Enabling Ultra Reliable Wireless Communications for Factory Automation with Distributed MIMO

Casciano, Gianluca; Baracca, Paolo; Buzzi, Stefano

doi:10.1109/vtcfall.2019.8891368

Cited by 9 publications

(10 citation statements)

References 15 publications

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“…Under suitable constraints, the authors described an optimization problem aimed to jointly optimizing the blocklength and power allocation to minimize the decoding error probability. Paper [12] considered a scenario wherein the access points (APs) form a distributed multiantenna system, to communicate with the active ACs in the factory, assuming that the small scale fading was modelled as the common Rayleigh fading, instead, a path-loss model for industrial scenario was used [13]. The performances in term of SINR, for different deployments, different beamforming, in case of equal and optimal power allocation [14] was analyzed.…”

Section: Introductionmentioning

confidence: 99%

Cell-Free and User-Centric Massive MIMO Architectures for Reliable Communications in Indoor Factory Environments

Alonzo

Baracca

Khosravirad

et al. 2021

IEEE Open J. Commun. Soc.

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Factory automation is one of the use cases for 5G-and-beyond mobile networks where strict requirements in terms of latency, availability and reliability are required. In this paper, we investigate the potentials of massive MIMO in delivering those promises for industrial automation. Namely, communications between actuators (ACs) and Access Points (APs) inside an industrial scenario is considered and different transmission modes are compared: joint transmission (JT) where the distributed antennas are used to communicate with each AC, cell-free transmission (CFT) where all the ACs are served by all APs, single AP transmission (SAT) where each AC is served by only one AP, and user-centric transmission (UCT) where each AC is served by a subset of APs. A power control strategy, aimed at maximizing the minimum signal-to-interference plus noise ratio (SINR), is also introduced. Numerical results, shown in terms of downlink SINR and achievable rate, evaluated using the final block length capacity formula (FBLC), demonstrate that the use of distributed antenna setting and of power control bring substantial performance improvements in terms of reliability and latency.

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Section: Introductionmentioning

confidence: 99%

Cell-Free and User-Centric Massive MIMO Architectures for Reliable Communications in Indoor Factory Environments

Alonzo

Baracca

Khosravirad

et al. 2021

IEEE Open J. Commun. Soc.

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“…12. Since CF mMIMO not only captures the benefits of mMIMO but also network MIMO [36], it provides more distinctive features than mMIMO [106]- [109]. In the following, we present its key features and benefits compared to mMIMO.…”

Section: Potential Of Emerging Cf Mmimomentioning

confidence: 99%

“…13 with an indoor GF URLLC scenario, where URLLC devices perform GF random access to transmit data. Similar to [106], we assume a factory automation scenario with a square area of 100 × 100 m 2 . Within this area, there are Q = 100 distributed APs deployed on the ceiling on a square grid.…”

Section: A Features Of Cf Mmimomentioning

confidence: 99%

Enabling Grant-Free URLLC: An Overview of Principle and Enhancements by Massive MIMO

Ding

Pokhrel

Park

et al. 2022

IEEE Internet Things J.

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Enabling ultra-reliable low-latency communication (URLLC) with stringent requirements for transmitting data packets (e.g., 99.999% reliability and 1 millisecond latency) presents considerable uplink transmission challenges. For each packet transmission over dynamically allocated network radio resources, the conventional random access protocols are based on a request-grant scheme. This induces excessive latency and necessitates reliable control signalling, resulting in overhead. To address these problems, grant-free (GF) solutions are proposed in the fifth-generation (5G) new radio (NR). In this paper, an overview and vision of the state-of-the-art in enabling GF URLLC are presented. In particular, we first provide a comprehensive review of NR specifications and techniques for URLLC, discuss underlying principles, and highlight impeding issues of enabling GF URLLC. Furthermore, we briefly explain two key phenomena of massive multiple-input multiple-output (mMIMO) (i.e., channel hardening and favorable propagation) and build several deep insights into how celebrated mMIMO features can be exploited to address the issues and enhance the performance of GF URLLC. Moving further ahead, we examine the potential of cell-free (CF) mMIMO and analyze its distinctive features and benefits over mMIMO to resolve GF URLLC issues. Finally, we identify future research directions and challenges in enabling GF URLLC with CF mMIMO.

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“…10. Since CF mMIMO not only captures the benefits of mMIMO but also network MIMO [36], it provides more distinctive features than mMIMO [100]- [103]. In the following, we present its key features and benefits compared to mMIMO.…”

Section: Potential Of Cf Mmimomentioning

confidence: 99%

“…11 with an indoor URLLC scenario. Similar to [100], we assume a factory automation scenario with a square area of 100 × 100 m 2 . Within this area, there are Q = 100 distributed APs deployed on ceiling on a square grid.…”

Section: A Features Of Cf Mmimomentioning

confidence: 99%

Enabling Grant-Free URLLC: An Overview of Principle and Enhancements by Massive MIMO

Ding¹,

Pokhrel²,

Park³

et al. 2021

Preprint

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<div>Enabling ultra-reliable low-latency communication (URLLC) with stringent requirements for transmitting data packets (e.g., 99.999% reliability and 1 millisecond latency) presents considerable challenges in uplink transmissions. For each packet transmission over dynamically allocated network radio resources, the conventional random access protocols are based on a request- rant scheme. This induces excessive latency and necessitates reliable control signalling, resulting overhead. To address these problems, grant-free (GF) solutions are proposed in the fifth-generation (5G) new radio (NR). In this paper, an overview and vision of the state-of-the-art in enabling GF URLLC are presented. In particular, we first provide a comprehensive review of NR specifications and techniques for URLLC, discuss underlying principles, and highlight impeding issues of enabling GF URLLC. Furthermore, we explain two key phenomena of massive multiple-input multiple-output (mMIMO) (i.e., channel hardening and favorable propagation) and build several deep insights into how celebrated mMIMO features can be exploited to enhance the performance of GF URLLC. Moving further ahead, we examine the potential of cell-free (CF) mMIMO and analyze its distinctive features and benefits over mMIMO to resolve GF URLLC issues. Finally, we identify future research directions and challenges in enabling GF URLLC with CF mMIMO.</div>

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Enabling Ultra Reliable Wireless Communications for Factory Automation with Distributed MIMO

Cited by 9 publications

References 15 publications

Cell-Free and User-Centric Massive MIMO Architectures for Reliable Communications in Indoor Factory Environments

Cell-Free and User-Centric Massive MIMO Architectures for Reliable Communications in Indoor Factory Environments

Enabling Grant-Free URLLC: An Overview of Principle and Enhancements by Massive MIMO

Enabling Grant-Free URLLC: An Overview of Principle and Enhancements by Massive MIMO

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