Due to the high path loss attenuations, MIMO systems with beamforming techniques are essential to ensure an acceptable range of communication in mmWave networks. In particular, the use of antenna arrays for future mobile scenarios is fundamental in order to create a beam in the direction of the user equipment. Therefore, increasing the gain of the transmission. Among the possible antenna array designs, the most suitable approach is the use of uniform planar arrays (UPA). In this configuration, the antenna elements are evenly spaced on a two-dimensional plane and a 3D beam can be synthesized.
In order to precisely evaluate mmWave scenarios, it is important to consider realistic and accurate radiation models. Related works in the literature characterize the antenna array either over-simplifying its gain with piece-wise functions, or modeling it as an array of isotropic transmitting sources. At high frequencies (e.g., mmWave bands), where high attenuations are present, quantifying the actual antenna gain obtained due to the radiation pattern is fundamental in order to precisely evaluate any mmWave system.
The radiation model proposed by the 3GPP can be used to address this issue. This model precisely simulates the radiation pattern of a patch antenna element assuming large attenuation for lobes in the opposite plane of transmission. In our works, motivated by the need to properly capture mmWave propagation behaviors and understand the achievable performance (e.g., capacity in 5G cellular scenarios), we aim at accurately characterizing the antenna radiation pattern.
Our results show how the performance changes with the radiation pattern used. Consequently, it is crucial to use an accurate and realistic radiation model for proper performance assessment and system dimensioning.
Despite our preliminary studies, a lot of research activity is still required in the optimization of array radiation components such as the spacing of the elements, the amplitude and the phase vectors of each antenna element.
LIST OF RELATED PUBLICATIONS
|P. Testolina, M. Lecci, M. Rebato, A. Testolin, J. Gambini, C. Mazzucco, and M. Zorzi, “Enabling Simulation-Based Optimization Through Machine Learning: A Case Study on Antenna Design,” in IEEE Global Communication Conference: Wireless Communication (GLOBECOM2019 WC), Waikoloa, USA, Dec 2019||2019/12||Antenna Modeling|
|M. Rebato, L. Rose and M. Zorzi, "Performance Assessment of MIMO Precoding on Realistic mmWave Channels", in IEEE ICC Workshop on Millimeter-Wave Communications for 5G and B5G, Shanghai, China, May 2019||2019/05||Interference, Precoding, Antenna Modeling|
|M. Rebato, M. Polese, and M. Zorzi, "Multi-Sector and Multi-Panel Performance in 5G mmWave Cellular Networks", in IEEE Global Communications Conference: Communication QoS, Reliability and Modeling (Globecom2018 CQRM), Abu Dhabi, UAE, Dec 2018||2018/08||Interference, Simulation, Antenna Modeling|
|M. Rebato, J. Park, P. Popovski, E. de Carvalho, and M. Zorzi, "Stochastic Geometric Coverage Analysis in mmWave Cellular Networks with Realistic Channel and Antenna Radiation Models," in IEEE Transactions on Communications.||2018/06||Interference|
|M. Rebato, L. Resteghini, C. Mazzucco, and M. Zorzi, “Study of realistic antenna patterns in 5G mmwave cellular scenarios”, in IEEE ICC Communications QoS, Reliability, and Modeling Symposium (ICC18 CQRM), Kansas City, USA, May 2018.||2018/02||Interference, Antenna Modeling|
|F. Gómez-Cuba, E. Erkip, S. Rangan and F. J. González-Castaño, "Capacity Scaling of Cellular Networks: Impact of Bandwidth, Infrastructure Density and Number of Antennas," in IEEE Transactions on Wireless Communications, vol. 17, no. 1, pp. 652-666, Jan. 2018.||2018/01||Integrated Access and Backhaul|