Programming Wireless Security Through Learning-Aided Spatiotemporal Digital Coding Metamaterial Antenna

The advancement of future large-scale wireless networks necessitates the development of cost-effective and scalable security solutions. Specifically, physical layer (PHY) security has been put forth as a cost-effective alternative to cryptographic mechanisms that can circumvent the need for explicit key exchange between communication devices. Herein, a space-time-modulated digitally-coded metamaterial (MTM) leaky wave antenna (LWA) is proposed that can enable PHY security by achieving the functionalities of directional modulation (DM) using a machine learning-aided branch-and-bound (B & B) optimized coding sequence. Theoretically, it is first shown that the proposed space-time MTM antenna can achieve DM through both the spatial and spectral manipulation of the orthogonal frequency division multiplexing signal. Simulation results are then provided as proof-of-principle, demonstrating the applicability of the approach for achieving DM in various communication settings. Furthermore, a prototype of the proposed architecture controlled by a field-programmable gate array is realized, which achieves DM via an optimized coding sequence carried out by the learning-aided B & B algorithm corresponding to the states of the MTM LWA's unit cells. Experimental results confirm the theory behind the space-time-modulated MTM LWA in achieving DM, which is observed via both the spectral harmonic patterns and bit error rate measurements.