Research On Key Techniques In Cognitive MIMO Wireless Networks

As a non-regenerative resource, the scarce characteristics of wireless spectrum become serious gradually with the rapid growth of wireless applications in recent years. CR technology has been recently proposed as a smart and agile technology which aims at guaranteeing the coexistence of primary licensed users and cognitive non-legitimate users in the same spectral resource opportunistically. However, just as everything growing up with its two sides, the dynamics spectrum access technique is no exception, which has made the traditional spectrum access algorithms involved in a new challenge. MIMO techniques (Multiple Input Multiple Output) is one of several forms of smart antenna technology which uses multiple antennas at both the transmitter and receiver to offer significant increases in data throughput and link range without additional bandwidth or transmitted power. With the aims at extending the coverage, increasing connectivity and capacity, we try to study MIMO technology in cognitive radio network. This dissertation aims to study the system performance, e.g. maximal stable throughput, sum rate, transmit power, as well as cost-effective algorithms that are suitable for implementations in practical systems.Based on a priority queuing framework model, we analyze the maximal stable throughput and the corresponding power control optimization problem in the non-cooperative cognition network with a single user. And a kind of individual cognitive user’s selection algorithm is proposed which can assure the near orthogonalization between the primary user and the cognitive user, meanwhile ensuring the cognitive user with the maximum channel gain. Based on Loynes’ stability criteria, we directly exact the formula of stable throughput for the cognitive link in the structure that cognitive link using two transmitting antennas as primary link in the ideal scenario. Through the multi-dimensional search algorithm, we draw the corresponding optimal power allocation methods; In the real scenario, with the assumption that the possibility of detection error or leak will occur due to misty and indetermination of wireless channels, we exact stability of an equivalent dominant system to case of interaction queues with a fixed packet arriving rate selected by the primary link. By greedy algorithm, we get the corresponding power control method for per single antenna. The upper conclusions are then extended to the case in which both primary and cognitive links using multiple transmission antennas.After modeling a non-cooperative centralized access control cognitive MISO (Multiple Input Single Output) system with multiple users, one detection strategy with cooperation is proposed, in which, the central node control more than one cognitive users to of jointly detect the primary channel. And we derive the cognitive link’s maximal stable throughput with the corresponding power control for each transmission antenna. A cognitive MU-MIMO (Multi-User Multiple Input Multiple Output) network is modeled. Based on subspace theory, we learn a scheme how to choose a group of cognitive users in a cognitive MU-MIMO network and try to use the BD method to white co-channel interference between the cognitive users order to maximize cognitive base station’s sum-rate.Two precoding algorithms used in the downlink of non-cooperative cognitive MU-MIMO system are studied. Firstly we propose one CR-TR-BD to pre-white the interference from the cognitive users to the primary user and solve the question of how to maximize sum rate while considering the transmit powers constrain at cognitive base station. CR-TR-BD algorithm can be used within slight tightness degree of the antenna number constraint in cognitive network and performs close to or even better than BD in general MU-MIMO system with same number of transmitting antennas. Then we a double-updated algorithm to solve the transmitting power optimization problem with constrains of SINR for cognitive users and interference constrain from cognitive users to the primary one. Various performance evaluation results show the proposed algorithm can converge to the SOCP results quickly and performance better than others.