Analysis of a Waveguide-Fed Metasurface Antenna

Dicker²,

Eldar

et al. 2019

IEEE Trans. Commun.

Self Cite

123

117

Massive multiple-input multiple-output (MIMO) communications are the focus of considerable interest in recent years. While the theoretical gains of massive MIMO have been established, implementing MIMO systems with large-scale antenna arrays in practice is challenging. Among the practical challenges associated with massive MIMO systems are increased cost, power consumption, and physical size. In this work we study the implementation of massive MIMO antenna arrays using dynamic metasurface antennas (DMAs), an emerging technology which inherently handles the aforementioned challenges. Specifically, DMAs realize large-scale planar antenna arrays, and can adaptively incorporate signal processing methods such as compression and analog combining in the physical antenna structure, thus reducing the cost and power consumption. We first propose a mathematical model for massive MIMO systems with DMAs and discuss their constraints compared to ideal antenna arrays. Then, we characterize the fundamental limits of uplink communications with the resulting systems, and propose two algorithms for designing practical DMAs for approaching these limits. Our numerical results indicate that the proposed approaches result in practical massive MIMO systems whose performance is comparable to that achievable with ideal antenna arrays.

Section: A Dynamic Metasurface Antennasmentioning

confidence: 99%

Section: A Dynamic Metasurface Antennasmentioning

confidence: 99%

Dynamic Metasurface Antennas for Uplink Massive MIMO Systems

Dicker²,

Eldar

et al. 2019

IEEE Trans. Commun.

Self Cite

123

117

“…P1 Each element acts as resonant electrical circuit, whose frequency response is described by the Lorentzian form [15], [16]:…”

Section: A Dynamic Metasurface Antennasmentioning

confidence: 99%

“…Here, we study uplink MU-MIMO-OFDM communications in which a bit-constrained BS is equipped with a DMA. We first extend the model formulated in [24], which was built upon approximations of the DMA properties proposed in [15] that hold for narrowband signals, to faithfully capture the reconfigurable frequency selective nature of DMAs in wideband setups, such as OFDM systems. Then, we show how the resulting DMA characteristics can be incorporated into the MU-MIMO-OFDM model, resulting in a form of a hybrid receiver.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Metasurface Antennas for Bit-Constrained MIMO-OFDM Receivers

Wang

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Jin

et al. 2020

Self Cite

The combination of orthogonal frequency modulation (OFDM) and multiple-input multiple-output (MIMO) systems plays an important role in modern communication systems. In order to meet the growing throughput demands, future MIMO-OFDM receivers are expected to utilize a massive number of antennas, operate in dynamic environments, and explore high frequency bands, while satisfying strict constraints in terms of cost, power, and size. An emerging technology to realize massive MIMO receivers of reduced cost and power consumption is based on dynamic metasurface antennas (DMAs), which inherently implement controllable compression in acquisition. In this work we study the application of DMAs for MIMO-OFDM receivers operating with bit-constrained analog-to-digital converters (ADCs). We present a model for DMAs which accounts for the configurable frequency selective profile of its metamaterial elements, resulting in a spectrally flexible hybrid structure. We then exploit previous results in task-based quantization to show how DMAs can be configured to improve recovery in the presence of constrained ADCs, and propose methods for adjusting the DMA parameters based on channel state information. Our numerical results demonstrate that the DMA-based receiver is capable of accurately recovering OFDM signals. In particular, we show that by properly exploiting the spectral diversity of DMAs, notable performance gains are obtained over existing designs of conventional hybrid architectures, demonstrating the potential of DMAs for MIMO-OFDM setups in realizing high performance massive antenna arrays of reduced cost and power consumption.

“…In particular, DMAs consist of a set of microstrips, each embedded with configurable radiating metamaterial elements [39]. When used as a receive antenna, the signals observed by the elements are captured at a single output port for each microstrip, feeding an ADC.…”

Section: B Analog Combining Via Dynamic Metasurface Antennasmentioning

confidence: 99%

Asymptotic Task-Based Quantization With Application to Massive MIMO

IEEE Trans. Signal Process.

Eldar

Rodrigues

2019

Multiple-input multiple-output (MIMO) systems are required to communicate reliably at high spectral bands using a large number of antennas, while operating under strict power and cost constraints.In order to meet these constraints, future MIMO receivers are expected to operate with low resolution quantizers, namely, utilize a limited number of bits for representing their observed measurements, inherently distorting the digital representation of the acquired signals. The fact that MIMO receivers use their measurements for some task, such as symbol detection and channel estimation, other than recovering the underlying analog signal, indicates that the distortion induced by bit-constrained quantization can be reduced by designing the acquisition scheme in light of the system task, i.e., by task-based quantization.In this work we survey the theory and design approaches to task-based quantization, presenting modelaware designs as well as data-driven implementations. Then, we show how one can implement a task-based bit-constrained MIMO receiver, presenting approaches ranging from conventional hybrid receiver architectures to structures exploiting the dynamic nature of metasurface antennas. This survey narrows the gap between theoretical task-based quantization and its implementation in practice, providing concrete algorithmic and hardware design principles for realizing task-based MIMO receivers. N. Shlezinger and Y. C. Eldar are with the Faculty of Math and CS, the number of BS antennas grow arbitrarily large [1], [2]. An additional method to increase the network throughput is to explore the millimeter wave (mmWave) frequency range [3], thus overcoming the spectral congestion of traditional wireless bands. Such mmWave communications is particularly suitable for massive MIMO systems: The short wavelengths of mmWave signals allows packing a large number of antenna elements at a small physical size, and the massive number of elements facilitates directed beamforming which is essential at mmWave bands. While the theoretical gains of massive MIMO systems, particularly when combined with mmWave transmission, are clear, implementing such systems in practice under strict cost and power constraints is a challenging task. A major source of this increased cost are the analog-todigital convertor (ADC) components, which allow the analog signals observed by each antenna element to be processed in digital. The power consumption of an ADC is directly related to the signal bandwidth and the number of bits used for digital representation [4], [5]. Consequently, in massive MIMO systems, where the number of antennas and ADCs operating at high frequency bands is large, limiting the number of bits, thus operating under quantization constraints, is crucial to keep cost and power consumption feasible [3].Focusing on uplink communications, i.e., when the BS acts as the receiver, quantization constraints imply that the BS cannot process the channel output directly but rather only an inaccurate distorted digital representation of it. The distor...