Automated Identification of Clusters in UWB Channel Impulse Responses

TitleAutomated Identification of Clusters in UWB Channel Impulse Responses
Publication TypeConference Paper
Year of Publication2007
AuthorsChuang, J., S. Bashir, and D. G. Michelson
Conference NameElectrical and Computer Engineering, 2007. CCECE 2007. Canadian Conference on
Pagination761 -764
Date Publishedapr.
Keywordschannel modeling process, cluster identification, IEEE 802.15.3a, IEEE 802.15.4a, ultra wideband communication, UWB channel impulse responses, wireless channels

The tendency for the multipath components (MPCs) in wideband channel impulse responses (CIRs) to appear in clusters that are characterized by their own arrival and decay rates was first observed over twenty years ago by Saleh and Valenzuela. Cluster identification is thus an obvious and essential first step in the channel modeling process. However, despite the tremendous effort that has been applied to ultra wideband (UWB) channel modeling by groups such as IEEE 802.15.3a and 802.15.4a in recent years, clusters are still usually identified through time-consuming manual techniques that rely on subjective assessment by the analyst. This presents a significant limitation to development of channel models applicable to new environments. Our algorithm for automated identification of clusters in UWB CIRs seeks to overcome these limitations by making cluster identification less subjective and less time consuming. The starting point for the algorithm is expression of the UWB power delay profile (PDP) on a semi-logarithmic scale so that exponential decay profiles will be displayed as straight lines with constant slopes. After the most significant MPCs have been identified by searching for local maxima within the PDP, an iterative procedure is used to determine the combination of straight lines that best fit these MPCs and thereby not exceed a threshold for RMS error. The number of clusters that are required is defined by number of straight lines while the slopes of the lines define the cluster decay rate. By assuming that incrementing the number of clusters used to represent a CIR will always involve subdividing an existing cluster, we reduce the number of combinations dramatically (and make the algorithm tractable). Cluster identification trials conducted using UWB CIRs generated using a simulation code developed by the IEEE 802.15.4a channel modeling committee have confirmed the validity of our approach.


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