Dynamic Resource Optimization In Cognitive Radio Networks

As the improvement of people's life, the requirements of wireless communication service are changed from the voice communication to the multi-media data communi-cation. So more and more spectrum resource are needed to support the service require-ments. But the ongoing spectrum management policies are based on fixed allocation and licensed usage. The spectrum allocation is managed by the radio management committee of the government in each country. For example, the spectrum band be-tween 3kHz and 300GHz has been licensed to the different service applications, and the available idle bands barely remain. Meanwhile, based on the report of Federal Communication Committee (FCC), the spectrum utility varies in different time and geographic location. Most of the spectrum has a very low utility. In order to solve the problem of the spectrum scarcity and the low spectrum utility, " Cognitive Radio (CR)" has attracted attention as the research topic for its properties, such as sensitive spectrum sensing and intelligent spectrum access.In this thesis, we mainly studied the wireless resource allocation problem in the cognitive radio networks. Based on the different network structures, using different spectrum sharing models, we studied the power control, carrier allocation and times-lot scheduling problem in cognitive cellular networks, cognitive multi-carrier networks and cognitive sensor networks, respectively. Through the mathematic formulation, we formulate the research problem into the convex optimization problem. So the problem can be solved using convex optimization theory and dual decomposition theory and obtain the optimal resource allocation algorithm. Main contributions of the thesis are as follows:1. We studied the multi-user power control problem in the cognitive cellular networks. The cognitive user networks apply the centralized cellular network structure. The cognitive users share the licensed spectrum with the primary user using the Un-derlay spectrum sharing model and access the cognitive user networks in Code Division Multiple Access (CDMA). The research objective is to maximize the total capacity of the cognitive users, satisfying the constraint of the interference power to the primary user. Due to that the proposed problem formulation is a nonlin-ear and nonconvex problem which couldn't guarantee obtaining the global optimal solution, we introduce the Geometric Programming (GP) theory to transform the nonlinear and nonconvex problem into nonlinear and convex problem. As the vari-ables in the utility functions between the cognitive users arc coupled with each other which couldn't lead to a distributed solution, we introduce the couple dc-composition method and dual decomposition theory to separate the optimization problem for the system into optimization sub-problem for the cognitive users and obtain the final global optimal solutions.2. We studied the carrier and power allocation for cognitive users in cognitive multi-carrier networks. Based on the characteristic of Overlay and Underlay spectrum sharing model, we proposed a Hybrid Opportunistic Spectrum Access (H-OSA) Algorithm. In this algorithm, the cognitive user could access not only the idle channels but also the channels occupied by the primary user, guaranteeing the in-terfcrence constraints for primary user. So it could both utilize the spectrum holes more efficiently and take advantage of the primary user's tolerance threshold. This could improve the spectrum utility effectively. We first analysed the H-OSA algo-rithm in the singlc-cognitivc-user system. We obtain the optimal power solution in each carrier through the dual decomposition theory which separate the pro-posed problem into several sub-problem. Then, we studied the H-OSA algorithm in the cognitive multi-carrier networks, considering downlink and uplink scenar-ios, respectively. We deduced the optimal carrier and power allocation strategies for both scenarios. At last, considering that the information of the interference channel to primary user is imperfect channel state information, we analysed the performance of the H-OSA algorithm.3. We studied the timeslot scheduling and power control based on energy efficiency in cognitive sensor networks. The cognitive user networks apply the Ad Hoc net- work structure. The primary users and cognitive users exist in pairs. The research objective is to minimize the transmission power of cognitive user, guaranteeing the Quality of Service (QoS) of the primary user and cognitive user. Using the "spectrum leasing" model, the primary users first achieve their minimal required transmission rates, and then, lease the residual transmission timeslots to the cogni-tive users. The cognitive users access the transmission timeslots in Time Division Multiple Access (TDMA) model. Through the cooperative transmission by relay nodes, the cognitive sensors could take advantage of the transmission path which has a better channel state to improve the channel capacity. So it could effectively save the transmission power and satisfying the minimal required transmission rates of cognitive users.