The long term evolution advanced （LTE-advanced） standards target at high system performance comparable or superior to the requirements of the International mobile telecommunications advanced （IMT-advanced）. In order to support backward compatibility with LTE, most of the key technologies have been retained in LTE-advanced, one of which is the discontinuous reception mechanism （DRX）. LTE-advanced adopts carrier aggregation technology to extend the system bandwidth, which requires the LTE DRX applied in single-transceiver scenario to be adapted to multi-transceiver scenario with multiple component carriers. Apparently, carrier aggregation will influence the performance of DRX severely, so it＇s worth studying the impact brought by the coexistence ofLTE DRX and carrier aggregation on the system performance, e.g., the system delay. In this paper, first an overview of DRX in carrier aggregation scenario is given. Then it is modeled as a Markov process based on the queuing theory. Simulation results show that the independent component carrier configuration with a uniform Inactivity Timer achieves a superior service delay performance compared with other reference schemes.
Cooperative access among user devices by sharing wireless access bandwidth opens a new paradigm in heterogeneous networks. However, how to stimulate cooperative relay nodes forwarding service data for others and allocating corresponding bandwidth to support it are two key issues in the cooperative access. This paper proposes a Stackelberg game based framework which is benefit participants including relay nodes and client nodes. This framework generalizes the pricing based bandwidth allocation algorithm by the Stackelberg game model, which optimizes the profit of the cooperative relay nodes while guaranteeing the bandwidth requirements of client nodes, We transform the profit maximization problem into a convex problem and solve it using the convex optimization method. The simulation results demonstrate that the proposed framework and corresponding algorithms outperform the bidding weight proportional fairness and fixed value bandwidth allocation ones significantly.
MIAO JieHU ZhengZHANG Yi-fanGUI LiWANG Can-ruTIAN HuiYANG Kun
A challenge in the convergence of heterogeneous networks is how to combine the ubiquitous resources and provide the diversified individual services. This paper designs a market model for aggregating reconfiguration in heterogeneous networks based on the tradeoff between resource allocation and consumers＇ requirement. To unify the benefits of operators and consumers, a novel Stackelberg-based dynamic incentive pricing algorithm is proposed. The results of the theoretical analysis and simulation demonstrate that the proposed strategy provides incentive for cooperation by means of appropriate resource allocation, and improves the utilization of network resources, thereby effectively realizing the optimization of the whole network performance.
Heterogeneous networks are employed in the next generation communication systems to enhance the area spectral efficiency （ASE）, where cell range extension （CRE） is a promising technique to improve the cell edge performance and utilize the low power node （LPN） resources more effectively. In this paper we propose a dynamic spectrum aUocation scheme for Macro-Pico scenario to mitigate both the co-tier and cross-tier interferences. The available system spectrum is divided into different parts by four steps, i.e. user set partition, service request collection, cross-tier occupation and CRE occupation decision, while the service request of each user is taken into consideration. During the process implementation, the reference signal receiving power （RSRP） threshold is derived by mathematical means to judge cell edge macro users when a predefined ratio is given. Simulation results show that the proposed scheme reaches almost the same cell edge performance with the best existing option, meanwhile provides higher overall system throughput and better spectral efficiency. Therefore, much better balance is achieved.
Dynamic spectrum access（DSA）,consisting of spectrum sharing and spectrum trading stage,becomes a promising approach to increase the efficiency of spectrum usage and system performance.In this paper,from the perspective of individual interest optimization,we focus on strategy adaptation of network users and their interaction in spectrum trading process.Considering adverse effects on decision-making accuracy and the fairness among network users via local information acquirement,a hybrid game model based on global information of relevant spectrum is proposed to formulate intelligent behaviors of both primary and secondary users.Specifically,by using the evolutionary game theory,a spectrum-selection approach for the evolution process of secondary users is designed to converge to the evolutionary equilibrium gradually.Moreover,competition among primary users is modeled as a non-cooperative game and an iterative algorithm is employed to achieve the Nash equilibrium.The simulation results show that the proposed hybrid game model investigates network dynamics under different network parameter settings.
