Dynamic metasurface antennas (DMAs) are leaky-wave antennas with frequency-reconfigurable slots. While resonant frequency of individual slots on the DMA can be independently configured in a wide frequency range, the DMA’s beamforming performance across different operating frequencies in the available range has not been studied yet. We show that the dominant beam direction and the operating frequency of a DMA are interdependent. Using this observation, we derive a closed-form expression for line-of-sight (LOS) beamforming gain maximization to jointly configure the operating frequency and per-slot resonant frequency configuration of the DMA. A benefit of this approach in the LOS channel case is that all slots are tuned to the same resonant frequency, eliminating the need for a computationally expensive search across all feasible resonant frequency configurations. We also apply this approach to mitigate beam training overhead in large arrays by proposing a single-shot beam training algorithm that estimates the optimal resonant frequency configuration through simultaneous probing of multiple angular directions across frequencies. Simulation results show that our proposed approach offers a comparable achievable rate to true-time-delay (TTD) based systems, but with lower power consumption and hardware cost.

Dynamic metasurface antennas (DMA) provide low-power beamforming through reconfigurable radiative slots. Each slot has a tunable component that consumes low power compared to typical analog components like phase shifters. This makes DMAs a potential candidate to minimize the power consumption of multiple-input multiple-output (MIMO) antenna arrays. In this paper, we investigate the use of DMAs in a wideband communication setting with practical DMA design characteristics. We develop approximations for the DMA beamforming gain that account for the effects of waveguide attenuation, element frequency-selectivity, and limited reconfigurability of the tunable components as a function of the signal bandwidth. The approximations allow for key insights into the wideband performance of DMAs in terms of different design variables. We develop a simple successive beamforming algorithm to improve the wideband performance of DMAs by sequentially configuring each DMA element. Simulation results for a line-of-sight (LOS) wideband system show the accuracy of the approximations with the simulated DMA model in terms of spectral efficiency. We also find that the proposed successive beamforming algorithm increases the overall spectral efficiency of the DMA-based wideband system compared with a baseline DMA beamforming method.

A parasitic reconfigurable antenna array is a low-power approach for beamforming using passive tunable elements. Prior work on reconfigurable antennas in communication theory is based on ideal radiation pattern abstractions. Beamforming with parasitic elements is inherently difficult because mutual coupling creates non-linearity in the beamforming gain objective. We develop a multi-port circuit-theoretic model of the hybrid array with parasitic elements and antennas with active RF chain validated through electromagnetic simulations with a dipole array. Based on this formulation, we derive the beamforming weight of the parasitic element using the theoretical beam pattern expression for the case of a single active antenna and multiple parasitic elements. The analysis shows that the parasitic beamforming is challenging because the weights are subject to coupled magnitude and phase constraints. To overcome this, a shift-of-origin transformation simplifies the optimization, leading to a closed-form expression for the parasitic reactance. The solution generalizes to arrays with multiple active and parasitic elements operating in multipath channels. The proposed hybrid architecture with parasitic elements outperforms conventional architectures in terms of energy efficiency.

A dynamic metasurface antenna (DMA) is a slottedwaveguide antenna with tunable components that allow for beamforming with low power consumption. The resonant frequencies of the individual DMA slot elements are reconfigurable, which can be leveraged for wideband communications to support larger bandwidths. The vast majority of prior work on DMAs focuses on narrowband applications for DMAs. In this paper, we develop a beamforming algorithm to improve the performance of a multicarrier DMA-based wireless system with large signal bandwidths. We build upon prior DMA signal models to incorporate different frequency-selective aspects of the physical DMA elements, and investigate the impact of different DMA designs on wideband performance. We find that the proposed beamforming algorithm outperforms a baseline beamforming algorithm in terms of spectral efficiency and data rates under significant frequencyselectivity in the multi-carrier channel and DMA elements.

