Joint Hybrid and Passive RIS-Assisted Beamforming for mmWave MIMO Systems Relying on Dynamically Configured Subarrays

Feng, Chenghao; Shen, Wenqian; An, Jianping; Hanzo, Lajos

doi:10.1109/jiot.2022.3142932

Cited by 42 publications

(24 citation statements)

References 76 publications

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“…As characterized in the literature, the RISs are made from metasurfaces; thus, their phases are independently tuned. 2,14,28 In addition, a RIS is often equipped with a smart controller, and its phases are discrete. 44 More specifically, the RISs' phases are often not continuous because of hardware limitations.…”

Section: System Modelmentioning

confidence: 99%

“…By utilizing a high phase resolution so that ℝ w ) 1 and the perfect channel estimation at the RIS controller, the w th RIS can create an ideal/optimal phase * to achieve ξ wt ¼ 0 for all w and t. 2,11,14,28 In other words, it is reasonable to obtain φ wt þ θ isd À ϕ iwt À ψ wt ¼ 0. † Therefore, the phase φ wt of the w th =t th is optimized as…”

Section: System Modelmentioning

confidence: 99%

“…12 In the literature, mmWave communications and RISs have been combined in the wireless networks. 2,4,13 Since the RISs are often deployed on the top/wall of factories/buildings, they can support mmWave communications to significantly reduce the effects of blocking objects. [14][15][16] In particular, the design of beamforming and reflecting coefficients was proposed to enhance the performance of RISs-assisted mmWave communications.…”

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confidence: 99%

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Symbol error probability of mmWave communications with transmit antenna selection and RISs under the impacts of hardware impairments

Vinh

2023

Int J Communication

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SummaryIn practice, hardware impairments (HIs) often exist in wireless devices, especially in low‐cost device systems. However, previous reports usually ignored HIs due to the computational complexity in mathematical derivations, particularly in millimeter‐wave (mmWave) communications. This article proposes the usage of transmit antenna selection (TAS) and multiple reconfigurable intelligent surfaces (RISs) to address HIs in mmWave communications. In particular, TAS is utilized at the source to increase the received signal power at the destination and reduce the effects of HIs. Multiple channel gains from RISs are combined with the classical source‐destination channel gain at the destination. The symbol error probability (SEP) expression of the mmWave communications with TAS and RISs under the effects of HIs (shortened as the TAS‐RISs‐HIs communications) is formulated over Nakagami‐ channels and verified through Monte Carlo simulations. The effects of HIs on the SEP of TAS‐RISs‐HIs communications are demonstrated through numerical illustrations. Specifically, the SEP of the TAS‐RISs‐HIs communications is significantly higher than the SEP of the ideal hardware communications with TAS and RISs, especially in the high transmit power regime. As a result, ignoring HIs when evaluating the SEP of the mmWave communications can result in some inappropriate conclusions. Moreover, the joint and separate advantages of TAS and RISs are thoroughly analyzed when comparing the SEPs in the cases with and without TAS, with and without RISs.

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Section: System Modelmentioning

confidence: 99%

Section: System Modelmentioning

confidence: 99%

mentioning

confidence: 99%

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Symbol error probability of mmWave communications with transmit antenna selection and RISs under the impacts of hardware impairments

Vinh

2023

Int J Communication

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“…However, these studies primarily focused on fully digital beamforming with a single RF chain behind every antenna. BS collaboration in mmWave multicell networks was studied in [18], but singlestream communication was only mode of communication possible due to the mobile receiver's single omnidirectional antenna.The wireless industry has recently been encouraged to examine mmWave for cellular networks due to improvements in hardware design, successful outside trials, and the availability of plentiful mmWave spectrum [19].However, due to the excessive demand on real-time signal processing for high BF gains [20], high power consumption, and cost, adopting same number of transceivers may not be practical when a large number of antennas are used to obtain superior BF gains.Therefore, it will be easier and more affordable to construct a BF structure with a lot fewer digital transceivers than total antennas.Analog BF [21], where every transceiver is connected with numerous active antennas as well as signal phase on every antenna is regulated by a network of analogue phase shifters, is an intriguing method of lowering the number of transceivers.…”

