Characterization of Human Blockage in 60 GHz Communication

The massive availability of bandwidth in the millimeter wave (mmWave) frequency band has the potential to address the challenges posed by the unprecedented increase in the mobile data traffic. Therefore, mmWave wireless access is being seen as a promising candidate for multi-Gbps wireless access in the next generation (i.e., 5G) of wireless communications. In particular, 60 GHz frequency band with 9 GHz of unlicensed bandwidth (57-66 GHz) is being considered for the next generation of Wireless Local Area Networks (WLANs) for high data rate indoor communications. Although the 60 GHz band provides very high data rates, its signal propagation properties are quite different from the 2.4/5 GHz bands. The high free-space path loss in 60 GHz band requires directional antennas to compensate for this high path loss. Further, the small wavelengths in 60 GHz frequency band makes 60 GHz links highly susceptible to blockage due to its inability to penetrate the obstacles. For example, human shadowing overwhelmingly attenuates the received signal power and results in frequent blockages. In this thesis, we experimentally evaluate the impact of human blockage on the performance (link quality, data rate) of Commercial Off-The Shelf (COTS) 60 GHz devices. To identify the blockages due to the human activities, we propose a reactive blockage characterization algorithm based on the observation of signal quality degradation time; and signal quality recovery time. Based on this, we categorized the blockage into: (i) short-term and (ii) long-term blockage. Our measurement results indicate that different actions are required to circumvent the link disruption caused by the long-term and the short-term human blockages. We show that in case of a long-term blockage, connecting to an alternate access point (AP) or searching for an alternate path helps in maintaining the link quality. On the other hand, in case of short-term blockage it is not advantageous to look for alternate APs or paths due to its transient nature. We also show that the incorrect detection of a blockage type aggravates the throughput performance degradation. Furthermore, we derive an important trade-off relation between the decision time and the accuracy of blockage-type detection, and show that by using an appropriate decision threshold, correct action can be executed with high detection accuracy.

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