Subject to the laws of classical physics - the science that governs the design of today's 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.

A closed electromagnetic resonant chamber (RC) is a highly favorable artificial environment for wireless communication. A pair of antennas within the chamber constitutes a two-port network described by an impedance matrix. We analyze communication between the two antennas when the RC has perfectly conducting walls and the impedance matrix is imaginary-valued. The transmit antenna is driven by a current source, and the receive antenna is connected to a load resistor whose voltage is measured by an infinite-impedance amplifier. There are a countably infinite number of poles in the channel, associated with resonance in the RC, which migrate towards the real frequency axis as the load resistance increases. There are two sources of receiver noise: the Johnson noise of the load resistor, and the internal amplifier noise. An application of Shannon theory yields the capacity of the link, subject to bandwidth and power constraints on the transmit current. For a constant transmit power, capacity increases without bound as the load resistance increases. Surprisingly, the capacity-attaining allocation of transmit power versus frequency avoids placing power close to the resonant frequencies.

The increasing demand for wireless data transfer has been the driving force behind the widespread adoption of Massive MIMO (multiple-input multiple-output) technology in 5G. The next-generation MIMO technology is now being developed to cater to the new data traffic and performance expectations generated by new user devices and services in the next decade. The evolution towards "ultra-massive MIMO (UM-MIMO)" is not only about adding more antennas but will also uncover new propagation and hardware phenomena that can only be treated by jointly utilizing insights from the communication, electromagnetic (EM), and circuit theory areas. This article offers a comprehensive overview of the key benefits of the UM-MIMO technology and the associated challenges. It explores massive multiplexing facilitated by radiative near-field effects, characterizes the spatial degrees-of-freedom, and practical channel estimation schemes tailored for massive arrays. Moreover, we provide a tutorial on EM theory and circuit theory, and how it is used to obtain physically consistent antenna and channel models. Subsequently, the article describes different ways to implement massive and dense antenna arrays, and how to co-design antennas with signal processing. The main open research challenges are identified at the end.

This paper provides a deterministic channel model for a scenario where wireless connectivity is established through a reflection off a smooth planar surface of an infinite extent. The developed model is rigorously built upon the physics of wave propagation and is as precise as tight are the unboundedness and smoothness assumptions on the surface. This model allows establishing how line-of-sight multiantenna communication is altered by a reflection off an electrically large surface, a situation of high interest for mmWave and terahertz frequencies.

Information theory, starting with Shannon’s groundbreaking work, has fundamentally shaped the way communication systems are designed and operated. Information theoretic principles form the underpinnings of modern communication networks. This issue explores how new advances in information theory can impact future communication systems. Several papers address issues at the heart of next generation w...

The majority of stochastic channel models rely on the electromagnetic far-field assumption, which allows to decompose the channel in terms of plane waves. The far-field assumption breaks down in future applications that push towards the electromagnetic near-field region, such as those where the use of electromagnetically large antenna arrays is envisioned. Motivated by this consideration, we show how physical principles can be used to derive a plane-wave scalar channel model that is also valid in the reactive near-field region. Precisely, we show that narrowband wave propagation through a three-dimensional scattered medium can be generally modeled as a linear and space-variant system. We first review the physics principles that lead to a closed-form deterministic plane-wave representation of the channel impulse response. This serves as a basis for deriving a stochastic representation of the channel in terms of statistically independent Gaussian random coefficients for spatially stationary random propagation environments. The very desirable property of spatial stationarity can always be retained in the radiative near-field region by excluding reactive propagation mechanisms confined in close proximity to the source. Remarkably, the provided stochastic representation is directly connected to the Fourier spectral representation of a general stationary spatial random field.

