithm to solve and optimize the user association and energy harvesting of the system model. A new UEs’ prediction method is introduced to provide a future information for the model and to apply an accurate designing parameters. This method is based on a combined approach of Non-linear Autoregressive with External input(NARX) and probabilistic Latent semantic Analysis (pLSA) to provide accurate prediction for multiple steps. Therefore, we consider integrating the powerful Machine Learning (ML) techniques to provide solution of the system model with less computation demands. Thus, we introduced an efficient less complex approach that is based on synthetically generating data from the optimization problem and employing it to train and configure an Artificial Neural Network. An extensive simulation results are presented to show the effectiveness of our approaches in comparison to the optimal results

A comprehensive survey on radio resource management in 5G HetNets: current solutions, future trends and open issues

The 5G network technologies are intended to accommodate innovative services with a large influx of data traffic with lower energy consumption and increased quality of service and user quality of experience levels. In order to meet 5G expectations, heterogeneous networks (HetNets) have been introduced. They involve deployment of additional low power nodes within the coverage area of conventional high power nodes and their placement closer to user underlay HetNets. Due to the increased density of small-cell networks and radio access technologies, radio resource management (RRM) for potential 5G HetNets has emerged as a critical avenue. It plays a pivotal role in enhancing spectrum utilization, load balancing, and network energy efficiency. In this paper, we summarize the key challenges i.e., cross-tier interference, co-tier interference, and user association-resource-power allocation (UA-RA-PA) emerging in 5G HetNets and highlight their significance. In addition, we present a comprehensive survey of RRM schemes based on interference management (IM), UA-RA-PA and combined approaches (UA-RA-PA + IM). We introduce a taxonomy for individual (IM, UA-RA-PA) and combined approaches as a framework for systematically studying the existing schemes. These schemes are also qualitatively analyzed and compared to each other. Finally, challenges and opportunities for RRM in 5G are outlined, and design guidelines along with possible solutions for advanced mechanisms are presented

マクロセルにオーバーレイするスモールセルのための層間干渉低減に関する研究

The huge number of mobile terminals in use and the radio frequency scarceness are the relevant issues for future wireless communications. Frequency sharing has been considered to solve the problem. Addressing the issues has led to a wide adoption of small cell networks particularly femtocells overlaid onto macrocell or small cells implemented with the support of distributed antenna systems (DASs). Small cell networks improve link quality and frequency reuse. Spectrum sharing improves the usage efficiency of the licensed spectrum. A macrocell underlaid with femtocells constitutes a typical two-tier network for improving spectral efficiency and indoor coverage in a spectrum sharing environment. Considering the end-user access control over the small cell base station (SBS), with shared usage of the macrocell’s spectrum, this dissertation contribution is an investigation of mitigation techniques of crosstier interference. Such cross-tier interference mitigation leads to possible implementation of multi-tier and heterogeneous networks. The above arguments underpin our work which is presented in the hereby dissertation. The contributions in this thesis are three-fold. Our first contribution is an interference cancellation scheme based on the transmitter symbols fed back to the femtocell base station (FBS) undergoing harmful cross-tier interference. We propose a cross-tier interference management between the FBS and the macrocell base station (MBS) in uplink communications. Our proposal uses the network infrastructure for interference cancellation at the FBS. Besides, we profit from terminal discovery to derive the interference level from the femtocell to the macrocell. Thus, additionally, we propose an interference avoidance method based on power control without cooperation from the MBS. In our second contribution, we dismiss the use of the MBS for symbol feedback due to delay issues. In a multi-tier cellular communication system, the interference from one tier to another, denoted as cross-tier interference, is a limiting factor for the system performance. In spectrum-sharing usage, we consider the uplink cross-tier interference management of heterogeneous networks using femtocells overlaid onto the macrocell. We propose a variation of the cellular architecture and introduce a novel femtocell clustering based on interference cancellation to enhance the sum rate capacity. Our proposal is to use a DAS as an interface to mitigate the cross-tier interference between the macrocell and femtocell tiers. In addition, the DAS can forward the recovered data to the macrocell base station (MBS); thus, the macrocell user can reduce its transmit power to reach a remote antenna unit (RAU) located closer than the MBS. By distributing the RAUs within the macrocell coverage, the proposed scheme can mitigate the cross-tier interference at different locations for several femtocell clusters. Finally, we address the issue of cross-tier interference mitigation in heterogeneous cognitive small cell networks comparing equal and unequal signal-to-noise ratio (SNR) branches in multi-input multi-output (MIMO) Alamouti scheme. Small cell networks enhance spectrum efficiency by handling the indoor traffic of mobile networks on a frequency-reuse operation. Because most of the current mobile traffic happens indoor, we introduce a prioritization shift by imposing a threshold on the outage generated by the outdoor mobile system to the indoor small cells. New closed-form expressions are derived to validate the proposed bit error rate (BER) function used in our optimization algorithm. We propose a joint transmit antenna selection and power allocation which minimizes the proposed BER function of the outdoor mobile terminal. The optimization is constrained by the outage at the small cell located near the cooperating transmit relays. Such constraint improves the initialization of the iterative algorithm compared to randomly choosing initial points. The proposed optimization yields a dynamic selection of the relays with power control pertaining to the outdoor mobile terminal performance.電気通信大学201