Ergodic Rate Analysis of Reconfigurable Intelligent Surface-Aided Massive MIMO Systems With ZF Detectors

Zhi, Kangda; Pan, Cunhua; Ren, Hong; Wang, Kezhi

doi:10.1109/lcomm.2021.3128904

Cited by 26 publications

(7 citation statements)

References 18 publications

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“…While RIS seems perfect to work with MIMO at the BS for enhancing mobile coverage, mobile networks may see another transformation by letting a large number of access points (APs) serve as distributed BS antennas for supermassive coordinated beamforming in the cell-free architecture for accommodating many users on the same time-frequency resource block [92]- [95]. The integration of RIS and CF mMIMO has the potential to improve the network performance further [96], [97].…”

Section: E Ris and Cf Mmimomentioning

confidence: 99%

MIMO Evolution Beyond 5G Through Reconfigurable Intelligent Surfaces and Fluid Antenna Systems

et al. 2022

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With massive deployment, multiple-inputmultiple-output (MIMO) systems continue to take mobile communications to new heights, but the ever-increasing demands mean that there is a need to look beyond MIMO and pursue the next disruptive wireless technologies. Reconfigurable intelligent surface (RIS) is widely considered a key candidate technology block to provide the next generational leap. The first part of this article provides an updated overview of the conventional reflection-based RIS technology, which complements the existing literature to include active and semiactive RIS, and the synergies with cell-free massive MIMO (CF mMIMO). Then, we Manuscript

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Section: E Ris and Cf Mmimomentioning

confidence: 99%

MIMO Evolution Beyond 5G Through Reconfigurable Intelligent Surfaces and Fluid Antenna Systems

et al. 2022

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“…In [10] and [11], the performance of a RIS-assisted MIMO system was studied, when one of the two RIS-enabled links is modeled as Rician fading channels while the other is described by pure LoS conditions. Also, a phase shift design was proposed in these works based on a statistical CSI.…”

Section: A Related State Of the Artmentioning

confidence: 99%

“…To further boost the system performance, multiple input-multiple output (MIMO) signal transmission can be used in conjunction with RIS [6]- [11]. Nevertheless, the main challenge in these systems is the phase shift adaptation/optimization.…”

Section: Introductionmentioning

confidence: 99%

Zero Forcing Uplink Detection Through Large-Scale RIS: System Performance and Phase Shift Design

Miridakis

Tsiftsis

Yao

2023

IEEE Trans. Commun.

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A multiple-input multiple-output wireless communication system is analytically studied, which operates with the aid of a large-scale reconfigurable intelligent surface (LRIS). LRIS is equipped with multiple passive elements with discrete phase adjustment capabilities, and independent Rician fading conditions are assumed for both the transmitter-to-LRIS and LRIS-to-receiver links. A direct transceiver link is also considered which is modeled by Rayleigh fading distribution. The system performance is analytically studied when the linear yet efficient zero-forcing detection is implemented at the receiver. In particular, the outage performance is derived in closed-form expression for different system configuration setups with regards to the available channel state information (CSI) at the receiver. In fact, the case of both perfect and imperfect CSI is analyzed. Also, an efficient phase shift design approach at LRIS is introduced, which is linear on the number of passive elements and receive antennas. The proposed phase shift design can be applied on two different modes of operation; namely, when the system strives to adapt either on the instantaneous or statistical CSI. Finally, some impactful engineering insights are provided, such as how the channel fading conditions, CSI, discrete phase shift resolution, and volume of antenna/LRIS element arrays impact on the overall system performance.

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“…Since Hd and Hr are mutual independent and both contain complex Gaussian variables, we have dj ∼ CN (0, I Nt ) and rj ∼ CN (0, I N ), ∀j = 1, 2, • • • , N r . Since the linear transformation of a Gaussian random vector or the sum of independent Gaussian vectors is Gaussian [48], the j-th column of Ȟ yields…”

Section: Model-driven Large-timescale Passive Beamforming With Lower-...mentioning

confidence: 99%

Two-Timescale Optimization for Intelligent Reflecting Surface-Assisted MIMO Transmission in Fast-Changing Channels

Cao

2022

IEEE Trans. Wireless Commun.

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The application of intelligent reflecting surface (IRS) depends on the knowledge of channel state information (CSI), and has been hindered by the heavy overhead of channel training, estimation, and feedback in fast-changing channels. This paper presents a new two-timescale beamforming approach to maximizing the average achievable rate (AAR) of IRS-assisted MIMO systems, where the IRS is configured relatively infrequently based on statistical CSI (S-CSI) and the base station precoder and power allocation are updated frequently based on quickly outdated instantaneous CSI (I-CSI). The key idea is that we first reveal the optimal small-timescale power allocation based on outdated I-CSI yields a water-filling structure. Given the optimal power allocation, a new mini-batch sampling (mbs)based particle swarm optimization (PSO) algorithm is developed to optimize the large-timescale IRS configuration with reduced channel samples. Another important aspect is that we develop a model-driven PSO algorithm to optimize the IRS configuration, which maximizes a lower bound of the AAR by only using the S-CSI and eliminates the need of channel samples. The modeldriven PSO serves as a dependable lower bound for the mbs-PSO. Simulations corroborate the superiority of the new two-timescale beamforming strategy to its alternatives in terms of the AAR and efficiency, with the benefits of the IRS demonstrated.

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Ergodic Rate Analysis of Reconfigurable Intelligent Surface-Aided Massive MIMO Systems With ZF Detectors

Cited by 26 publications

References 18 publications

MIMO Evolution Beyond 5G Through Reconfigurable Intelligent Surfaces and Fluid Antenna Systems

MIMO Evolution Beyond 5G Through Reconfigurable Intelligent Surfaces and Fluid Antenna Systems

Zero Forcing Uplink Detection Through Large-Scale RIS: System Performance and Phase Shift Design

Two-Timescale Optimization for Intelligent Reflecting Surface-Assisted MIMO Transmission in Fast-Changing Channels

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