Research On Data Compression In C-RAN System And Cooperative Cognitive Resource Allocation Algorithin

Due to the development of wireless communication restricted by conventional cellular network, Cloud-Radio Access Network (C-RAN), adopting centralized data processing, collaborative resource allocation and real-time cloud computing device, is a perfect option for next generation wireless communication network. Meanwhile, C-RAN can meet the demands of multiservice and energy-efficient in the future communication.On one hand, considering the application of large-scale Multiple-Input Multiple-Output (MIMO), the substantial increase of the link burden between baseband unit (BBU) and remote radio unit (RRU) will exceed the capacity of existing standards. Therefore, it is meaningful to compress the link data through efficient preprocessing algorithm. On the other hand, the resource allocation of C-RAN is mainly researched in licensed spectrum, while cognitive radio (CR) technology has the ability of improving the utilization of spectrum. Thus, this thesis researched on the data compression and cooperative resource allocation in C-RAN. The main works can be summarized as follows:(1)After analyzing the link overloading in C-RAN, this thesis proposed an efficient compression algorithm which was based on minimum mean square error (MMSE) equalization algorithm and used channel information completely. Three specific schemes were proposed by different channel estimation policies, combining with the structure of C-RAN. In order to verify the performance of different compression schemes, we performed link level simulation on uplink of LTE. Simulation results showed the proposed compression schemes in C-RAN can compress the data effectively to meet the rate limitation of interlink with little performance loss.(2) In order to allocate resource more flexibly, this thesis constructed a multi-carriers and multi-users cooperative communication system which adopted CR technology. In the proposed spectrum leasing communication system, secondary users used the spectrum of primary user dynamically by serving as amplify-and-forward (AF) relay. Taking the fairness of secondary users into account, this thesis aimed at maximizing α-utility of the secondary users and optimized the allocation of power, relay and subcarrier-pair, meeting the target rate of primary users and the power limitation of primary user and secondary users. The results showed that compared with the constant power policy and fixed carrier pairing strategy, the proposed algorithm not only considered the fairness of secondary users, but also optimized the secondary system rate.