Coherent and Noncoherent Detection in Dense Arrays: Can We Ignore Mutual Coupling?

This paper investigates the impact of mutual coupling on MIMO systems with densely deployed antennas. Leveraging multiport communication theory, we analyze both coherent and noncoherent detection approaches in a single-user uplink scenario where the receiver ignores mutual coupling effects. Simulation results indicate that while coherent detection is generally more accurate, it is highly sensitive to mismatches in the coupling model, leading to severe performance degradation when antennas are closely spaced, to the point of becoming unusable. Noncoherent detection, on the other hand, exhibits a higher error probability but is more robust to coupling model mismatches.

Harnessing Wavefront Curvature and Spatial Correlation in Noncoherent MIMO Communications

Noncoherent communication systems have regained interest due to the growing demand for high-mobility and low-latency applications. Most existing studies using large antenna arrays rely on the far-field approximation, which assumes locally plane wavefronts. This assumption becomes inaccurate at higher frequencies and shorter ranges, where wavefront curvature plays a significant role and antenna arrays may operate in the radiative near field. In this letter, we adopt a model for the channel spatial correlation matrix that remains valid in both near and far field scenarios. Using this model, we demonstrate that noncoherent systems can leverage the benefits of wavefront spherical curvature, even beyond the Fraunhofer distance, revealing that the classical far-field approximation may significantly underestimate system performance. Moreover, we show that large antenna arrays enable the multiplexing of various users and facilitate near-optimal noncoherent detection with low computational complexity.

Asymptotic Analysis of Near-Field Coupling in Massive MISO and Massive SIMO Systems

This paper studies the receiver to transmitter antenna coupling in near-field communications with massive arrays. Although most works in the literature consider that it is negligible and approximate it by zero, there is no rigorous analysis on its relevance for practical systems. In this work, we leverage multiport communication theory to obtain conditions for the aforementioned approximation to be valid in MISO and SIMO systems. These conditions are then particularized for arrays with fixed inter-element spacing and arrays with fixed size.

Quadratic Detection in Noncoherent Massive SIMO Systems over Correlated Channels

With the goal of enabling ultrareliable and low-latency wireless communications for industrial internet of things (IIoT), this paper studies the use of energy-based modulations in noncoherent massive single input multiple output (SIMO) systems. We consider a one-shot communication over a channel with correlated Rayleigh fading and colored Gaussian noise. We first provide a theoretical analysis on the limitations of non-negative pulse-amplitude modulation (PAM) in systems of this kind, based on maximum likelihood detection. The existence of a fundamental error floor at high signal-to-noise ratio (SNR) regimes is proved for constellations with more than two energy levels, when no (statistical) channel state information is available at the transmitter. In the main body of the paper, we present a design framework for quadratic detectors that generalizes the widely-used energy detector, to better exploit the statistical knowledge of the channel. This allows us to design receivers optimized according to information-theoretic criteria that exhibit lower error rates at moderate and high SNR. We subsequently derive an analytic approximation for the error probability of a general class of quadratic detectors in the large array regime. Finally, we introduce an improved reception scheme based on the combination of quadratic detectors and assess its capabilities numerically.