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Due to recent boom of network applications, access to network usage data has earned tremendous attention. As traditional usage exporting mechanisms become inadequate to support current needs, the Internet Protocol Detail Records(IPDR) stands as an outstanding solution in transferring general network management and measurement information. This paper briefly describes IPDR in terms of high-level model...
Interference alignment is a new technique recently proposed in physical layer wireless communications research, which purposely align the interference among multiple users thus increase the efficiency of channel use. This paper proposes a new method to enhance throughput of multi-hop wireless networks by utilizing interference alignment at physical layer. At first, it takes a simple network with only...
This paper presents a study on joint optimization of antenna orientation and spectrum allocation, with the objective of maximizing the total throughput of a cognitive radio network. The mathematical model is presented and subsequently formulated as a Mixed Integer Linear Programming problem. We obtain the optimal solution by adopting the branch and bound algorithm. Through simulation results, we investigate...
We consider a cognitive radio network in which a set of base stations make opportunistic spectrum access to support wireless subscribers within their covering cells. The spectrum of interest is divided into independent channels licensed to the primary users. Channel assignment and power control must be carried out in the cognitive network so that no excessive interference is caused to the primary...
Relay transmissions improve performance and save communication energy in wireless network. We present an optimal relay nodes assignment algorithm to maximize the number of information packets received at the sink for a two-tiered wireless network, in which the relay nodes are temporarily placed and have energy constraint. We first derive the optimal transmit power theory from relay node to sink node...
In this paper, we present a self-adapted fuzzy method to predict network traffic . This method incorporates the traffic decomposition by wavelet transform as well as a fuzzy lookup scheme. In addition, a clustering method is designed to determine the parameters of membership functions of the fuzzy system. The experimental results show that our method can enhance the prediction accuracy
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