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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., Comment: Submitted to Proceedings of the IEEE, 36 pages, 23 figures

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 two electric Chu's 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.

The narrowband and far-field assumption in conventional wireless system design leads to a mismatch with the optimal beamforming required for wideband and near-field systems. This discrepancy is exacerbated for larger apertures and bandwidths. To characterize the behavior of near-field and wideband systems, we derive the beamforming gain expression achieved by a frequency-flat phased array designed for plane-wave propagation. To determine the far-field to near-field boundary for a wideband system, we propose a frequency-selective distance metric. The proposed far-field threshold increases for frequencies away from the center frequency. The analysis results in a fundamental upper bound on the product of the array aperture and the system bandwidth. We present numerical results to illustrate how the gain threshold affects the maximum usable bandwidth for the n260 and n261 5G NR bands.

The focus of this paper is on multi-user MIMO transmissions for millimeter wave systems with a hybrid precoding architecture at the base-station. To enable multi-user transmissions, the base-station uses a cell-specific codebook of beamforming vectors over an initial beam alignment phase. Each user uses a user-specific codebook of beamforming vectors to learn the top-P (where P >= 1) beam pairs in terms of the observed SNR in a single-user setting. The top-P beam indices along with their SNRs are fed back from each user and the base-station leverages this information to generate beam weights for simultaneous transmissions. A typical method to generate the beam weights is to use only the best beam for each user and either steer energy along this beam, or to utilize this information to reduce multi-user interference. The other beams are used as fall back options to address blockage or mobility. Such an approach completely discards information learned about the channel condition(s) even though each user feeds back this information. With this background, this work develops an advanced directional precoding structure for simultaneous transmissions at the cost of an additional marginal feedback overhead. This construction relies on three main innovations: 1) Additional feedback to allow the base-station to reconstruct a rank-P approximation of the channel matrix between it and each user, 2) A zeroforcing structure that leverages this information to combat multi-user interference by remaining agnostic of the receiver beam knowledge in the precoder design, and 3) A hybrid precoding architecture that allows both amplitude and phase control at low-complexity and cost to allow the implementation of the zeroforcing structure. Numerical studies show that the proposed scheme results in a significant sum rate performance improvement over naive schemes even with a coarse initial beam alignment codebook., Comment: 32 pages, 6 figures