On Capacity Region And Power Allocation Of Multi-user Cognitive Channels

As the fast development of the wireless communication technology, the number of wireless systems and services is growing rapidly, the radio spectrum has become a very pre-cious and scarce resource. Cognitive radio, as a new wireless communication technology to improve the radio spectrum utilization, has been attracted extensive attentions from aca-demic and industrial communities. There are a lot of achievements about the cognitive radio technology, however, the cognitive radio cannot be applied to the actual application. To make the cognitive radio be a real wireless communication technology to improve the radio spectrum utilization, the supports from not only the technical innovation but also study on network information theory are indeed needed.This thesis studies the performances of cognitive radio network from information theo-retic perspective. The capacity region of the multi-user channels in cognitive radio networks and the power allocation in the Gaussian multi-user channels are investigated. The contents of this thesis are listed as follows.The power allocation in Gaussian multi-user channel is studied. For the Gaussian broadcast channel, the power allocation is studied to maximize the system throughput with the different weight allocated to each user. For the power allocation, we construct a mathe-matical model of the weighted rate sum maximization. By analyzing the objective function, we derive the closed-form optimal solution based on the special property of the objective function. For the power allocation in Gaussian multiple access channel, we construct a mathematical model of weighted rate sum maximization under the constraint of power sum. Based on the duality of between Gaussian multiple access channel and Gaussian broadcast channel, we transform the weighted rate sum maximization under the constraint of power sum into the weighted rate sum maximization in Gaussian broadcast channel, and derive the closed-form optimal solution. The computational complexity of the derived closed-form optimal solutions is low. Thus, it is suitable for the dynamic power allocation in real com-munication system.The capacity region of Gaussian cognitive broadcast channel is studied. We give the mathematical models of cognitive broadcast channel and define the capacity region of cog-nitive multiple access channel. We derive the capacity region of the Gaussian cognitive broadcast channel in the low-interference-gain regime. To ensure cognitive radio creates no rate degradation for the primary user, we study the capacity region of the Gaussian cognitive broadcast channel under the constraint of coexistence conditions, and derive the capacity re-gion of the Gaussian cognitive broadcast channel in the low-interference-gain regime under the constraint of coexistence conditions. For the power allocation in Gaussian cognitive broadcast channel under the constraint of coexistence conditions, we construct a mathemat-ical model of weighted rate sum maximization in Gaussian cognitive broadcast channel and derive the closed-form optimal solution.The capacity region of Gaussian cognitive multiple access channel is studied. We give the mathematical models of cognitive multiple access channel and define the capacity region of cognitive multiple access channel. For a special Gaussian cognitive multiple access channel—Gaussian cognitive multiple access channel in the symmetric low-interference-gain regime, we derive the capacity region. To ensure cognitive radio creates no rate degradation for the primary user, we study the capacity region of the Gaussian cognitive multiple access channel under the constraint of coexistence conditions, and derive the capacity region of the Gaussian cognitive multiple access channel in the symmetric low-interference-gain regime under the constraint of coexistence conditions.