Resource Allocation and Performance Optimization in Wireless Networks

As wireless networks continue streaking through more aspects of our lives, it is seriously constrained by limited network resources, in terms of time, frequency and power. In order to enhance performance for wireless networks, it is of great importance to allocate resources smartly based on the current network scenarios. The focus of this dissertation is to investigate radio resource management algorithms to optimize performance for different types of wireless networks. Firstly, we investigate a joint optimization problem on relay node placement and route assignment for wireless sensor networks. A heuristic binary integer programming algorithm is proposed to maximize the total number of information packets received at the base station during the network lifetime. We then present an optimization algorithm based on binary integer programming for relay node assignment with the current node locations. Subsequently, a heuristic algorithm is applied to move the relay nodes to the locations iteratively to better serve their associated edge nodes. Secondly, as traditional goal of maximizing the total throughput can result in unbalanced use of network resources, we study a joint problem of power control and channel assignment within a wireless mesh network such that the minimal capacity of all links is maximized. This is essentially a fairness problem. We develop an upper bound for the objective by relaxing the integer variables and linearization. Subsequently, we put forward a heuristic approach to approximate the optimal solution, which tries to increase the minimal capacity of all links via setting tighter constraint and solving a binary integer programming problem. Simulation results show that solutions obtained by this algorithm are very close to the upper bounds obtained via relaxation, thus suggesting that the solution produced by the algorithm is near-optimal. Thirdly, we study the topology control of disaster area wireless networks to facilitate mobile nodes communications by deploying a minimum number of relay nodes dynamically. We first put forward a novel mobility model for mobile nodes that describes the movement of first responders within a large disaster area. Secondly, we formulate the square disk cover problem and propose three algorithms to solve it, including the two-vertex square covering algorithm, the circle covering algorithm and the binary integer programming algorithm. Fourthly, we explore the joint problem of power control and channel assignment to maximize cognitive radio network throughput. It is assumed that an overlaid cognitive radio network (CRN) co-exists with a primary network. We model the opportunistic spectrum access for cognitive radio network and formulate the cross-layer optimization problem under the interference constraints imposed by the existing primary network. A distributed greedy algorithm is proposed to seek for larger network throughput. Cross-layer optimization for CRN is often implemented in centralized manner to avoid co-channel interference. The distributed algorithm coordinates the channel assignment with local channel usage information. Thus the computation complexity is greatly reduced. Finally, we study the network throughput optimization problem for a multi-hop wireless network by considering interference alignment at physical layer. We first transform the problem of dividing a set of links into multiple maximal concurrent link sets to the problem of finding the maximal cliques of a graph. Then each concurrent link set is further divided into one or several interference channel networks, on which interference alignment is implemented to guarantee simultaneous transmission. The network throughput optimization problem is then formulated as a non-convex nonlinear programming problem, which is NP-hard generally. Thus we resort to developing a branch-and-bound framework, which guarantees an achievable performance bound

A survey of self organisation in future cellular networks

This article surveys the literature over the period of the last decade on the emerging field of self organisation as applied to wireless cellular communication networks. Self organisation has been extensively studied and applied in adhoc networks, wireless sensor networks and autonomic computer networks; however in the context of wireless cellular networks, this is the first attempt to put in perspective the various efforts in form of a tutorial/survey. We provide a comprehensive survey of the existing literature, projects and standards in self organising cellular networks. Additionally, we also aim to present a clear understanding of this active research area, identifying a clear taxonomy and guidelines for design of self organising mechanisms. We compare strength and weakness of existing solutions and highlight the key research areas for further development. This paper serves as a guide and a starting point for anyone willing to delve into research on self organisation in wireless cellular communication networks

Cognitive Radio Network with a distributed control channel and quality-of-service solution

The proliferation of wireless access and applications to the Internet and the advent of a myriad of highly evolved portable communication devices; creates the need for an efficiently utilized radio spectrum. This is paramount in the licensed and unlicensed radio frequency bands, that spawn an exponential growth in Dynamic Spectrum Access (DSA) research, Cognitive Radio (CR) and Cognitive Radio Networks (CRN) research. DSA research has given way to the paradigm shift toward CR with its dynamic changes in transmission schemas. This paradigm shift from a fixed and centralized frequency spectrum environment has morphed into a dynamic and decentralized one. CR provides wireless nodes the capability to adapt and exploit the frequency spectrum. The spectrum information obtained is scanned and updated to determine the channel quality for viability and a utilization/availability by the licensed (primary) user. To take advantage of the CR capabilities, previous research has focused on a Common Control Channel(CCC) for the control signals to be used for spectrum control. This utilization generates channel saturation, extreme transmission overhead of control information, and a point of vulnerability. The traditional designs for wireless routing protocols do not support an ad hoc multi-hop cognitive radio network model. This research focuses on a real world implementation of a heterogeneous ad hoc multi-hop Cognitive Radio Network. An overall model, coined Emerald, has been designed to address the architecture; the Medium Access Control layer, E-MAC; and the network layer, E-NET. First, a Medium Access Control(MAC) layer protocol is provided to avoid the pitfalls of a common control channel. This new design provides CRNs with network topology and channel utilization information. Spectrum etiquette, in turn, addresses channel saturation, control overhead, and the single point of vulnerability. Secondly, a routing model is proposed that will address the efficiency of an ad hoc multi-hop CRN with a focus on the Quality-of-Service(QoS) of the point-to-point as well as end-to-end communication. This research has documented weaknesses in spectrum utilization; it has been expanded to accommodate a distributed control environment. Subsets of the model will be validated through Network Simulator-2(NS/2) and MatLab© simulations to determine point-to-point and end-to-end communications

