Ghanaatian R, Jamali V, Burg A, Schober R (2019)
Publication Type: Conference contribution
Publication year: 2019
Publisher: Institute of Electrical and Electronics Engineers Inc.
Book Volume: 2019-September
Conference Proceedings Title: IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
Millimeter wave (mmWave) communication is a promising solution for coping with the ever-increasing mobile data traffic because of its large bandwidth. To enable a suffi-cient link margin, a large antenna array employing directional beamforming, which is enabled by the availability of channel state information at the transmitter (CSIT), is required. However, CSIT acquisition for mmWave channels introduces a huge feedback overhead due to the typically large number of transmit and receive antennas. Leveraging properties of mmWave channels, this paper proposes a precoding strategy which enables a flexible adjustment of the feedback overhead. In particular, the optimal unconstrained precoder is approximated by selecting a variable number of elements from a basis that is constructed as a function of the transmitter array response, where the number of selected basis elements can be chosen according to the feedback constraint. Simulation results show that the proposed precoding scheme can provide a near-optimal solution if a higher feedback overhead can be afforded. For a low overhead, it can still provide a good approximation of the optimal precoder.
Ghanaatian, R., Jamali, V., Burg, A., & Schober, R. (2019). Feedback-Aware Precoding for Millimeter Wave Massive MIMO Systems. In IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC. Istanbul, TR: Institute of Electrical and Electronics Engineers Inc..
Ghanaatian, Reza, et al. "Feedback-Aware Precoding for Millimeter Wave Massive MIMO Systems." Proceedings of the 30th IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2019, Istanbul Institute of Electrical and Electronics Engineers Inc., 2019.