Energy Efficient Multi-User MISO Communication Using Low Resolution Large Intelligent Surfaces

By Chongwen Huang, George C. Alexandropoulos, Alessio Zappone, Merouane Debbah, Chau Yuen. 2018 IEEE Globecom Workshops (GC Wkshps), 2018

309 citations recorded by the source corpus.

We consider a multi-user Multiple-Input Single-Output (MISO) communication system comprising of a multiantenna base station communicating in the downlink simultaneously with multiple single-antenna mobile users. This communication is assumed to be assisted by a Large Intelligent Surface (LIS) that consists of many nearly passive antenna elements, whose parameters can be tuned according to desired objectives. The latest design advances on these surfaces suggest cheap elements effectively acting as low resolution (even 1-bit resolution) phase shifters, whose joint configuration affects the electromagnetic behavior of the wireless propagation channel. In this paper, we investigate the suitability of LIS for green communications in terms of Energy Efficiency (EE), which is expressed as the number of bits per Joule. In particular, for the considered multi-user MISO system, we design the transmit powers per user and the values for the surface elements that jointly maximize the system's EE performance. Our representative simulation results show that LIS-assisted communication, even with nearly passive 1-bit resolution antenna elements, provides significant EE gains compared to conventional relay-assisted communication.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/f2c02359e0cd01efec6ddeec691f19eab50d539e

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Citations in the corpus

Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication (2018, background): “Among the candidate transceiver approaches [15]–[18] for green communication, a recent emerging hardware technology with increased potential for signiﬁcant energy consumption reductions is the so-called reconﬁgurable intelligent surface (RIS) [14], [19]–[23].”
Wireless Communications With Reconfigurable Intelligent Surface: Path Loss Modeling and Experimental Measurement (2019, methodology): “The energy efficiency of RIS-based downlink multi-user MISO systems was maximized in [26], [27].”
Communication Through a Large Reflecting Surface With Phase Errors (2019, methodology): “In [10], [11], the LRS-based system is optimized over lowresolution phase shifts.”
Reconfigurable Intelligent Surface Aided NOMA Networks (2019, methodology): “The associated energy consumption model was proposed in [17], [18], where the EE of the proposed network was optimized.”
Reconfigurable Intelligent Surfaces for Wireless Communications: Principles, Challenges, and Opportunities (2020, background): “The same approach is generalized to accommodate energy efficiency maximization in [44].”
Asymptotic Max-Min SINR Analysis of Reconfigurable Intelligent Surface Assisted MISO Systems (2019, background): “The works in [3], [4] proposed designs for both the transmit power allocation at the BS and the phases induced by the RIS elements to maximize either the energy or the spectral efficiency of an RIS-assisted multi-user MISO system, that employs zeroforcing precoding and models the RIS-assisted links ”
Secrecy Rate Maximization for Intelligent Reflecting Surface Assisted Multi-Antenna Communications (2019, background): “The problem is quite challenging even when the eavesdropper has a single antenna, which cannot be straightforwardly solved with the techniques developed in [9]–[14].”
Joint Active and Passive Beamforming Optimization for Intelligent Reflecting Surface Assisted SWIPT Under QoS Constraints (2019, methodology): “Furthermore, from the optimization perspective, the prior works (e.g., [9]–[14], [16], [21], [24], [25]) all adopted an alternating optimization approach by successively optimizing the transmit precoders and the IRS’s phase shifts in an iterative manner, which, however, becomes highly inefﬁcient as…”
Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey (2019, background): “A special case with the 1-bit phase resolution is studied in [157].”
An Interpretable Neural Network for Configuring Programmable Wireless Environments (2019, background): “Such materials have also been recently generalized under the term intelligent surfaces [4]–[7], to denote their end-facility while abstracting the underlying physicallayer technology specifics.”
Iterative Channel Estimation Using LSE and Sparse Message Passing for MmWave MIMO Systems (2016, methodology): “These properties make the lens a practical and energy efficiency tool for implementing the RF frontend in beamforming systems [6], [45]–[47].”
Intelligent Reflecting Surface: A Programmable Wireless Environment for Physical Layer Security (2019, background): “As for a downlink multi-user MISO system [21]–[23], the spectrum-/ energy-efficiency problem under the individual signalto-interference-plus-noise ratio (SINR) constraints was investigated in [21] and [22] considering continuous or discrete reflecting coefficients on the reflecting elements.”
A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future (2020, background): “For instance, several recent studies indicate that the capacity achieved through RSS is comparable to the one achieved through radio relays [100], [112], [113].”