Accelerated Randomized Methods for Receiver Design in Extra-Large Scale MIMO Arrays

Rodrigues, V.; Amiri, Abolfazl; Abrão, Taufik; Carvalho, Elisabeth de; Popovski, Petar

doi:10.1109/tvt.2021.3082520

Cited by 14 publications

(8 citation statements)

References 25 publications

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“…3) Select the optimal δ (K,B) * NOVR-XL in the sense that maximizes the system sum-rate, such as: (17) and record the optimal scale factor in the reference table. Notice that the scale factor δ in eq.…”

Section: B Exploring Vrs Subarrays and Noma In Novr-xl Protocolmentioning

confidence: 99%

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NOMA-Based Random Access in mMTC XL-MIMO

Alves

Abrão

2023

IEEE Access

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In machine-type communication (MTC), massive access attempts are generated and the massive MIMO is the key technology to support this demand. To support massive MTC (mMTC), the recent extra-large scale massive multiple-input multiple-output (XL-MIMO) architecture has been seen as a promising technology for providing very high-data rates in high-user density scenarios. Therefore, the large dimension is of the same order as the distances to the user equipment (UE) causing spatial nonstationarities and visibility regions (VRs) to occur across the huge XL array extension. We investigate the random access (RA) problem in crowded XL-MIMO scenarios; the proposed grant-based random access (GB-RA) protocol combining the advantage of non-orthogonal multiple access (NOMA) and strongest user collision resolutions in extra-large arrays (SUCRe-XL) named NOVR-XL can allow access of multiple colliding users in the same XL subarray (SA) selecting the same pilot sequence. The proposed NOVR-XL GB-RA protocol is able to provide a reduction in the number of attempts to access the network, while improving the average sum-rate, as the number of SA increases.

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Section: B Exploring Vrs Subarrays and Noma In Novr-xl Protocolmentioning

confidence: 99%

“…Recently, XL-MIMO systems have received a lot of research interest. Recent papers analyse RA improvements in linear receiver schemes [13]- [15], appropriate channel models [12], channel estimation algorithms [16], non-linear receiver schemes [17], and efficient RA schemes in XL-MIMO [18]- [20].…”

Section: Introductionmentioning

confidence: 99%

NOMA-Based Random Access in mMTC XL-MIMO

Alves

Abrão

2023

IEEE Access

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“…To accelerate the speed of the convergence in Algorithm 1, some modified versions of the rKA-based schemes can be implemented [28]. To achieve higher SE and accelerate the speed of the convergence, inspired by [23], we apply the SwoR-rKA algorithm with a different randomization scheme compared to the former rKA algorithm. Before the iteration from step 2 to step 11 in Algorithm 1, we store h j jr(t)…”

Section: B Swor-rka Algorithmmentioning

confidence: 99%

“…So it is necessary to design an algorithm to offer a possibility for a performance-complexity trade-off. On the other hand, the work in [22], [23] based on the regularized ZF (RZF) algorithm design achieves a better SE performance than the ZF algorithm. However, it focused on the low-complexity algorithm of uplink signal detection.…”

Section: Introductionmentioning

confidence: 99%

Low-Complexity Precoding for Extremely Large-Scale MIMO Over Non-Stationary Channels

Xu¹,

Wang²,

Xiao³

et al. 2023

Preprint

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Extremely large-scale multiple-input-multiple-output (XL-MIMO) is a promising technology for the future sixthgeneration (6G) networks to achieve higher performance. In practice, various linear precoding schemes, such as zero-forcing (ZF) and regularized zero-forcing (RZF) precoding, are capable of achieving both large spectral efficiency (SE) and low bit error rate (BER) in traditional massive MIMO (mMIMO) systems. However, these methods are not efficient in extremely large-scale regimes due to the inherent spatial non-stationarity and high computational complexity. To address this problem, we investigate a low-complexity precoding algorithm, e.g., randomized Kaczmarz (rKA), taking into account the spatial non-stationary properties in XL-MIMO systems. Furthermore, we propose a novel mode of randomization, i.e., sampling without replacement rKA (SwoR-rKA), which enjoys a faster convergence speed than the rKA algorithm. Besides, the closed-form expression of SE considering the interference between subarrays in downlink XL-MIMO systems is derived. Numerical results show that the complexity given by both rKA and SwoR-rKA algorithms has 51.3% reduction than the traditional RZF algorithm with similar SE performance. More importantly, our algorithms can effectively reduce the BER when the transmitter has imperfect channel estimation.

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“…Due to the emergence of new applications such as digital twin, holographic imaging, and extended reality, the spectral efficiency of 6G is expected to grow tenfold [1]- [3]. To achieve higher spectral efficiency, the extremely large-scale MIMO (XL-MIMO) is regarded as one of the most important technology for 6G [4], [5]. In XL-MIMO communications, by exploiting the high spatial multiplexing gain, the transmitter equipped with an extremely large-scale antenna array serves multiple users to achieve better spectral efficiency.…”

Section: Introductionmentioning

confidence: 99%

Double-Side Near-Field Channel Estimation for Extremely Large-Scale MIMO System

Lu¹,

Dai²

2022

Preprint

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Accurate channel estimation is essential to empower extremely large-scale MIMO (XL-MIMO) in 6G networks with ultra-high spectral efficiency. Unfortunately, most of the existing channel estimation methods designed for XL-MIMO fail to consider a double-side near-field scenario, where both transmitter and receiver are equipped with extremely large-scale antenna arrays. The existing channel estimation schemes cannot be directly applied to the double-side near-field scenario. In this paper, based on this scenario, we first derive double-side near-field Rayleigh distance (DS-RD) and effective doubleside near-field Rayleigh distance (EDS-RD) to determine the range of the double-side near-field region.Then, a double-side near-field channel model is proposed to match this scenario, where the distance of the transmitter from the receiver is smaller than EDS-RD. In the proposed channel model, the line of sight (LoS) path component is modeled by the geometric free assumption while non-line of sight (NLoS) path components are modeled by the near-field array response vectors. Finally, a double-side near-field channel estimation algorithm is proposed to solve the channel estimation problem in this scenario, where the LoS path component and NLoS path components are estimated separately. Numerical simulation results demonstrate that, the proposed channel estimation algorithm is able to outperform the existing methods.

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Accelerated Randomized Methods for Receiver Design in Extra-Large Scale MIMO Arrays

Cited by 14 publications

References 25 publications

NOMA-Based Random Access in mMTC XL-MIMO

NOMA-Based Random Access in mMTC XL-MIMO

Low-Complexity Precoding for Extremely Large-Scale MIMO Over Non-Stationary Channels

Double-Side Near-Field Channel Estimation for Extremely Large-Scale MIMO System

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