Media-Based Modulation for Next-Generation Wireless: Latest Progress and New Applications

Media-based modulation (MBM) is a novel technique for embedding information in the channel states via intentional perturbations of the transmission media. This article provides an overview of MBM and its benefits while highlighting relevant challenges and future research directions. We explain how MBM differs from source-based modulation and how it addresses issues in legacy multiple-input multiple-output (MIMO) systems, such as deep fades and MIMO diversity-multiplexing trade-off. We demonstrate how MBM works in harmony with other index modulations and improves upon them by providing similar advantages with a more compact transmitter. Numerical results (simulation and analytical) support these claims and include outage comparison with legacy MIMO systems, comparisons with other state-of-the-art modulation schemes, and a performance example showcasing transmitting 32 bits of information in a single channel use with an excellent symbol error rate of $\mathsf {SER} \simeq 10^{-5}$ at “energy per bit to noise power spectral density ratio” of $\mathsf {E_{b}/N_{0}} \simeq -3.5$ dB. The article continues with methods to address the issues of receiver training and decoding for large constellation sets. A number of other research questions, such as pulse shaping to limit bandwidth expansion due to the time-varying nature of MBM and the effect of forward error correcting codes on MBM diversity order are discussed. We present an RF transceiver structure that generates independent propagation paths for embedding information. Fabrication and testing of the transceiver structure show close agreement between simulation and measurement. There are inherent connections between MBM and Intelligent Reflecting Surface (IRS). These connections, including the application of MBM in beamforming, are discussed. We present a solution that involves the integration of a filtering radiating patch within the MBM walls to restrict bandwidth expansion. Lastly, we delve into several specific application domains for MBM.