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The paper presents a two-phase state based multi-beam-switching scheme implemented on a customdesigned 4 × 4 antenna array operating with a bandwidth of 1.5 GHz around 14 GHz. The antenna array and the beam-switching scheme have been experimentally validated. A phasing network designed to produce two phase states is used to experimentally validate the beam-switching and five beam states are presented, though this can be extended to other configurations using the split beam as a building block to construct multiple beams. The antenna can find potential use in multi-user millimetre-wave massive MIMO scenarios which require simultaneous multiple beams along selective directions. ; This work was supported by the 5G wireless project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 641985 and by the University of Cantabria PAR project P111.

In this paper, the design, operational principle and experimental validation of an endfire antenna element that is inspired by the energy-focusing characteristics of graded-index optical fibre are presented. The antenna operates with a bandwidth of 1.5 GHz centred around 14 GHz. It has a gain of around 5.5 dBi along the band of interest and a good pattern stability over the band. The antenna derives its unique nature from the arrangement of the arc-shaped parasitics, that couple onto the antenna´s driver dipole. An electromagnetic refractive index retrieval mechanism is used to guide the placement of the parasitics to enhance the gain. In addition to the design principle, a parametric study of the main parameters and their influence on the antenna behaviour is presented. The antenna is a potential candidate for use in multi-user massive MIMO antenna arrays for 5G communications where space is premium and in antenna array applications where a low-profile antenna element with a high gain is a necessity. ; This work was supported by the 5G wireless project that has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 641985.