Research On Energy Efficient Resource Management With Control And Date Plane Separation In Heterogeneous Wireless Networks

With the exponential growth of traffic in wireless networks, the heterogeneous deployment of macro cells and small cells has become the main approach to increase the network capacity and achieve high throughput transmission. However, as a result,the interference in the dense and heterogeneous wireless network also comes complicated, which raises the challenge to the efficient schedule and flexible control of the network, as well as huge amount of energy consumption coming up with the traffic growth. In addition, new types of the massive connection, sudden and low-rate internet-of-things traffic has brought a tremendous burden of network signal exchange and traffic schedule. In order to face these difficulties, the software defined network with control and data plane separation is now emerging as a promising paradigm of next generation of the network to achieve high energy-efficiency and on-demand scheduling in wireless networks. The dissertation proposes solutions to the study of heterogenous wireless network performance with control and data plane split and deeply investigates the collaboration network between satellite and ground, and the high-efficiency cache management schemes, by utilizing the control and data plane features. The main contributions and innovations of this dissertation are summarized as follows.1. Research on energy-efficiency characteristics of the software-defined heterogeneous networkThe base station distribution is studied based on the practical data collected in the real network and the base stations spatial distribution model is built in urban, suburban and dense urban respectively, along with the typical parametres, which paves a foundation of base station model for the whole dissertation. From the perspective of network evolution, a data-only carrier (DoC) system is proposed as one of the typical control and data split network, and the public signalling overhead and backhaul exchange cost are evaluated in this software-defined networks. The relationship between the performance of various configurations of the network, including the same or different frequency of small cells and macro cells, and network parameters, e.g.,small cell transmission power and density, is given theoretically. It is shown that under the constraint of network load, the control and data plane split network can achieve much higher network energy efficiency and coverage probability, compared with traditional networks. This conclusion comes consistently with the results by system level simulation platform. As one of the typical scenario, the ultra-dense deployment of small cells in heterogeneous control and data split network, the mobility parametres are optimized in advance, to decrease the handover failure rate by more than 80%, while increasing the network efficiency.2. Research on the energy-efficient heterogeneous collaboration network between satellite and groundTaking advantage of the wide area coverage of satellite, the collaboration network between satellite and ground becomes a new approach to realize control and data plane split to a large scale. A novel control and data plane separated network is proposed with the collaboration between satellite and ground, which breakthroughs traditional wireless resource management and scheduling strategy. For the small cell sparse and dense deployed scenarios, the network coverage probability, throughput and network energy efficiency are studied theoretically under various transmission power and deployment density. With the wide coverage and the information cognition of the whole network, the proposed resource management schemes, bandwidth allocation schemes and on-off approaches in the collaborated satellite and ground network are verified to improve the network throughput and end-to-end energy efficiency effectively. It is shown that with the cost of 3% of spectral efficiency, the network energy efficiency can achieve approximately 90% growth instead, and the network coverage and spectral efficiency can be improved by making full use of the bandwidth resource of the satellite in the sparse network. In the dense network, the probability of sleeping for small cells can be greatly increased under the flexible schedule of satellite, so that the network can achieve higher energy efficiency while maintaining coverage.3. Research on energy-efficient cache management techniques in heterogeneous wireless networksConsidering the communication, storage and computing resources in heterogeneous wireless networks, the cache management techniques are studied based on the model of the network, user and traffic pattern in the control and data split networks. We propose energy efficient cache deployment scheme, user association scheme and energy-efficient joint optimization method which combines cache and access strategy in the network to improve the performance of the network, under the constraint of given access scheme, cache deployment scheme, and network behavior respectively. Traditional cache management techniques ignore the constraint of backhaul capacity and the study of energy consumption, and the relationship between traffic is a lack of utilization. We proposed the techniques including novel cache deployment method, user-centric access strategy, and the definition of base station social-tie factor, which is used to dig out the representative base stations as Very Important Base-station (VIBS) to reflect the traffic characteristics in a certain region.Under the target storage and backhaul capacity constraint, the performance of the heterogeneous network under various cache management techniques are derived theoretically, and the relationship between network coverage,throughput and energy efficiency, and the key parametres are given. It is verified that there exists three typical fundamental tradeoffs in the cache-enabled network with control and data plane split:the tradeoff between network energy efficiency and density of small cells, the tradeoff between network efficiency and storage capacity of small cells, as well as the tradeoff between network efficiency and transmission power of small cells. It is shown that the proposed techniques can obviously increase the probability of hitting the cache in local storage in access networks for users, and the network capacity and energy efficiency achieve higher gain compared with traditional cache management schemes.