Adaptive Spatial Resource Management For Cognitive MIMO-OFDM System

To relieve the short of the wireless resource due to the increasing demand of available resource, highly frequency utilized communicaiton technique has attracted more and more researchers'attention. Cognitive Radio(CR) has become the research trend for the future wireless communication, and what's more, the physical relization of CR and resource management are the core of CR research.This paper takes spaitial resource management of Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing(MIMO-OFDM) under the CR circumstances as research object, and propose a new spatial resource management scheme. This scheme emphasizes to maximize the throughput of cognitive user through arranging available spatial antenna while ensuring the communication quality of the primary user. Aiming at the spatial resource management, this paper carries out the following research work.As the fundamental part, this paper firstly introduces the basic principle of CR and frequency sensing model of CR. Secondly, the principle diagram and the mathematical model of MIMO, OFDM, MIMO-OFDM are introduced. Finally, the channel model of MIMO-OFDM is introduced.As the essential part, under the circumstances of sharing the same frequency band between CU an PU, this paper proposes an adaptive spatial resource management using Gerschgorin Circle antenna selection-MIMO streaming control algorithm and an improved MMSE-SIC algorithm in order to efficiently manage spatial resource, which is to increase the throughput of CU.(1) Antenna selection based on the Gerschgorin CircleTo realize the spatial mangement, antenna selection based on the Gerschgorin Circle is proposed. Gerschgorin Circle algorithm provides lower bit error ratio and higher system capacity than the original one.(2) An Improved Minimum Mean Squre Error/Serial Interference Cancellation (MMSE-SIC) algorithmTo cooperate with the antenna selection method, the improved MMSE-SIC algorithm is proposed but with reverse order, the improved MMSE-SIC algorithm shows better cancellation remove effect and decreases bit error of cognitive user..(3) New spatial resource managementCombine both the Gerschgorin Circle algorithm and the improved MMSE-SIC, the scheme of spatial management using the adapitve antenna selection and interference canellation is formed. By using this new spatial data stream management, the outage of communication is reduced and the throughput of CU can be efficiently improved.As the result analysis, this paper firstly compares system throughput under conventional method and the proposed method of spatial management; Secondly, CU throughput under different two kinds of spectrum sensing is analyzed. The results show that the spatial management scheme shows an improved system throughput compared with the conventional cognitive resource management.