The paper defines self-similarity for vector processes by employing the discrete-time continuous-dilation operation which has successfully been used previously by the authors to define 1-D discrete-time stochastic self-similar processes. To define self-similarity of vector processes, it is required to consider the cross-correlation functions between different 1-D processes as well as the autocorrelation function of each constituent 1-D process in it. System models to synthesize self-similar vector processes are constructed based on the definition. With these systems, it is possible to generate self-similar vector processes from white noise inputs. An important aspect of the proposed models is that they can be used to synthesize various types of self-similar vector processes by choosing proper parameters. Additionally, the paper presents evidence of vector self-similarity in two-channel wireless LAN data and applies the aforementioned systems to simulate the corresponding network traffic traces.

Date Published: 23 July 2003
PDF: 11 pages
Proc. SPIE 5100, Digital Wireless Communications V, (23 July 2003); doi: 10.1117/12.498577

Published in SPIE Proceedings Vol. 5100:
Digital Wireless Communications V
Raghuveer M. Rao; Soheil A. Dianat; Michael D. Zoltowski, Editor(s)