Dynamic metasurface antennas (DMAs) enable beamforming through low-power components that reconfigure each radiating element. Previous studies on a single user multiple-input-single-output (MISO) system with transmit DMA focused on maximizing beamforming gain in narrowband scenarios. In this paper, we analyze the beamforming performance of DMAs in wideband scenarios. By leveraging DMA's frequency reconfigurability, our proposed approach dynamically adjusts both the transmission frequency and element configuration, achieving a higher beamforming gain than the narrowband method. We also propose the optimal waveguide refractive index and DMA element spacing to obtain an equal beamforming gain as the power hungry true-time-delay (TTD) architecture in the desired angular range. We evaluate the achievable rate performance and show that the rate approaches that of TTD when the DMA tuning range increases.

Impedance-matching networks affect power transfer from the radio frequency (RF) chains to the antennas. Their design impacts the signal to noise ratio (SNR) and the achievable rate. In this paper, we maximize the information-theoretic achievable rate of a multiple-input-single-output (MISO) system with wideband matching constraints. Using a multiport circuit theory approach with frequency-selective scattering parameters, we propose a general framework for optimizing the MISO achievable rate that incorporates Bode-Fano wideband matching theory. We express the solution to the achievable rate optimization problem in terms of the optimized transmission coefficient and the Lagrangian parameters corresponding to the Bode-Fano inequality constraints. We apply this framework to a single electric Chu’s antenna and an array of dipole antennas. We compare the optimized achievable rate obtained numerically with other benchmarks like the ideal achievable rate computed by disregarding matching constraints and the achievable rate obtained by using sub-optimal matching strategies like conjugate matching and frequency-flat transmission. We also propose a practical methodology to approximate the achievable rate bound by using the optimal transmission coefficient to derive a physically realizable matching network through the ADS software.

Conventional achievable rate analysis using Shannon's theory does not assume practical constraints imposed by Bode-Fano wideband matching theory. This leads to an achievable rate bound that cannot be attained by practical matching networks. In this paper, we generalize the information-theoretic achievable rate of a single-input-single-output (SISO) system by incorporating wideband matching constraints at the transmitter. We express the solution to the achievable rate optimization problem in terms of the optimized transmission coefficient and the Lagrangian parameters corresponding to the Bode-Fano inequality constraints. We also propose a practical strategy to design a physically realizable matching network through the ADS software which attains the achievable rate bound with near-optimality. In simulations, we apply this framework to a Chu's antenna and compare the achievable rate performance with the conventional conjugate matching strategy.

We consider a two-way full-duplex (FD) system where a massive multi-input-multi-output FD base station (BS) communicates with multiple FD users via an intelligent reflecting surface (IRS). We derive a closed-form network spectral efficiency lower bound by considering spatial correlation at the BS and IRS. We demonstrate the importance of modelling spatial correlation by simplifying this lower bound for uncorrelated channels to show that the IRS capability to modify the wireless medium now is significantly impeded. This lower bound, which is a function of only the long-term channel statistics, is also used to maximize the non-concave global energy efficiency metric by optimally allocating the transmit powers, and by designing the IRS phases. We derive closed-form updates for optimizing the transmit powers using Lagrangian dual, Quadratic, and Dinkelbach’s transforms. We then optimize the IRS phases by using the projected gradient ascent algorithm. We numerically show that increasing the number of IRS elements can help a FD mMIMO BS outperform its half-duplex counterpart, which otherwise under-performs due to its limited ability to cancel various FD interferences.

We consider a multi-user system where a massive multi-input-multi-output (mMIMO) full-duplex (FD) base-station (BS) communicates with multiple FD users via an intelligent reflecting surface (IRS). We derive novel uplink and downlink spectral efficiency (SE) lower bound expressions when the BS estimates composite BS-IRS-user channels. The lower bounds are derived considering spatially-correlated IRS and user channels, and require only statistical channel state information (CSI). We propose a projected gradient ascent based IRS phase optimization algorithm, which also uses only statistical CSI, and enables the system to achieve a higher SE in the presence of the loop and inter-user interferences. We analytically investigate the dependence of SE on the IRS phase for spatially correlated channels considered herein. We show that the proposed analysis can help in increasing the SE by appropriate IRS placement.