Noncoherent magnitude-based MIMO (NMB-MIMO) has been envisaged as a promising architecture for the low-cost implementation of massive machine-type communications (mMTC). Nevertheless, the existing channel estimation methods are not applicable to NMB-MIMO due to its unique magnitude-only detection mechanism. This paper introduces an innovative channel estimation framework specifically designed for NMB-MIMO systems. Initially, we deploy a local oscillator (LO) to transmit known reference signals, and the NMB-MIMO channel estimation is formulated as a compressive phase retrieval problem by leveraging the inherent angular-domain sparsity of wireless channels. To address the proposed problem, we subsequently develop an efficient universal compressive phase retrieval (UCPR) algorithm. Simulation results demonstrate the robustness of the proposed UCPR approach, validating its effectiveness in accurately reconstructing NMB-MIMO channels.

The paradigm shift from massive MIMO to extremely large MIMO (XL-MIMO) catalyzes significant improvements in the spectral efficiency and spatial resolution of MIMO systems. However, the large-scale arrays also lead to the near-field effect, which indicates the coexistence of far-field and near-field user equipments (UEs). This paper proposes a unified beam training framework applicable to both far-field and near-field scenarios, even including thosewithin the Fresnel distance. Specifically, our proposed beam training method builds upon a rigorous wavenumber-domain spectrum analysis based on the geometric propagation characteristics. By estimating the non-zero boundaries rather than the specific non-zero entries in the wavenumber-domain spectrum, we introduce an efficient and fidelity-robust algorithm to estimate the location of the UE, which is termedellipse-fitting localization (EFL). Simulation results validate the effectiveness of our beam training framework across far-field and near-field scenarios, even within the Fresnel distance.

The mutual coupling (MC) effect refers to the phenomenon where the voltage on one antenna element induces excitation currents on nearby antenna elements. This paper initially derives precise MC matrices grounded in meticulous circuit and antenna theories, unveiling the asymmetry of MC effects between the transmitter (Tx) and receiver (Rx). This asymmetry arises from the fact that the transmitted signal is the voltage on the antenna elements, whereas the received signal represents the voltage input to the low-noise amplifiers (LNAs). Upon this approach, an MC-aware hybrid beamforming methodology is introduced to mitigate distortions in radiation patterns precipitated by MC effects. Furthermore, we undertake comprehensive performance analysis across various antenna topologies, including rectangular, hexagonal, circular, and concentric circular configurations. Simulation results substantiate the necessity for addressing MC effects and demonstrate the effectiveness of our proposed MC-aware hybrid beamforming methodology. Moreover, these results indicate that MC effects can enhance the capacity under certain antenna separations and topologies, highlighting that MC effects are not merely detrimental but potentially beneficial in densely-packed MIMO.

The large antenna aperture in extremely large-scale multiple-input-multiple-output (XL-MIMO) systems results in a hybrid far and near-field communication. Existing hybrid-field beam training works mostly treat plane waves as spherical ones with infinite distance, thereby inheriting several limitations associated with spherical wave based training, such as protocol incompatibility, high overhead, and complex hierarchical codebook design. To address these issues, we propose a unified far-field and near-field wavenumber domain beam training framework, involving a semi-codebook-based beam sweeping scheme and a hierarchical training strategy. The core idea is reinterpreting spherical wave as a superposition of plane waves, retaining accuracy while inheriting the charming protocol compatibility, low overhead, and simple codebook design provided by plane waves. Moreover, due to the linearity of plane waves, the ideal beam pattern with negligible power leakage can be easily obtained by the proposed phased-shifted alternative minimization (PS-AltMin) codeword design method. Finally, numerical results show that the proposed wavenumber domain beam training methods have a significant achievable rate gain compared to the benchmarks, which comes from the use of the semi-codebook-based transmission technique and the unified channel model for both far-field and near-field.

This paper addresses the critical challenges of fractional delay and Doppler effects in low earth orbit (LEO) satellite orthogonal time-frequency space (OTFS) systems, where conventional channel estimation methods suffer from high complexity and inadequate prior utilization. To overcome these limitations, we propose a fast and robust framework with: 1) A subspace-constrained variational Bayesian inference (SC-VBI) mechanism that reduces complexity by decoupling high-dimensional matrix operations and 2) A statistical Delay-Doppler-prior (SD2P) integration scheme leveraging elevation angle distributions from real-world LEO orbital dynamics to enhance sparse signal recovery (SSR) accuracy. Departing from traditional sparse Bayesian learning (SBL) approaches, our algorithm mitigates the curse of dimensionality through iterative sub-space updates while embedding physical-layer Doppler characteristics into Bayesian priors. Simulations under 3GPP LEO configurations demonstrate that the proposed method achieves a ten-times compression in computational time and 60% normalized mean square error (NMSE) improvement.

Rydberg atomic receivers have been envisaged as a revolutionary technology for future wireless communications and sensing. In order to detect the angle of arrival (AoA), researchers have typically constructed arrays comprisingmultipleRydberg atomic receivers. This paper presents a novel finding: The AoA of an incident signal can be accurately recovered even with asingleRydberg atomic receiver, by harnessing the phenomenon of inner-vapor interference. Firstly, we apply the micro-element method to the atomic vapor and derive a closed-form expression for the laser transmission in the presence of interference between the incident and local oscillator (LO) radio frequency (RF) signals. Secondly, we propose a robust method to estimate the AoA based on the particle swarm optimization (PSO) algorithm. Simulation results substantiate the effectiveness of our proposed scheme with practical parameter settings, verifying the applicability of AoA detection using a single Rydberg atomic receiver.