Search for: All records

Design and standardization of future millimeter-wave (mmWave) wireless communications systems require accurate models of wireless propagation channels. In particular, comprehensive statistical models describing the effect of human bodies moving randomly in the surrounding environment, acting as reflectors or absorbers, on the received power and delay spread are urgently needed. To enable these, new measurements campaigns are required based on channel sounders designed specifically to capture the realtime dynamics of the channel responses. This paper proposes a new methodology to enable fully dynamic measurements with a pseudonoise (PN)-sequence channel sounder by means of quasi-perfect transmitter-receiver (Tx-Rx) synchronization and suppression of probing signal effects in the post-processed channel impulse responses (CIRs). This approach allows the identification of the weak multipath components (MPCs) originated by reflections on the human body. The approach is validated by analysing CIRs collected in an indoor environment with one person moving close to the 60 GHz link. The results also demonstrate that future mmWave systems could exploit these additional MPCs and benefit from human interactions. 

The 60 GHz band plays an important role for wireless signalling with extremely high data rates, both for WiFi and cellular applications. For the design and performance analysis of this band, the impact of human interactions on the propagation from transmitter to receiver has to be taken into account. While the impact of a single human body blocking the line-of-sight (LOS) has been investigated as a deterministic effect, statistical models describing the effect of multiple human bodies, acting as reflectors, on received power and delay spread are still lacking. To close this gap, this paper analyzes measurements of 60 GHz channel impulse responses in static but “evolutionary” office scenarios that involve one and two people and uses them to calibrate a ray tracer that allows the generation of a larger number of channel realizations. Regression fits are applied to the resulting channel responses to obtain an accurate characterization of human-induced power and delay variations in proximity situations where humans give rise to additional multipath.