Cognitive Research On Wireless Resource Allocation In Wireless Networks

In recent years, with the increase of rquirements of mobile users, the fu-ture wireless communication networks face the problem of spectrum scarcity. Although the fixed spectrum allocation and usage avoids the interference be-tween wireless networks, its spectrum efficiency is very low due to the uneven and suddenness of the distribution of users and services, which causes the con-flict between the spectrum scarcity and low spectrum efficienty. The concept of dynamic spectrum allocation and usage is proposed to solve the problem of low spectrum efficiency caused by fixed spectrum allocation. Through dy-namic spectrum allocation and usage, wireless networks can allocate and use spectrum according to service requests, and further solve the problem of spec-trum scarcity with heavy service load and the problem of spectrum waste with light service load. Cognitive wireless network is believed to be one of the key technologies to achieve dynamic spectrum allocation and usage. It can acquire spectrum status information by cognitive methods, then dynamically access and use spectrum as long as the quality of service of primary users on the licensed spectrum is protected. This thesis focuses on the radio resource allocation re-search, which is one of the key technologies in the cognitive wireless network. Radio resource allocation is used to allocate radio resources, e.g., spectrum, power, rate, in the complex wireless channel fading environment, interference and uneven user distribution, in order to efficiently use these radio resources to improve system performance indicators such as spectrum efficiency.Firstly, this thesis investigates the problem of power allocation in cognitive wireless network. For the problem "of power allocation with imperfect channel state information, we propose optimal power allocation algorithms to maximize ergodic capacity and outage capacity, respectively, taken both channel estima-tion errors and feedback delay into consideration. The proposed power alloca- tion algorithms can well protect the primary user transmission due to imperfect channel state information. Closed-form expressions for ergodic capacity and outage capacity are derived, which complete the existing capacity results anal-ysis with imperfect channel state information. Aiming at minimizing bit errir rate of cognitive wireless network, we propose the optimal power allocation algorithms under various transmit power and interference power constraints, which can provide lower bit error rate than that of waterfill power allocation algorithm.Secondly, this thesis investigates the problem of joint power and rate al-location in cognitive wireless network under the delay quality of service con-straint. We propose the optimal joint power and rate allocation algorithms to maximize the effective capacity with the perfect channel state information and imperfect channel state information, respectively. The proposed algorithms can well protect the delay quality of service of secondary users. The expression for the effective capacity with perfect channel state information and maximum ra-tio combining as well as the expression for the effective capacity with imperfect channel state information are also derived.Thirdly, this thesis investigates the problem of joint channel and power allocation in cognitive wireless network. We propose a low complexity and close optimal joint channel and power allocation algorithm with primary user-s’limited cooperation. The performance of the proposed algorithm is great-ly improved compared with that of the non-cooperative algorithm and is very close to that of the optimal cooperative algorithm with much lower complexi-ty. Considering the fact that most of the studies focus on rate fairness between secondary users, we proposed joint channel and power allocation algorithms based on resource fairness constraint. The proposed algorithms can flexibly adjust the fairness between secondary users through regulating the allocated minimum and maximum number of channels constraints.Lastly, this thesis investigates the problem of joint channel, power and rate allocation in cognitive wireless network. Aiming at minimizing the outage probability for cognitive wireless multicast network, we propose joint channel, power and rate allocation algorithms. The proposed algorithms consider two types of outage probabilities, i.e., group outage probability and individual out-age probability. The impacts of various system parameters on the outage prob-abilities for cognitive wireless multicast network are also investigated. For the scenario that there are heterogeneous services, i.e., delay-sensitive and delay-insensitive services, provided by cognitive wireless network, an efficient joint channel, power and rate allocation algorithm is proposed to minimize the trans-mit power consumption of cognitive wireless network. Compared with existing algorithms, the proposed algorithm provides lower transmit power consump-tion while guaranteeing the quality of service of secondary users.