Key Technology Of Resource Management And Allocation In Cognitive Radio Networks

With the growing popularity of wireless terminal devices, which makes new wireless services continuously arise and the utilization of spectrum resources is extremely rigorous. And the radio communication system must adopt a more innovative technologies and means to improve the utilization efficiency of spectrum resources and meet the increasing transmission rate demands of various wireless services. Cognitive radio technology is an important means to improve the spectrum efficiency, which allows the secondary users to access the unoccupied licensed band of primary users under the premise of fully protect the primary user by spectrum sensing to make full use of the spectrum resources. As one of the pivotal technologies in5G wireless communication systems, cognitive radio technology has and will continue to receive widespread attention in academia and industry.Cognitive radio technology makes the network structure of the next generation wireless communication system has great changes, in other words, the next generation network will be made up of cognitive wireless network and the primary users’network. One of the important problems which should be settled in the cognitive wireless network is the resource management and allocation problem, such as subcarrier allocation and power allocation, spectrum sharing, cognitive users access and cognitive radio technology combined with other technologies, etc. At present, there have been many scholars who carried out extensive research on this issue, which leads to a lot of relevant works, however, various problems, remain to be solved. In this dissertation, we focus on the resource management and allocation problem in cognitive radio networks, and the novelty resource allocation schemes are proposed. In addition, we validate the impact of the proposed strategies on network performance through theoretical analysis and computer simulation results. The main contributions are listed below:1. Considering the limitations of spectrum sensing techniques, we investigate the effects of imperfect spectrum sensing on cognitive radio network performance, and then we propose a probability power allocation strategy which is based on the probabilities of false alarm and miss detection.Firstly, in order to optimize the throughput of cognitive radio network, we propose a power allocation strategy based on the imperfect pectrum sensing. By analyzing the co-channel interference between primary users and secondary users caused by miss detection, the waste of the spectrum resources caused by false alarm and the side-lobe leakage interference caused by the OFDM technology with external leakage, the power allocation problem with the objective of maximizing spectrum efficiency of the cognitive radio network has been modelled as a constrained nonlinear optimization model. Then, the optimal power allocation strategy can be obtained. The simulation results verify that the proposed scheme can significantly improve cognitive network performance.Secondly, considering the channel information by imperfect spectrum sensing, another power allocation strategy with the aim at maximizing energy efficiency of the cognitive radio network has been proposed, which can be modelled as a constrained nonlinear optimization model with a fractional structure. And the nonlinear fractional programming problem can be equivalently transformed into a parametric programming problem. The simulation results show that the proposed scheme can reduce the power consumption obviously.2. Considering the QoS requirements of different secondary users, we investigate the joint subcarrier and energy-efficient power allocation problem in cognitive radio networks, and then propose an energy-efficient link adaptation scheme. Firstly, in order to optimize the energy efficiency of cognitive radio network, we propose a joint subcarrier and energy-efficient power allocation strategy considering the total power constraint and delay constraint of cognitive users, and interference constraint to primary users. Then, the delay constraint of cognitive users can be readily transformed into corresponding transmission rate constraint by queuing theory. The resource allocation problem in cognitive radio network aiming at maximizing the energy efficiency can be modelled as a constrained nonlinear fractional programming problem which can be equivalently transformed into a parametric programming problem. The dual decomposition method and bisection method can be adopted to obtain the optimal solution.3. Based on the Stackelberg model, the energy (power) cooperation problem between the primary users and secondary users is investigated, and then we propose an economic energy-efficient power allocation scheme.Firstly, we investigate the distributed relay selection and power allocation problem in a multi-user multi-relay network, aiming at maximize users’achievable rate while consume less power of relays which are selected for helping users transmit information. Then we use the auction game theory to choose the relays for each user preliminarily, then for each user and the selected relays, we model the interaction between them as a two-level Stackelberg game, the relays modelled as the service provider and the users modelled as customers who will buy power from the providers. Based on this game model, we get the relays at relatively better locations for each user and the optimal power need to buy from them. Otherwise, as the users will not exchange information between themselves, we recalculate the power allocated to each user for relays the power users buy from it exceeds the maximizing transmit power. Simulation results show the effectiveness of our proposed scheme.Secondly, different from the traditional energy efficiency metric, in this thesis, we defined a novel energy efficiency metric from the point of economics, namely, the economic energy efficiency (EEE), which represents the economic benefits by consuming unit energy (power). The interaction between the primary users and secondary users can be modelled as a Stackelberg model. And then we get the solution of the Stackelberg equilibrium problem and propose an optimal distributed EEE power allocation scheme. Simulation results show that the proposed resource allocation strategy can not only fully protect the primary user, but also requires less information exchange, which has significant advantages compared to the centralized resource allocation strategy.