Investigation On Hybrid Networks Based On Cognitive Radio Technologies

Now the explosive increase of wireless data traffic brings higher and higher requirement on capacity of radio communication network. On the one hand, the available radio spectrum resource for future licensing allocation is getting scarce. On the other hand, the investigation shows that the utilization ratio of some spectrum resources is quite low. The spectrum utilization ratio should be improved without harmful effect on current wireless systems and applications. This will greatly help to solve the bottleneck problem of spectrum scarcity.Cognitive radio enables the wireless equipments to sense the radio environment for the side information such as spectrum usage and channel condition, which will be utilized for flexible spectrum usage. Danamic spectrum access based on cognitive radio technologies helps multiple wireless systems to share and reuse radio spectrum resources, thus improves the total spectrum efficiency.Multiple wireless communication systems, which share radio spectrum based on cogtive radio technologies, compose a hybrid radio network. The dissertation focuses on hybrid network including a cognitive radio system and a conventional wireless communication system. Wherein, the architecture of the congnitive radio system herein could be infrastructural network or Ad hoc network, which will impact the framework design of the hybrid network and the radio resource management inside, including interference avoidance and control scheme.In this dissertation, Chapter 1 introduces the evolution and current status of cognitive radio technologies. In Chapter 2, the radio resource allocation algorithms are studied for infrastructure-based cognitive radio system in hybrid network. Chapter 3 focuses on the design of the framework solution and the interference avoidance and control scheme in hybrid cellular and device-to-device network. And the radio resource allocation algorithms for cognitive device-to-device communication are investigated in Chapter 4 based on the aforementioned framework. The main contribution of the dissertation is presented as follows:1. Under the interference temperature constraints, a iterative-adjustment-based radio resource allocation method is proposed for the OFDMA-based infrastructural cognitive radio system in a hybrid network. Two algorithms of resource adjustment are studied. One of them estimates the throughput difference caused by subcarrier adjustment with the consideration of the interference constraint and the equivalent noise floor. It approaches the performance of optimal resource allocation with relative high computation complexity. In the other algorithm, the throughput difference caused by subcarrier adjustment is coarsely estimated. And it can achieve good performance with lower computation burden.2. A framework solution for spectrum sharing and reuse is proposed for hybrid cellular and device-to-device network. Wherein, the two sub-systems in the hybrid network adopt the same basic transmission technologies in physical layer with synchronized frame structure. The purpose of the framework solution is to facilitate a novel basestation-assisted distributed radio resource management for device-to-device communication. The interference between celluar and device-to-device communication is addressed considering uplink/downlink resource sharing and reuse. And interference avoidance and control schemes are proposed to solve the above interference problems.3. The base-station-assisted distributed radio resource allocation algorithms are studied for device-to-device communication in hybrid cellular and device-to-device network. Considering the fast scheduling in cellular system, a distributed power control scheme is proposed based on cellular scheduling information and base-station assistance information. The algorithm is robust in time-variant interference environment caused by cellular fast scheduling and fluctuant channel condition. The substantial solution of the algorithm is designed for real application based on current cellular systems.