scholarly journals SIC Aided K-Repetition for Mission-Critical MTC in Cell-Free Massive MIMO

2021 ◽  
Author(s):  
Jie Ding ◽  
Jinho Choi
Keyword(s):  
Interference Cancellation ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Reliability Improvement ◽  
Machine Type ◽  
Critical Machine ◽  
Multiple Input ◽  
Interference Signals ◽  
Machine Type Communication ◽  
Mission Critical

<div>In this paper, a successive interference cancellation (SIC) aided K-repetition scheme is proposed to support contention-based mission-critical machine-type communication (MTC) in cell-free (CF) massive multiple-input and multipleoutput (MIMO) systems. With the assistance of a tailored deep neural network (DNN) based preamble multiplicity estimator, the proposed SIC in K-repetition is capable of fully cancelling the interference signals, which leads to the reliability improvement in CF massive MIMO. Simulation results show the accuracy of preamble multiplicity estimation by the proposed DNN, and</div><div>demonstrate that, compared to the existing schemes, the proposed SIC scheme can achieve an improvement of two orders of magnitude in terms of block error rate (BLER) under a given latency constraint. Moreover, when the number of access points (APs) is sufficiently large, employing the proposed SIC scheme provides a great potential to meet ultra-reliable and low-latency requirements, e.g., 10<sup>-5 </sup>BLER and 1 ms access latency, for crowd mission-critical applications, which is far beyond the capabilities of the existing schemes.</div>

scholarly journals SIC Aided K-Repetition for Mission-Critical MTC in Cell-Free Massive MIMO

2021 ◽  
Author(s):  
Jie Ding ◽  
Jinho Choi
Keyword(s):  
Interference Cancellation ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Reliability Improvement ◽  
Machine Type ◽  
Critical Machine ