Interference Coordination Based Resource Allocation For Next Generation Mobile Communication Networks

In OFDMA based wireless communication systems, in order to further improvenetwork performance, evolving cellular network topology to heterogeneous structure,has become a technique trend and attracted much attention from both industry andacademic community. In particular, heterogeneous networks have been introduced inthe LTE-Advanced, as a standard for next generation mobile networks. Aheterogeneous network deploys some low-power nodes such as femtos and relays inorder to bring the network closer to end users. In this way, network throughput andcoverage can be effectively improved. Nevertheless, the heterogeneity of networks alsobrings in some technique challenges. Specifically, low-power overlay base stationsmay coexist in the same geographical area, potentially sharing the same spectrum. Thiskind of spectrum reuse may lead to strong interferences and thus greatly deterioratesystem performance. As interference is an important issue to the successful deploymentof heterogeneous networks, in this dissertation we mainly address the interferencesintroduced by relays and femtos. Based on convex optimization and game theory, wedesign some new analysis models and develop a number of interference coordinationschemes which can provide effective solutions to resource allocation ininterference-prone wireless communications.We first analyze the possible interference scenarios in the relay networks anddevelop a general classification of interference levels. Based on the insights in ouranalysis, we propose an Integrated Interference Coordination Scheme (IICS) whichperforms a number of resource allocation algorithms according to traffic load. Weconduct simulation experiments based on the model with realistic broadband channelpropagation conditions. Numerical results show that our proposed IICS can effectivelyimprove system throughput compared with the resource allocation schemes withoutadequate interference coordination. In addition, our proposed scheme dose not havecomplicated theoretical model and with low complexity. Thus it is practical and canprovide an effective solution to the resource allocation in the interference-aware cases.Interferences in wireless networks mainly stem from the competition of limited frequency resources among users. The users may act in a selfish fashion to use moreresources regardless of interferences they may generate if no measure is taken. Totackle this problem, we develop a non-cooperative game theoretic framework calledInterference Coordination Game (ICG) to mitigate interferences in OFDMA relaynetworks. In ICG, we define the utility function of a player as the sum of theinterferences it generates and it is suffered. A higher system payoff can be obtained byimproving individual players’ payoff. Moreover, we take into account not onlyinterferences, but also signal strength of players. Thus, players can choose appropriatestrategies to mitigate interferences without excessively compromising data rate of users.In order to obtain equilibrium of the game with a reasonable complexity, wedecompose ICG into two sub-games and propose an efficient pre-process algorithm.Numerical results demonstrate that our proposed interference coordination approachcan guarantee that the game converges to NE (Nash Equilibrium) with a reasonablecomplexity, and achieve better performance in terms of SINR distribution and systemthroughput compared with the schemes without interference coordination.Interference coordination can potentially increase data rate of users. However, inrelay networks, the available data rate of a relay link user is also affected by thethroughput of the backhaul link. Therefore, we carefully investigate the relationshipbetween the access link and the backhaul link, and then propose a two-stage gamebased on the Stackelberg model. Simulation results show that the proposed algorithm isbeneficial to balancing the throughput of two-hop links and can improve the systemperformance compared with the average allocation or separate allocation schemes. Inaddition, our approach also can be extended to solve other similar problems, such asthe balance of traffic load among different cells.Different from relay networks, the deployment of femtocells will bring the deadzone problem, in which the macro users will severely interfered by the neighboringfemtocell in the downlink. In view of this, we can change access points for these macrousers to mitigate interference. In open access mode, we design a graph-based approachand a game based interference coordination algorithm respectively. The former can beused to avoid interference when the available RBs (Resource Blocks) are sufficient,while the latter can be used in general cases to realize the selection of access point forusers. Furthermore, in hybrid access mode, we propose an interference coordination algorithm based on double auction model. By asking or bidding price, we provide amechanism that the femtocells are willing to provide access right to nonsubscribers.The users suffered from strong interferences can achieve higher data rate than thatwhen they are in the close access mode. Our proposed interference coordinationschemes cannot only effectively reduce interference, but also provide accesssuggestion for the users with different constraints or different priority.For addressing the interference problems introduced by heterogeneous networks,we analyze the possible interference scenarios and build corresponding analyticalmodels. Furthermore, we propose effective solutions of interference coordinationschemes and resource allocation algorithms. Note that our proposed algorithms fit forthe basic framework of LTE-Advanced, and thus they can provide effective solutionsto the development of LTE-Advanced system. On the other hand, our developedsolutions are not limited by the current standards, and can be applied to interferenceanalysis, modeling and solving of the general cases.