Joint Link Allocation and Rate Assignment Algorithm for Multi-Channel Wireless Networks

This paper presents a link allocation and rate assignment algorithm for multi-channel wireless networks. The objective is to reduce network con-flicts and guarantee the fairness among links. We first design a new network model. With this net-work model, the multi-channel wireless network is divided into several subnets according to the num-ber of channels. Based on this, we present a link allocation algorithm with time complexity O（l^2）to al-locate all links to subnets. This link allocation algo-rithm adopts conflict matrix to minimize the network contention factor. After all links are allocated to subnets, the rate assignment algorithm to maximize a fairness utility in each subnet is presented. The rate assignment algorithm adopts a near-optirml al-gorithm based on dual decomposition and realizes in a distributed way. Simulation results demonstrate that, compared with IEEE 802.11b and slotted see-ded channel hopping algorithm, our algorithm de-creases network conflicts and improves the net-work throughput significantly.

Social-Aware Joint Mode Selection and Link Allocation for Device-to-Device Communication Underlaying Cellular Networks

Joint mode selection and link allocation are crucial to achieve the advantage of Device-to-Device(D2 D) communications in improving spectral efficiency. In practice, cellular users tend to not be totally altruistic or absolutely selfish. How to stimulate them to devote their links and how to allocate their links to D2 D pair candidates efficiently are two main challenges. In this paper, we encourage cellular users through the variable payment with regard to the social tie strength between cellular users and D2 D pair candidates. In particular, the social tie strength is inferred through a graph inference model and its impact on the payment is quantified as a negative exponential function. Then, we propose a resource scheduling optimization model based on the non-transferable utility coalition formation game, and a distributed coalition formation algorithm based on the Pareto preference and merge-and-split rule. From them, the final coalition structure is obtained, which reflects the strategy of mode selection and link allocation. Numerical results are presented to verify the effectiveness of our proposed scheme.

LBLP:Link-Clustering-Based Approach for Overlapping Community Detection

Recently, complex networks have attracted considerable research attention. Community detection is an important problem in the field of complex networks and is useful in a variety of applications such as information propagation, link prediction, recommendation, and marketing. In this study, we focus on discovering overlapping community structures by using link partitions. We propose a Latent Dirichlet Allocation （LDA）-Based Link Partition （LBLP） method, which can find communities with an adjustable range of overlapping. This method employs the LDA model to detect link partitions, which can calculate the community belonging factor for each link. On the basis of this factor, link partitions with bridge links can be found efficiently. We validate the effectiveness of the proposed solution by using both real-world and synthesized networks. The experimental results demonstrate that the approach can find a meaningful and relevant link community structure.