Physically consistent wireless communications with statistical channel state information

The deployment of 5G and 6G wireless networks enforces a paradigm shift in communication system design, driven by the move towards sub-THz frequencies and extremely large antenna arrays. These advancements leave traditional channel modeling—which often relies on far-field assumptions and neglects electromagnetic interactions between antenna elements—physically inconsistent. Furthermore, the overhead associated with acquiring instantaneous channel state information (CSI) in massive multiple-input multiple-output (mMIMO) systems presents a critical bottleneck, particularly for low-latency or high-mobility communications.

This thesis addresses the aforementioned challenges by developing a framework for the design and analysis of noncoherent wireless communication systems that operate solely with statistical, rather than instantaneous, CSI. The core of this work is the establishment of a physically consistent channel model that accurately incorporates the effects of near-field spherical wavefronts and mutual coupling. We demonstrate that these complex physical phenomena can be effectively captured within a correlated Rayleigh fading model, providing a tractable yet realistic foundation for system analysis.

Using this framework, we investigate the performance of one-shot, energy-based communication schemes, which are particularly well suited for low-latency applications. A key result is the existence of a fundamental error floor at high signal-to-noise ratio (SNR) for constellations with more than two energy levels when no CSI is available at the transmitter. However, we also prove that this error vanishes as the number of receiver antennas grows, highlighting the channel hardening benefits of massive arrays.

A widely adopted receiver in energy-based noncoherent systems is the so-called energy detector. Although it is optimal under uncorrelated fading, its performance degrades significantly in correlated channels. To address this limitation, we introduce a novel class of quadratic detectors, including the best quadratic unbiased estimator (BQUE) as well as a practical implementation called assisted BQUE. These detectors leverage statistical CSI to achieve near-optimal performance. Furthermore, two strategies for enhancing reliability are proposed and evaluated: a constellation design methodology that minimizes the analytical symbol error rate by leveraging statistical CSI at the transmitter, and a permutational index modulation (PIM) scheme that introduces coding gain with minimal complexity.

Finally, the thesis explores the impact of model mismatch, revealing that noncoherent systems exhibit greater robustness to mutual coupling than their coherent counterparts. We also demonstrate that wavefront curvature can be exploited well beyond the classical Fraunhofer distance. Moreover, we show that large antenna arrays enable the multiplexing and low-complexity detection of multiple users, even when employing noncoherent processing.