Radio network management in cognitive LTE-Femtocell Systems

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.There is a strong uptake of femtocell deployment as small cell application platforms in the upcoming LTE networks. In such two-tier networks of LTEfemtocell base stations, a large portion of the assigned spectrum is used sporadically leading to underutilisation of valuable frequency resources. Novel spectrum access techniques are necessary to solve these current spectrum inefficiency problems. Therefore, spectrum management solutions should have the features to improve spectrum access in both temporal and spatial manner. Cognitive Radio (CR) with the Dynamic Spectrum Access (DSA) is considered to be the key technology in this research in order to increase the spectrum efficiency. This is an effective solution to allow a group of Secondary Users (SUs) to share the radio spectrum initially allocated to the Primary User (PUs) at no interference. The core aim of this thesis is to develop new cognitive LTE-femtocell systems that offer a 4G vision, to facilitate the radio network management in order to increase the network capacity and further improve spectrum access probabilities. In this thesis, a new spectrum management model for cognitive radio networks is considered to enable a seamless integration of multi-access technology with existing networks. This involves the design of efficient resource allocation algorithms that are able to respond to the rapid changes in the dynamic wireless environment and primary users activities. Throughout this thesis a variety of network upgraded functions are developed using application simulation scenarios. Therefore, the proposed algorithms, mechanisms, methods, and system models are not restricted in the considered networks, but rather have a wider applicability to be used in other technologies. This thesis mainly investigates three aspects of research issues relating to the efficient management of cognitive networks: First, novel spectrum resource management modules are proposed to maximise the spectrum access by rapidly detecting the available transmission opportunities. Secondly, a developed pilot power controlling algorithm is introduced to minimise the power consumption by considering mobile position and application requirements. Also, there is investigation on the impact of deploying different numbers of femtocell base stations in LTE domain to identify the optimum cell size for future networks. Finally, a novel call admission control mechanism for mobility management is proposed to support seamless handover between LTE and femtocell domains. This is performed by assigning high speed mobile users to the LTE system to avoid unnecessary handovers. The proposed solutions were examined by simulation and numerical analysis to show the strength of cognitive femtocell deployment for the required applications. The results show that the new system design based on cognitive radio configuration enable an efficient resource management in terms of spectrum allocation, adaptive pilot power control, and mobile handover. The proposed framework and algorithms offer a novel spectrum management for self organised LTE-femtocell architecture. Eventually, this research shows that certain architectures fulfilling spectrum management requirements are implementable in practice and display good performance in dynamic wireless environments which recommends the consideration of CR systems in LTE and femtocell networks

Unified radio and network control across heterogeneous hardware platforms

Experimentation is an important step in the investigation of techniques for handling spectrum scarcity or the development of new waveforms in future wireless networks. However, it is impractical and not cost effective to construct custom platforms for each future network scenario to be investigated. This problem is addressed by defining Unified Programming Interfaces that allow common access to several platforms for experimentation-based prototyping, research, and development purposes. The design of these interfaces is driven by a diverse set of scenarios that capture the functionality relevant to future network implementations while trying to keep them as generic as possible. Herein, the definition of this set of scenarios is presented as well as the architecture for supporting experimentation-based wireless research over multiple hardware platforms. The proposed architecture for experimentation incorporates both local and global unified interfaces to control any aspect of a wireless system while being completely agnostic to the actual technology incorporated. Control is feasible from the low-level features of individual radios to the entire network stack, including hierarchical control combinations. A testbed to enable the use of the above architecture is utilized that uses a backbone network in order to be able to extract measurements and observe the overall behaviour of the system under test without imposing further communication overhead to the actual experiment. Based on the aforementioned architecture, a system is proposed that is able to support the advancement of intelligent techniques for future networks through experimentation while decoupling promising algorithms and techniques from the capabilities of a specific hardware platform

FPGA based technical solutions for high throughput data processing and encryption for 5G communication: A review

The field programmable gate array (FPGA) devices are ideal solutions for high-speed processing applications, given their flexibility, parallel processing capability, and power efficiency. In this review paper, at first, an overview of the key applications of FPGA-based platforms in 5G networks/systems is presented, exploiting the improved performances offered by such devices. FPGA-based implementations of cloud radio access network (C-RAN) accelerators, network function virtualization (NFV)-based network slicers, cognitive radio systems, and multiple input multiple output (MIMO) channel characterizers are the main considered applications that can benefit from the high processing rate, power efficiency and flexibility of FPGAs. Furthermore, the implementations of encryption/decryption algorithms by employing the Xilinx Zynq Ultrascale+MPSoC ZCU102 FPGA platform are discussed, and then we introduce our high-speed and lightweight implementation of the well-known AES-128 algorithm, developed on the same FPGA platform, and comparing it with similar solutions already published in the literature. The comparison results indicate that our AES-128 implementation enables efficient hardware usage for a given data-rate (up to 28.16 Gbit/s), resulting in higher efficiency (8.64 Mbps/slice) than other considered solutions. Finally, the applications of the ZCU102 platform for high-speed processing are explored, such as image and signal processing, visual recognition, and hardware resource management