Quasi-deterministic approach to mmWave channel modeling in a non-stationary environment

Abstract

There is increasing faith that mmWave technology will be part of 5G wireless networks in the wide frequency range 30-90 GHz. Experimental measurements are used to model mmWave channels addressing issues like human body shadowing or reflections due to moving vehicles. In this paper a new quasi-deterministic (Q-D) approach is introduced for modeling mmWave channels. The proposed channel model allows natural description of scenario-specific geometric properties, reflection attenuation and scattering, ray blockage and mobility effects. This new channel modeling approach is of utmost importance for further measurement campaigns planning, channel model characterization, system level simulations and network access capacity estimations

Obstacle avoidance cell discovery using mm-waves directive antennas in 5G networks

“…In Fig. 4 the average rendezvous time is shown as function of memoryrange (m) parameter, when the number of obstacles placed in the area varies 2 . Clearly, when the number of obstacles is low (e.g., 3 obstacles), the announced user location can be likely reached through a direct beam (left points on the graph).…”

“…Refraction and reflection effects are adversely hampered by the presence of obstacles along the communication path. Therefore, modeling the propagation channel under those conditions becomes very challenging due to huge number of parameters to be tuned [2]. Fortunately, while the very small wave-length negatively affects the channel attenuation, this readily allows to use much more antenna elements in very limited areas (suitable for mobile devices).…”

Quasi-deterministic millimeter-wave channel models in MiWEBA

“…The analysis of experimental measurements described in Section 2 and the results available from previous experimental campaigns [9,17] campus, etc.) scenario was developed.…”

“…Such an approach, called Q-D, was offered for modeling access and backhaul millimeter-wave channels at 60 GHz [9,15]. The approach builds on the representation of the millimeter-wave channel impulse response comprised of a few Q-D strong rays (D-rays), a number of relatively weak random rays (R-rays, originating from the static surfaces reflections), and flashing rays (F-rays, originating from moving cars, buses, and other dynamic objects reflections).…”

“…This modeling approach was chosen in order to accurately support spatial consistency that would not be possible with a statistical model. New experimental data for an open square scenario measurement are used to improve the modeling methodology described previously in [8,9]. An extension is given in a form of the CEPD model that can be used to abstract the generic Q-D model to system level requirements, such as limited bandwidth and impact of antennas.…”