In most multiple-input multiple-output (MIMO) communication systems, e.g., Massive MIMO, the antenna spacing is generally no less than half a wavelength. It helps to reduce the mutual coupling and therefore facilitate the system design. The maximum array gain is the number of antennas in this settings. However, when the antenna spacing is made very small, the array gain of a compact array can be proportional to the square of the number of antennas - a value much larger than the traditional array. To achieve this so-called "superdirectivity" however, the calculation of the excitation coefficients (beamforming vector) is known to be a challenging problem. In this paper, we derive the beamforming vector of superdirective arrays based on a novel coupling matrix-enabled method. We also propose an approach to obtain the coupling matrix, which is derived by the spherical wave expansion method and active element pattern. The full-wave electromagnetic simulations are conducted to validate the effectiveness of our proposed method. Simulation results show that when the beamforming vector obtained by our method is applied, the directivity of the designed dipole antenna array has a good agreement with the theoretical values.

Imagine a MIMO communication system that fully exploits the propagation characteristics offered by an electromagnetic channel and ultimately approaches the limits imposed by wireless communications. This is the concept of Holographic MIMO communications. Accurate and tractable channel modeling is critical to understanding its full potential. Classical stochastic models used by communications theorists are derived under the electromagnetic far-field assumption, i.e. planar wave approximation over the array. However, such assumption breaks down when electromagnetically large (compared to the wavelength) antenna arrays are considered. In this paper, we start from the first principles of wave propagation and provide a Fourier plane-wave series expansion of the channel response, which fully captures the essence of electromagnetic propagation in arbitrary scattering and is also valid in the (radiative) near-field. The expansion is based on the Fourier spectral representation and has an intuitive physical interpretation, as it statistically describes the angular coupling between source and receiver. When discretized uniformly, it leads to a low-rank semi-unitarily equivalent approximation of the electromagnetic channel in the angular domain. The developed channel model is used to compute the ergodic capacity of a point-to-point Holographic MIMO system with different degrees of channel state information.

A resonant electromagnetic cavity - effectively the interior of a copper box - constitutes a highly favorable propagation environment for MIMO communications. A fundamental limitation on wireless communication within the box is thermal noise. Under conditions of thermal equilibrium the Equipartition Theorem of classical statistical mechanics states that every orthogonal normal mode has an independent random amplitude such that the expected energies of the modes are equal and proportional to absolute temperature. Collectively the randomly excited modes constitute a space-time stochastic process, stationary in time but non-stationary in space because of boundary conditions. As the linear dimensions of the box grow relative to a wavelength the process is asymptotically stationary. At each temporal frequency the wavenumber spectral density is identical to that of the Clarke model - a superposition of random plane waves having no preferred direction of propagation. At a single point in space the spectral density is proportional to the square of temporal frequency - the Rayleigh-Jeans spectrum. We call our space-time noise model Rayleigh-Jeans-Clarke (RJC).

We provide a deterministic channel model for a scenario where wireless connectivity is established through a reflection from a planar smooth surface of an infinite extent. The developed model is rigorously built upon the physics of wave propagation, and is as precise as tight are the unboundedness and smoothness assumptions on the surface. This model allows establishing that line-of-sight spatial multiplexing can take place via reflection off an electrically large surface, a situation of high interest for mmWave and terahertz frequencies.

A signal space approach is presented to study the Nyquist sampling, number of degrees of freedom and reconstruction of an electromagnetic field under arbitrary scattering conditions. Conventional signal processing tools, such as the multidimensional sampling theorem and Fourier theory, are used to provide a linear system theoretic interpretation of electromagnetic wave propagation, thereby revealing the spatially bandlimited nature of electromagnetic fields. Their spatial bandwidth is dictated by the selectivity of the underlying scattering that allows establishing the Nyquist spatial sampling with a reduction of the number of fields' samples needed to be processed.

