Estimation of Channel State Information (CSI) in Cell-Free Massive MIMO Based on Time of Arrival (ToA)

Almamori, Aqiel; Mohan, Seshadri

doi:10.1007/s11277-020-07450-8

Cited by 11 publications

(6 citation statements)

References 10 publications

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“…Additionally, inter-satellite communications may consider massive MIMO within the high frequency bands to realize high-speed data transmission and flexible network architecture but that requires accurate and fast channel estimation. Angle-of-arrival (AoA) is promising technology in this setup for improving the multiplexing gain and radio link quality especially in the regions with poor signal strength [95]. Moreover, the high density of mega-constellation along with the simultaneous visibility of more NGSO satellites can be exploited to establish cell-free massive MIMO architecture to benefit from the efficient duplexing technique, pilot assignment, and handover management, and then, a substantial performance improvement can be achieved [96].…”

Section: A Physical and Radio Access Aspectsmentioning

confidence: 99%

A Survey on Nongeostationary Satellite Systems: The Communication Perspective

Al-Hraishawi

Chougrani

Kisseleff

et al. 2023

IEEE Commun. Surv. Tutorials

103

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The next phase of satellite technology is being characterized by a new evolution in non-geostationary orbit (NGSO) satellites, which conveys exciting new communication capabilities to provide non-terrestrial connectivity solutions and to support a wide range of digital technologies from various industries. NGSO communication systems are known for a number of key features such as lower propagation delay, smaller size, and lower signal losses in comparison to the conventional geostationary orbit (GSO) satellites, which can potentially enable latency-critical applications to be provided through satellites. NGSO promises a substantial boost in communication speed and energy efficiency, and thus, tackling the main inhibiting factors of commercializing GSO satellites for broader utilization. The promised improvements of NGSO systems have motivated this paper to provide a comprehensive survey of the state-of-theart NGSO research focusing on the communication prospects, including physical layer and radio access technologies along with the networking aspects and the overall system features and architectures. Beyond this, there are still many NGSO deployment challenges to be addressed to ensure seamless integration not only with GSO systems but also with terrestrial networks. These unprecedented challenges are also discussed in this paper, including coexistence with GSO systems in terms of spectrum access and regulatory issues, satellite constellation and architecture designs, resource management problems, and user equipment requirements. Finally, we outline a set of innovative research directions and new opportunities for future NGSO research.

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Section: A Physical and Radio Access Aspectsmentioning

confidence: 99%

A Survey on Nongeostationary Satellite Systems: The Communication Perspective

Al-Hraishawi

Chougrani

Kisseleff

et al. 2023

IEEE Commun. Surv. Tutorials

103

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“…It might be less of an issue in CF mMIMO than in conventional mMIMO due to the distributed nature, where each AP has relatively few antennas, but it cannot be neglected. To mitigate pilot contamination, [68] proposed a time-ofarrival (TOA)-based scheme that first estimates the TOA of the multipath channel and then filters out interfering signals of paths originating from distant APs. It is shown that the proposed TOAbased scheme could outperform the LS estimator given the TOA estimation is accurate.…”

Section: A Channel Estimationmentioning

confidence: 99%

A Survey on User-Centric Cell-Free Massive MIMO Systems

Chen¹,

Zhang²,

Zhang³

et al. 2021

Preprint

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The mobile data traffic has been exponentially growing during the last decades, which has been enabled by the densification of the network infrastructure, in terms of increased cell density (i.e., ultradense network (UDN)) and/or increased number of active antennas per access point (AP) (i.e., massive multiple-input multiple-output (mMIMO)). However, neither UDN nor mMIMO will meet the increasing data rate demands of the sixth generation (6G) wireless communications due to the inter-cell interference and large quality-of-service variations, respectively. Cell-free (CF) mMIMO, which combines the best aspects of UDN with mMIMO, is viewed as a key solution to this issue. In such systems, each user equipment (UE) is served by a preferred set of surrounding APs that cooperate to serve the UE in a CF approach. In this paper, we provide a survey of the state-of-the-art literature on CF mMIMO systems.As a starting point, we present the significance and challenges of improving the user-experienced data rates which motivate CF mMIMO, derive the basic properties of CF mMIMO, and provide an introduction to other technologies related to CF mMIMO. We then provide the canonical framework for CF mMIMO, where the essential details (i.e., transmission procedure and mathematical system model) are discussed. Next, we provide a deep look at the resource allocation and signal processing problems related to CF mMIMO and survey the state-of-the-art schemes and algorithms. After that, we discuss the practical issues when implementing CF mMIMO, including fronthaul limitations and hardware impairment. Potential future directions of CF mMIMO research are then highlighted. We conclude this paper with a summary of the key lessons learned in this field. The objective of this paper is to provide a starting point for anyone who wants to conduct research on CF mMIMO for future wireless networks.

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“…Pilot-aided estimation techniques suffer from loss of spectral efficiency unlike the blind and semi-blind techniques; however, it has a better performance and lower computational complexity which makes it more attractive in practical systems [1]. The pilot-based least square (LS) and minimum mean square error (MMSE) are widely used approaches to obtain the channel estimate in OFDM in [2]- [5] other iterative techniques like adaptive filtering are also used as in [6], however, LS is less demanding in terms of computational complexity and other requirements like the prior knowledge of the noise power and channel statistics. The LS estimator does not take into account the presence of noise and this causes a degradation in the performance which motivates the need for further processing to improve the LS channel estimate [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Pilot based channel estimation improvement in orthogonal frequency-division multiplexing systems using linear predictive coding

Saleh Idan,

Al-Haddad

2024

IJECE

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Pilot based least square (LS) channel estimation is a commonly used channel estimation technique in orthogonal frequency-division multiplexing based systems due to its simplicity. However, LS estimation does not handle the noise effect and hence suffers from performance degradation. Since the channel coefficients are correlated in time and hence show a slower variation than the noise, it is possible to encode the channel using linear predictive coding (LPC) without the noise. In this work, the channel is estimated from the pilots using LS estimation and in a second step the channel’s LS estimated is encoded as LPC coefficients to produce an improved channel estimation. The estimation technique is simulated for space-time block coding (STBC) based orthogonal frequency-division multiplexing (OFDM) system and the bit error rate (BER) curves show improvement of the LPC estimation over the LS estimation of the channel.

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Estimation of Channel State Information (CSI) in Cell-Free Massive MIMO Based on Time of Arrival (ToA)

Cited by 11 publications

References 10 publications

A Survey on Nongeostationary Satellite Systems: The Communication Perspective

A Survey on Nongeostationary Satellite Systems: The Communication Perspective

A Survey on User-Centric Cell-Free Massive MIMO Systems

Pilot based channel estimation improvement in orthogonal frequency-division multiplexing systems using linear predictive coding

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