Different classes of communication network topologies and their representation in the form of adjacency matrix and its eigenvalues are presented. A self-organizing feature map neural network is used to map different classes of communication network topological patterns. The neural network simulation results are reported.
The current study investigates the dynamic relationship between structural changes, real GDP per capita, energy consumption, trade openness, population density, and carbon dioxide (CO2) emissions within the EKC framework over a period 1971-2013. The study used the autoregressive distributed lagged (ARDL) approach to investigate the long-run relationship… (More)
We show practical feasibility of Long-Term Evolution (LTE) based indoor coverage using optical wireless communication, exploiting commercially available Light Emitting Diodes (LEDs). A common LTE-Advanced signal is distributed in downlink by a visible LED, and in uplink by infrared LED (IR-LED). We demonstrate the bidirectional transmission operating in… (More)
One of the most vibrant and active " new " fields today is that of ad-hoc networks. In recent years, a variety of new routing protocols targeted specifically for ad-hoc networks have been developed. Current routing algorithms are not adequate to tackle the increasing complexity of such networks and it is not clear that any particular algorithm or class of… (More)