Section: Related Workmentioning

confidence: 99%

MMwave MIMO in 5G Network Analysis for Spectral Efficiency with Beamforming Based Channel Estimation

Dhabliya¹

2022

ijfrcsce

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5G network has its high energy efficiency and spectrum efficiency, massive multiple-input and multiple-output (MIMO) has been envisioned as a key technology.This research work is centred on optimal method creation of energy-efficient massive MIMO methods, which is most active research technology in the communication industry.The suggested model, which takes into account a multi-cell model scenario, is a realistic method that improved spectral efficiency (SE) of huge MIMO methods.Base stations (BSs) do channel estimate based on uplink (UL) transmission using least-square (LS), element-wise MMSE, and minimum mean-squared error (MMSE) estimators.This research propose novel technique in MMwaveMIMO 5G network based spectral efficiency and channel estimation. The aim of this research is to enhance the spectral efficiency of MIMO channel using HetNets zero forcing Multiuser propagation models. The channel estimation is carried out based on beamforming using matched filter channel estimation with wide band antenna.Finally, simulation results demonstrate the high channel estimate accuracy and spectrum efficiency that the suggested systems can accomplish.Proposed technique attained sum rate of 85%, spectral efficiency of 93%, DoF of 79%, energy efficiency of 98% and detection accuracy of 96% for number of cells and sum rate of 77%, spectral efficiency of 85%, DoF of 71%, energy efficiency of 92% and detection accuracy of 95% for number of users.

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“…However, equipping each antenna with a dedicated RF chain significantly increases the cost and power consumption of such systems. Hence, hybrid beamformers have attracted a lot of attention as a means to provide a trade-off between spectral and energy efficiencies, [ 16 , 17 ]. In such systems, a small number of RF chains are connected to a large number of antennas via a network of phase shifters and/or switches.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Beamforming and Relay Selection for End-to-End SNR Maximization in Single-User Multi-Relay MIMO Systems

Mustafa

Baik

You

et al. 2023

Sensors

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This paper proposes a novel hybrid beamforming and relay selection scheme for spectral efficiency maximization in a non-regenerative multi-relay multi-input multi-output (MIMO) system. The analog beamforming component in the radio-frequency (RF) domain must follow an element-wise constant modulus constraint, which makes the underlying design problem mathematically intractable and therefore, it is quite challenging to obtain the global optimal solution. To address this problem, phase-only precoding/combining matrices are derived by maximizing the end-to-end received signal-to-noise ratio (SNR) under transmit power constraint at the source and each relay node. This task is achieved by decomposing the original complicated optimization problem into two independent components. The first component designs the RF precoder/combiner at source and relay nodes by maximizing the received SNR at relay nodes. While the second component attempts to derive the analog precoder/combiner at relay nodes and destination by maximizing the received SNR at the destination. Digital baseband processing matrices are obtained by deriving the closed-form expression, which minimizes interference among different sub-channels. Finally, the relay selection is made by maximizing the overall SNR from the source to the destination. Computer simulations reveal that the performance of the proposed algorithm is close to its fully digital counterpart and approximately 6% higher than the specified relay-assisted hybrid beamforming techniques. Moreover, the proposed method achieves more than 15% higher performance in a sparse scattering environment when compared with the given relay selection techniques.

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Joint Hybrid and Passive RIS-Assisted Beamforming for mmWave MIMO Systems Relying on Dynamically Configured Subarrays

Cited by 42 publications

References 76 publications

Symbol error probability of mmWave communications with transmit antenna selection and RISs under the impacts of hardware impairments

Symbol error probability of mmWave communications with transmit antenna selection and RISs under the impacts of hardware impairments

MMwave MIMO in 5G Network Analysis for Spectral Efficiency with Beamforming Based Channel Estimation

Hybrid Beamforming and Relay Selection for End-to-End SNR Maximization in Single-User Multi-Relay MIMO Systems

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