While the heat equation has been extensively studied, heat conduction has not been studied as a means of communication until recently. Recent literature focusing on covert channels shows the feasibility of using thermal conduction to communicate information. Since heat conduction is modelled by a linear partial differential equation, it can be analyzed as a linear system with an input heat source and output temperature distribution. The magnitude of the thermal channel's frequency response is an exponentially decaying function of frequency. The thermal channel's capacity increases when the total power increases, similar to typical communication based on electromagnetic waves. Uniquely however, the thermal channel's effective bandwidth is constrained by the total power since a water-filling algorithm determines a cutoff frequency. Additionally, the quadratic nature of the heat equation presents a novel quadratic scaling of the channel capacity. Scaling space by a factor of 2 and time by 4 improves the channel capacity by a factor of 4. This implies that scaling space down from centimeter to micrometer domain improves the channel capacity by a factor of 10 8 • The thermal channel presents various novel qualities and a possible exciting application for intra-chip communication.

Imagine a MIMO communication system that fully exploits the propagation characteristics offered by an electromagnetic channel and ultimately approaches the limits imposed by wireless communications. This is the concept of Holographic MIMO communications. Accurate and tractable channel modeling is critical to understanding its full potential. Classical stochastic models used by communications theorists are derived under the electromagnetic far-field assumption. However, such assumption breaks down when large (compared to the wavelength) antenna arrays are considered - as envisioned in future wireless communications. In this paper, we start from the first principles of wave propagation and provide a Fourier plane-wave series expansion of the channel response, which fully captures the essence of electromagnetic propagation in arbitrary scattering and is also valid in the (radiative) near-field. The expansion is based on the Fourier spectral representation and has an intuitive physical interpretation, as it statistically describes the angular coupling between source and receiver. When discretized, it leads to a low-rank semi-unitarily equivalent approximation of the spatial electromagnetic channel in the angular domain. The developed channel model is used to compute the ergodic capacity of a Holographic MIMO system with different degrees of channel state information.

Communications at mm-wave frequencies and above rely heavily on beamforming antenna arrays. Typically, hundreds, if not thousands, of independent antenna channels are used to achieve high SNR for throughput and increased capacity. Using a dedicated ADC per antenna receiver is preferable but it’s not practical for very large arrays due to unreasonable cost and complexity. Frequency division multiplexing (FDM) is a well-known technique for combining multiple signals into a single wideband channel. In a first of its kind measurements, this paper explores FDM for combining multiple antenna outputs at IF into a single wideband signal that can be sampled and digitized using a high-speed wideband ADC. The sampled signals are sub-band filtered and digitally down-converted to obtain individual antenna channels. A prototype receiver was realized with a uniform linear array consisting of 4 elements with 250 MHz bandwidth per channel at 28 GHz carrier frequency. Each of the receiver chains were frequency-multiplexed at an intermediate frequency of 1 GHz to avoid the requirement for multiple, precise local oscillators (LOs). Combined narrowband receiver outputs were sampled using a single ADC with digital front-end operating on a Xilinx ZCU-1285 RF SoC FPGA to synthesize 4 digital beams. The approach allows $M$ -fold increase in spatial degrees of freedom per ADC, for temporal oversampling by a factor of $M$ .

This paper proposes a communication model for multiuser multiple-input multiple-output (MIMO) systems based on large intelligent surfaces (LIS), where the LIS is modeled as a collection of tightly packed antenna elements. The LIS system is first represented in a circuital way, obtaining expressions for the radiated and received powers, as well as for the coupling between the distinct elements. Then, this circuital model is used to characterize the channel in a line-of-sight propagation scenario, rendering the basis for the analysis and design of MIMO systems. Due to the particular properties of LIS, the model accounts for superdirectivity and mutual coupling effects along with near field propagation, necessary in those situations where the array dimension becomes very large. Finally, with the proposed model, the matched filter transmitter and the weighted minimum mean square error precoding are derived under both realistic constraints: limited radiated power and maximum ohmic losses.

