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Explore the intersection of sensing, modulation, and coding in next-generation MIMO systems through this technical lecture by Prof. Robin Rajamäki from Tampere University. Discover how sparse antenna array geometries serve as a unifying framework connecting direction-of-arrival estimation with analog subspace coding problems traditionally found in non-coherent communications. Learn about innovative structured subspace codes that achieve near-optimal error probability and noise-robust sparse arrays that deliver high angular resolution. Examine the strategic applications of antenna subset selection in integrated communications and sensing (ISAC) systems, including how judicious antenna selection enhances sensing performance while balancing spectral and energy efficiency through multiple antennas per radio-frequency chain. Understand how sparse array geometries enable high performance while reducing hardware complexity and increasing energy efficiency in MIMO systems that operate with significantly fewer RF chains than antennas, making them ideal for resource-efficient NextG wireless systems.
