Non-Orthogonal Multiple Access for Hybrid VLC-RF Networks with Imperfect Channel State Information

The present contribution proposes a general framework for the energy efficiency analysis of a hybrid visible light communication (VLC) and Radio Frequency (RF) wireless system, in which both VLC and RF subsystems utilize nonorthogonal multiple access (NOMA) technology. The proposed framework is based on realistic communication scenarios as it takes into account the mobility of users, and assumes imperfect channel-state information (CSI). In this context, tractable closed-form expressions are derived for the corresponding average sum rate of NOMA-VLC and its orthogonal frequency division multiple access (OFDMA)-VLC counterparts. It is shown extensively that incurred CSI errors have a considerable impact on the average energy efficiency of both NOMA-VLC and OFDMAVLC systems and hence, they should not be neglected in practical designs and deployments. Interestingly, we further demonstrate that the average energy efficiency of the hybrid NOMA-VLCRF system outperforms NOMA-VLC system under imperfect CSI. Respective computer simulations corroborate the derived analytic results and interesting theoretical and practical insights are provided, which will be useful in the effective design and deployment of conventional VLC and hybrid VLC-RF systems

Energy Efficient Network Function Virtualisation in 5G Networks

Once the dust settled around 4G, 5G mobile networks become the buzz word in the world of communication systems. The recent surge of bandwidth-greedy applications and the proliferation of smart phones and other wireless connected devices has led to an enormous increase in mobile traffic. Therefore, 5G networks have to deal with a huge number of connected devices of different types and applications, including devices running life-critical applications, and facilitate access to mobile resources easily. Therefore given the increase in traffic and number of connected devices, intelligent and energy efficient architectures are needed to adequately and sustainably meet these requirements. In this thesis network function virtualisation is investigated as a promising paradigm that can contribute to energy consumption reduction in 5G networks. The work carried out in this thesis considers the energy efficiency mainly in terms of processing power consumption and network power consumption. Furthermore, it considers the energy consumption reduction that can be achieved by optimising the locations of virtual machines running the mobile 5G network functions. It also evaluates the consolidation and pooling of the mobile resources. A framework was introduced to virtualise the mobile core network functions and baseband processing functions. Mixed integer linear programming optimisation models and heuristics were developed minimise the total power consumption. The impact of virtualisation in the 5G front haul and back haul passive optical network was investigated by developing MILP models to optimise the location of virtual machines. A further consideration is caching the contents close to the user and its impact on the total power consumption. The impact of a number of factor on the power consumption were investigated such as the total number of active users, the backhaul to the fronthaul traffic ratio, reduction/expansion in the traffic due to baseband processing, and the communication between virtual machines. Finally, the integration of network function virtualisation and content caching were introduced and their impact on improving the energy efficiency was investigated

Energy Efficient Resource and Topology Management for Heterogeneous Cellular Networks

This thesis investigates how resource and topology management techniques can be applied to achieve energy efficiency while maintaining acceptable quality of service (QoS) in heterogeneous cellular networks comprising high power macrocells and dense deployment of low power small cells. Partially centralised resource and topology management algorithms involving the sharing of decision making responsibilities regarding resource utilization and activation or deactivation of small cells among macrocells, small cells and a central node are developed. Resource management techniques are proposed to enable mobile users to be served by resources of a few small cells. A topology management scheme is applied to switch off idle small cells and switch on sleeping cells in accordance with traffic load and QoS. Resource management techniques, when combined with the topology management technique, achieve significant energy efficiency. A choice restriction technique that restricts users to resources from only a subset of suitable small cells is proposed to mitigate interference and improve QoS. A good balance between energy efficiency and QoS is achieved through this approach. Furthermore, energy saving under different generations of small cell base stations is investigated to provide insights to guide the design of energy saving strategies and the enhancement of existing ones. Also, an online, adaptive energy efficient joint resource and topology management technique is developed to correct deteriorating QoS conditions automatically by using a novel confidence level strategy to estimate QoS and regulate decision making epochs at the central node. Finally, a novel linear search scheme is applied together with database records of performance metrics to select appropriate resource and topology management policies for different traffic loads. This approach achieves better balance between QoS and energy efficiency than previous schemes proposed in the literature