摘要: |
Wireless channels in vehicular communications systems rapidly vary due to the fast changes of their topology. Obtaining reliable instantaneous information about the propagation channel is invariably important in wireless communications. It is more challenging in vehicular communication systems especially at millimeter wave (mmWave) bands since the problem is further exacerbated by the hardware constraints required for mmWave systems. For example, a small number of radio frequency (RF) chains and low-resolution ADCs enforce to limit to the number of measurements for and the direct access to the channels between transceivers.
Compared to the instantaneous channel information, the second order statistics (or the spatial correlation) of the channels vary slowly so it is relatively not hard to obtain them in general. In the case of mmWave systems, however, even acquiring the second order statics is still difficult because of the lack of direct access to the channel and possibly many transmit/receive antennas with hybrid beamforming architectures � inducing high training overhead. Therefore, to overcome the problem, we aim at developing a framework to leverage the second order statistics of out-of-band channels and to estimate mmWave channel correlations by using them. Specifically, algorithms will be developed to fetch out-of-band information from sub-6 GHz channels use this information for mmWave channel correlation estimation. |