60 GHz Blockage Study Using Phased Arrays

The millimeter wave (mmWave) frequencies offer the potential for enormous capacity wireless links. However, designing robust communication systems at these frequencies requires that we understand the channel dynamics over both time and space: mmWave signals are extremely vulnerable to blocking and the channel can thus rapidly appear and disappear with small movement of obstacles and reflectors. In rich scattering environments, different paths may experience different blocking trajectories and understanding these multi-path blocking dynamics is essential for developing and assessing beamforming and beam-tracking algorithms. This paper presents the design and experimental results of a novel measurement system which uses phased arrays to perform mmWave dynamic channel measurements. Specifically, human blockage and its effects across multiple paths are investigated with only several microseconds between successive measurements. From these measurements we develop a modeling technique which uses low-rank tensor factorization to separate the available paths so that their joint statistics can be understood.Comment: To appear in the Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 201

A Normalization Model for Analyzing Multi-Tier Millimeter Wave Cellular Networks

Based on the distinguishing features of multi-tier millimeter wave (mmWave) networks such as different transmit powers, different directivity gains from directional beamforming alignment and path loss laws for line-of-sight (LOS) and non-line-of-sight (NLOS) links, we introduce a normalization model to simplify the analysis of multi-tier mmWave cellular networks. The highlight of the model is that we convert a multi-tier mmWave cellular network into a single-tier mmWave network, where all the base stations (BSs) have the same normalized transmit power 1 and the densities of BSs scaled by LOS or NLOS scaling factors respectively follow piecewise constant function which has multiple demarcation points. On this basis, expressions for computing the coverage probability are obtained in general case with beamforming alignment errors and the special case with perfect beamforming alignment in the communication. According to corresponding numerical exploration, we conclude that the normalization model for multi-tier mmWave cellular networks fully meets requirements of network performance analysis, and it is simpler and clearer than the untransformed model. Besides, an unexpected but sensible finding is that there is an optimal beam width that maximizes coverage probability in the case with beamforming alignment errors.Comment: 7 pages, 4 figure