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Register a new userDynamic Metasurface Antennas for Energy Efficient Massive MIMO Uplink Communications
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Future wireless communications are largely inclined to deploy a massive number of antennas at the base stations (BS) by exploiting energy-efficient and environmentally friendly technologies. An emerging technology called dynamic metasurface antennas (DMAs) is promising to realize such massive antenna arrays with reduced physical size, hardware cost, and power consumption. This paper aims to optimize the energy efficiency (EE) performance of DMAs-assisted massive MIMO uplink communications. We propose an algorithmic framework for designing the transmit precoding of each multi-antenna user and the DMAs tuning strategy at the BS to maximize the EE performance, considering the availability of the instantaneous and statistical channel state information (CSI), respectively. Specifically, the proposed framework includes Dinkelbachs transform, alternating optimization, and deterministic equivalent methods. In addition, we obtain a closed-form solution to the optimal transmit signal directions for the statistical CSI case, which simplifies the corresponding transmission design. The numerical results show good convergence performance of our proposed algorithms as well as considerable EE performance gains of the DMAs-assisted massive MIMO uplink communications over the baseline schemes.
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Next generation wireless base stations and access points will transmit and receive using extremely massive numbers of antennas. A promising technology for realizing such massive arrays in a dynamically controllable and scalable manner with reduced cost and power consumption utilizes surfaces of radiating metamaterial elements, known as metasurfaces. To date, metasurfaces are mainly considered in the context of wireless communications as passive reflecting devices, aiding conventional transceivers in shaping the propagation environment. This article presents an alternative application of metasurfaces for wireless communications as active reconfigurable antennas with advanced analog signal processing capabilities for next generation transceivers. We review the main characteristics of metasurfaces used for radiation and reception, and analyze their main advantages as well as their effect on the ability to reliably communicate in wireless networks. As current studies unveil only a portion of the potential of metasurfaces, we detail a list of exciting research and implementation challenges which arise from the application of metasurface antennas for wireless transceivers.
We propose an uplink massive MIMO system using an array of holographic metasurfaces as a sector antenna. The antenna consists of a set of rectangular waveguide-fed metasurfaces combined along the elevation direction into a planar aperture, each with subwavelength-sized metamaterial elements as radiators. The metamaterial radiators are designed such that the waveguide-fed metasurface implements a holographic solution for the guided (or reference) mode, generating a fan beam towards a prescribed direction, thereby forming a multibeam antenna system. We demonstrate that a narrowband uplink massive MIMO system using the metasurfaces can achieve the sum capacity close to that offered by the Rayleigh channel at 3.5 GHz. We show that metasurfaces supporting multiple fan beams can achieve high spatial resolution in the azimuth directions in sub-6 GHz channels, and thereby form uncorrelated MIMO channels between the base station and users. Also, the proposed metasurface antenna is structurally simple, low-cost, and efficient, and thus is suitable to alleviate RF hardware issues common to massive MIMO systems equipped with a large antenna system.
User electromagnetic (EM) exposure is continuously being exacerbated by the evolution of multi-antenna portable devices. To mitigate the effects of EM radiation, portable devices must satisfy tight regulations on user exposure level, generally measured by specific absorption rate (SAR). To this end, we investigate the SAR-aware uplink precoder design for the energy efficiency (EE) maximization in multiuser multiple-input multiple-output transmission exploiting statistical channel state information (CSI). As the objective function of the design problem is computationally demanding in the absence of closed form, we present an asymptotic approximation of the objective to facilitate the precoder design. An iterative algorithm based on Dinkelbachs method and sequential optimization is proposed to obtain an optimal solution of the asymptotic EE optimization problem. Based on the transformed problem, an iterative SAR-aware water-filing scheme is further conceived for the EE optimization precoding design with statistical CSI. Numerical results illustrate substantial performance improvements provided by our proposed SAR-aware energy-efficient transmission scheme over the traditional baseline schemes.
In a practical massive MIMO (multiple-input multiple-output) system, the number of antennas at a base station (BS) is constrained by the space and cost factors, which limits the throughput gain promised by theoretical analysis. This paper thus studies the feasibility of adopting the intelligent reflecting surface (IRS) to further improve the beamforming gain of the uplink communications in a massive MIMO system. Under such a novel system, the central question lies in whether the IRS is able to enhance the network throughput as expected, if the channel estimation overhead is taken into account. In this paper, we first show that the favorable propagation property for the conventional massive MIMO system without IRS, i.e., the channels of arbitrary two users are orthogonal, no longer holds for the IRS-assisted massive MIMO system, due to its special channel property that each IRS element reflects the signals from all the users to the BS via the same channel. As a result, the maximal-ratio combining (MRC) receive beamforming strategy leads to strong inter-user interference and thus even lower user rates than those of the massive MIMO system without IRS. To tackle this challenge, we propose a novel strategy for zero-forcing (ZF) beamforming design at the BS and reflection coefficients design at the IRS to efficiently null the inter-user interference. Under our proposed strategy, it is rigorously shown that even if the channel estimation overhead is considered, the IRS-assisted massive MIMO system can always achieve higher throughput compared to its counterpart without IRS, despite the fact that the favorable propagation property no longer holds.
Terahertz (THz) communications with a frequency band 0.1-10 THz are envisioned as a promising solution to the future high-speed wireless communication. Although with tens of gigahertz available bandwidth, THz signals suffer from severe free-spreading loss and molecular-absorption loss, which limit the wireless transmission distance. To compensate the propagation loss, the ultra-massive multiple-input-multiple-output (UM-MIMO) can be applied to generate a high-gain directional beam by beamforming technologies. In this paper, a tutorial on the beamforming technologies for THz UM-MIMO systems is provided. Specifically, we first present the system model of THz UM-MIMO and identify its channel parameters and architecture types. Then, we illustrate the basic principles of beamforming via UM-MIMO and introduce the schemes of beam training and beamspace MIMO for THz communications. Moreover, the spatial-wideband effect and frequency-wideband effect in the THz beamforming are discussed. The joint beamforming technologies in the intelligent-reflecting-surface (IRS)-assisted THz UM-MIMO systems are introduced. Further, we present the corresponding fabrication techniques and illuminate the emerging applications benefiting from THz beamforming. Open challenges and future research directions on THz UM-MIMO systems are finally highlighted.
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