A Hybrid Simulation Methodology To Evaluate Network Centricdecision Making Under Extreme Events

Currently the network centric operation and network centric warfare have generated a new area of research focused on determining how hierarchical organizations composed by human beings and machines make decisions over collaborative environments. One of the most stressful scenarios for these kinds of organizations is the so-called extreme events. This dissertation provides a hybrid simulation methodology based on classical simulation paradigms combined with social network analysis for evaluating and improving the organizational structures and procedures, mainly the incident command systems and plans for facing those extreme events. According to this, we provide a methodology for generating hypotheses and afterwards testing organizational procedures either in real training systems or simulation models with validated data. As long as the organization changes their dyadic relationships dynamically over time, we propose to capture the longitudinal digraph in time and analyze it by means of its adjacency matrix. Thus, by using an object oriented approach, three domains are proposed for better understanding the performance and the surrounding environment of an emergency management organization. System dynamics is used for modeling the critical infrastructure linked to the warning alerts of a given organization at federal, state and local levels. Discrete simulations based on the defined concept of community of state enables us to control the complete model. Discrete event simulation allows us to create entities that represent the data and resource flows within the organization. We propose that cognitive models might well be suited in our methodology. For instance, we show how the team performance decays in time, according to the Yerkes-Dodson curve, affecting the measures of performance of the whole organizational system. Accordingly we suggest that the hybrid model could be applied to other types of organizations, such as military peacekeeping operations and joint task forces. Along with providing insight about organizations, the methodology supports the analysis of the after action review (AAR), based on collection of data obtained from the command and control systems or the so-called training scenarios. Furthermore, a rich set of mathematical measures arises from the hybrid models such as triad census, dyad census, eigenvalues, utilization, feedback loops, etc., which provides a strong foundation for studying an emergency management organization. Future research will be necessary for analyzing real data and validating the proposed methodology

The Coverage, Capacity and Coexistence of Mixed High Altitude Platform and Terrestrial Segments

This thesis explores the coverage, capacity and coexistence of High Altitude Platform (HAP) and terrestrial segments in the same service area. Given the limited spectrum available, mechanisms to manage the co-channel interference to enable effective coexistence between the two infrastructures are examined. Interference arising from the HAP, caused by the relatively high transmit power and the antenna beam profile, has the potential to significantly affect the existing terrestrial system on the ground if the HAP beams are deployed without a proper strategy. Beam-pointing strategies exploiting phased array antennas on the HAPs are shown to be an effective way to place the beams, with each of them forming service cells onto the ground in the service area, especially dense user areas. Using a newly developed RF clustering technique to better point the cells over an area of a dense group of users, it is shown that near maximum coverage of 96% of the population over the service area can be provided while maintaining the coexistence with the existing terrestrial system. To improve the user experience at the cell edge, while at the same time improving the overall capacity of the system, Joint Transmission – Coordinated Multipoint (JT-CoMP) is adapted for a HAP architecture. It is shown how the HAP can potentially enable the tight scheduling needed to perform JT-CoMP due to the centralisation of all virtual E-UTRAN Node Bs (eNodeBs) on the HAP. A trade-off between CINR gain and loss of capacity when adapting JT-CoMP into the HAP system is identified, and strategies to minimise the trade-off are considered. It is shown that 57% of the users benefit from the JT-CoMP. In order to enable coordination between the HAP and terrestrial segments, a joint architecture based on a Cloud – Radio Access Network (C-RAN) system is introduced. Apart from adapting a C-RAN based system to centrally connect the two segments together, the network functional split which varies the degree of the centralised processing is also considered to deal with the limitations of HAP fronthaul link requirements. Based on the fronthaul link requirements acquired from the different splitting options, the ground relay station diversity to connect the HAP to centralised and distributed units (CUs and DUs) is also considered

Facilitating Internet of Things on the Edge

The evolution of electronics and wireless technologies has entered a new era, the Internet of Things (IoT). Presently, IoT technologies influence the global market, bringing benefits in many areas, including healthcare, manufacturing, transportation, and entertainment. Modern IoT devices serve as a thin client with data processing performed in a remote computing node, such as a cloud server or a mobile edge compute unit. These computing units own significant resources that allow prompt data processing. The user experience for such an approach relies drastically on the availability and quality of the internet connection. In this case, if the internet connection is unavailable, the resulting operations of IoT applications can be completely disrupted. It is worth noting that emerging IoT applications are even more throughput demanding and latency-sensitive which makes communication networks a practical bottleneck for the service provisioning. This thesis aims to eliminate the limitations of wireless access, via the improvement of connectivity and throughput between the devices on the edge, as well as their network identification, which is fundamentally important for IoT service management. The introduction begins with a discussion on the emerging IoT applications and their demands. Subsequent chapters introduce scenarios of interest, describe the proposed solutions and provide selected performance evaluation results. Specifically, we start with research on the use of degraded memory chips for network identification of IoT devices as an alternative to conventional methods, such as IMEI; these methods are not vulnerable to tampering and cloning. Further, we introduce our contributions for improving connectivity and throughput among IoT devices on the edge in a case where the mobile network infrastructure is limited or totally unavailable. Finally, we conclude the introduction with a summary of the results achieved