Non-cooperative cellular massive MIMO, combined with power control, is known to lead to significant improvements in per-user throughput compared with conventional LTE technology. In this paper, we investigate further refinements to massive MIMO, first, in the form of three-fold sectorization, and second, coordinated multi-point operation (with and without sectorization), in which the three base stations cooperate in the joint service of their users. For these scenarios, we analyze the downlink performance for both maximum-ratio and zero-forcing precoding and derive closed-form lower-bound expressions on the achievable rate of the users. These expressions are then used to formulate power optimization problems with two throughput fairness criteria: i) network-wide max-min fairness, and ii) per-cell max-min fairness. Furthermore, we provide centralized and decentralized power control strategies to optimize the transmit powers in the network. We demonstrate that employing sectorized antenna elements mitigates the detrimental effects of pilot contamination by rejecting a portion of interfering pilots in the spatial domain during channel estimation phase. Simulation results with practical sectorized antennas reveal that sectorization and multi-point coordination combined with sectorization lead to more than 1.7x and 2.6x improvements in the 95%-likely per-user throughput, respectively.

Communication systems of the future will require hundreds of independent spatial channels achieved through dense antenna arrays connected to digital signal processing software defined radios. The cost and complexity of data converters are a significant concern with systems having hundreds of antennas. This paper explores frequency division multiplexing as an approach for augmenting the baseband signals of multiple antenna channels such that a single ADC can sample a multitude of antennas in an array. The approach is equally applicable to both massive MIMO and mm-wave digital wireless arrays. An example design based on Xilinx RF SoC for combining 4 antenna channels at 28 GHz into a single ADC is provided.

This paper proposes an adaptive large scale antenna system (ALSAS) for enhancing energy efficiency in low density wireless network scenarios. The proposed ALSAS comprises of two stages, a novel adaptive discontinuous transmission (ADTx) stage and an antenna array optimization (AAO) one. The basic idea is to utilize prior knowledge of the users' quality of service (QoS) requirements as well as precoding selection in the ADTx stage to maximize the transmitter hibernation periods subject to a certain complexity constraint. In the AAO stage, further power saving is achieved by reducing the number of active antenna elements subject to a certain QoS requirement. It is shown that, relative to conventional large scale antenna system (LSAS), the proposed ALSAS system achieves significant energy efficiency improvements under various scenarios. The results show that the proposed technique can provide energy efficiency improvement between 125% and 1124% in the suburban scenario, and between 196% and 952% in the rural scenario. It is also demonstrated that for rural environments with relatively small short inter-site-distance (ISD) values, ALSAS can provide up to 500% power saving for the fixed bit rate requirement case.

Holographic MIMO is a spatially-constrained MIMO system with a massive number of antennas, possibly thought of, in its ultimate form, as a spatially-continuous electromagnetic aperture. Accurate and tractable channel modeling is critical to understanding the full potential of this technology. This paper considers arbitrary spatially-stationary scattering and provides a 4D plane-wave representation in Cartesian coordinates, which captures the essence of electromagnetic propagation and allows to evaluate the capacity of Holographic MIMO systems with rectangular volumetric arrays. The developed framework generalizes the virtual channel representation, which was originally developed for uniform linear arrays.

Imagine an array with a massive (possibly uncountably infinite) number of antennas in a compact space. We refer to a system of this sort as Holographic MIMO. Given the impressive properties of Massive MIMO, one might expect a holographic array to realize extreme spatial resolution, incredible energy efficiency, and unprecedented spectral efficiency. At present, however, its fundamental limits have not been conclusively established. A major challenge for the analysis and understanding of such a paradigm shift is the lack of mathematically tractable and numerically reproducible channel models that retain some semblance to the physical reality. Detailed physical models are, in general, too complex for tractable analysis. This paper aims to take a closer look at this interdisciplinary challenge. Particularly, we consider the small-scale fading in the far-field, and we model it as a zero-mean, spatially-stationary, and correlated Gaussian scalar random field. Physically-meaningful correlation is obtained by requiring that the random field be consistent with the scalar Helmholtz equation. This formulation leads directly to a rather simple and exact description of the three-dimensional small-scale fading as a Fourier plane-wave spectral representation. Suitably discretized, this leads to a discrete representation for the field as a Fourier plane-wave series expansion, from which a computationally efficient way to generate samples of the small-scale fading over spatially-constrained compact spaces is developed. The connections with the conventional tools of linear systems theory and Fourier transform are thoroughly discussed.