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Pathloss is one of the essential characteristics of wireless propagation channels. It is usually captured from channel measurements with (quasi)isotropic antennas. To characterize the wireless channels at high frequencies, beamforming or directional antennas are commonly used, in which case a method for estimating the isotropic pathloss is needed. The method should account for the possible spatial overlap of the different directional measurements while including the received signal from all the multipath components in the channel. In this letter, we propose an efficient method that uses a weighted sum of the powers received from the directional measurements. The weights can be calculated using matrix inversion. We verify the solution using synthetic data and demonstrate the usage with measurements at sub-THz frequencies. 

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.