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In MIMO communications, information about the transmitted signal is conveyed to the receiver through fields and currents on the surface of the receive antenna array. However, this information can only be observed indirectly through the ports of the array. This raises fundamental information-theoretic questions: How much useful information is contained in the fields and currents on the surface of the receiver array? How much of this information is captured by the array ports? Do conventional arrays efficiently extract the information contained in their conducting surfaces? In this paper, we consider these questions in the context of a multiuser MIMO (MU-MIMO) uplink where users are separated by spatial beamforming at the receiver. Our main results can be summarized as follows: To quantify the information contained in the EM fields and currents on the surface of the receiving antenna array, we first introduce a new model, the surface receiver model. We then use this model to derive upper bounds on the spectral efficiency that can be approached with any location of M ports on the surface of the receiving antenna array. We denote this the surface modal bound. Furthermore, we also derive upper bound on the spectral efficiency approached with any number or location of ports on the receiver array. We call it the surface spectral efficiency. Finally, we apply the analytical results to a MU-MIMO uplink with an array of patch antennas at the receiver. The results suggests that the conventional arrays of single and dual-polarized patches fails to capture most of the information contained in the surface currents. The results further suggest ways to modify the number of antenna ports, together with the receiver front-end, to extract the information in the surface currents more efficiently.

Subject to the laws of classical physics -the science that governs the design of todays wireless communication systems -there is no need to match the radiation impedance of a receiver antenna to the impedance of the front-end electronics in order to effect communications. If we dispense with a transmission line and, instead, make the front-end electronics colocated with the antenna, then a high input-impedance preamplifier can measure the open-circuit voltage directly on the antenna port while drawing negligible power. Neither Friis’ concept of noise figure, nor Shannon information theory, nor electronics technology dictates that we must extract power from an antenna. Classical physics appears not to provide a lower bound on the energy that must be extracted from the antenna for every bit of received information.

Ambitions for the next generation of wireless communication include high data rates, low latency, ubiquitous access, ensuring sustainability (in terms of consumption of energy and natural resources), all while maintaining a reasonable level of implementation complexity. Achieving these goals necessitates reforms in cellular networks, specifically in the physical layer and antenna design. The deployment of transmissive metasurfaces at basestations (BSs) presents an appealing solution, enabling beamforming in the radiated wave domain, minimizing the need for energy-hungry RF chains. Among various metasurface-based antenna designs, we propose using Huygens’ metasurface-based antennas (HMAs) at BSs. Huygens’ metasurfaces offer an attractive solution for antennas because, by utilizing Huygens’ equivalence principle, they allow independent control over both the amplitude and phase of the transmitted electromagnetic wave. In this paper, we investigate the fundamental limits of HMAs in wireless networks by integrating electromagnetic theory and information theory within a unified analytical framework. Specifically, we model the unique electromagnetic characteristics of HMAs and incorporate them into an information-theoretic optimization framework to determine their maximum achievable sum rate. By formulating an optimization problem that captures the impact of HMA’s hardware constraints and electromagnetic properties, we quantify the channel capacity of HMA-assisted systems. We then compare the performance of HMAs against phased arrays and other metasurface-based antennas in both rich scattering and realistic 3GPP channels, highlighting their potential in improving spectral and energy efficiency.

This paper presents a comprehensive framework for holographic multiantenna communication, a paradigm that integrates both wide apertures and closely spaced antennas relative to the wavelength. The presented framework is physically grounded, enabling information-theoretic analyses that inherently incorporate correlation and mutual coupling among the antennas. This establishes the combined effects of correlation and coupling on the information-theoretic performance limits across SNR levels. Additionally, it reveals that, by suitably selecting the individual antenna patterns, mutual coupling can be harnessed to either reinforce or counter spatial correlations as appropriate for specific SNRs, thereby improving the performance.

Antenna efficiency is a key parameter in the design of large-scale dense arrays, and influences the signal-to-noise ratio (SNR) of wireless communications. Low embedded element efficiency (EEE) has been verified to be the bottleneck of dense array MIMO systems. Using ideas from the Floquet series, we propose a new framework to evaluate the mutual coupling for infinite arrays with a regular grid, including two new methods to calculate the EEE. The proposed methods can incorporate the impedance of the source network, whereas the traditional geometry based method assumes perfect impedance matching at all scan angles. Starting from the surface current of array elements, the radiation field is decomposed into a set of current-weighted orthogonal electromagnetic waves. This decomposition can be utilized to compute the radiation characteristics of the antenna array, including the active impedance, the generalized scattering parameters, and the embedded element patterns. Theoretical analysis is provided to illustrate how the degradation of EEE reduces the SNR and sequentially channel capacity of MIMO systems. Numerical simulations show that the proposed methods give a more accurate efficiency than the geometry based method. Channel capacity based on the polarization holographic channel model is evaluated to validate the constraining effect of EEE on system throughput.

The number of degrees of freedom (NDoF) in a communication channel fundamentally limits the number of independent spatial modes available for transmitting and receiving information. Although the NDoF can be computed numerically for specific configurations using singular value decomposition (SVD) of the channel operator, this approach provides limited physical insight. In this paper, we introduce a simple analytical estimate for the NDoF between arbitrarily shaped transmitter and receiver regions in free space. In the electrically large limit, where the NDoF is high, it is well approximated by the mutual shadow area, measured in units of wavelength squared. This area corresponds to the projected overlap of the regions, integrated over all lines of sight, and captures their effective spatial coupling. The proposed estimate generalizes and unifies several previously established results, including those based on Weyl’s law, shadow area, and the paraxial approximation. We analyze several example configurations to illustrate the accuracy of the estimate and validate it through comparisons with numerical SVD computations of the propagation channel. The results provide both practical tools and physical insight for the design and analysis of high-capacity communication and sensing systems.