Binary Stellar Population Synthesis Model

Using Yunnan evolutionary population synthesis (EPS) models, we present integrated colours, integrated spectral energy distributions (ISEDs) and absorption-line indices defined by the Lick Observatory image dissector scanner (Lick/IDS) system, for an extensive set of instantaneous-burst binary stellar populations (BSPs) with interactions. By comparing the results for populations with and without interactions we show that the inclusion of binary interactions makes the appearance of the population substantially bluer. This effect raises the derived age and metallicity of the population. To be used in the studies of modern spectroscopic galaxy surveys at intermediate/high spectral resolution, we also present intermediate- (3A) and high-resolution (~0.3A) ISEDs and Lick/IDS absorption-line indices for BSPs. To directly compare with observations the Lick/IDS absorption indices are also presented by measuring them directly from the ISEDs.Comment: 2 pages 2 figure

Joint Dynamic Radio Resource Allocation and Mobility Load Balancing in 3GPP LTE Multi-Cell Network

Load imbalance, together with inefficient utilization of system resource, constitute major factors responsible for poor overall performance in Long Term Evolution (LTE) network. In this paper, a novel scheme of joint dynamic resource allocation and load balancing is proposed to achieve a balanced performance improvement in 3rd Generation Partnership Project (3GPP) LTE Self-Organizing Networks (SON). The new method which aims at maximizing network resource efficiency subject to inter-cell interference and intra-cell resource constraints is implemented in two steps. In the first step, an efficient resource allocation, including user scheduling and power assignment, is conducted in a distributed manner to serve as many users in the whole network as possible. In the second step, based on the resource allocation scheme, the optimization objective namely network resource efficiency can be calculated and load balancing is implemented by switching the user that can maximize the objective function. Lagrange Multipliers method and heuristic algorithm are used to resolve the formulated optimization problem. Simulation results show that our algorithm achieves better performance in terms of user throughput, fairness, load balancing index and unsatisfied user number compared with the traditional approach which takes resource allocation and load balancing into account, respectively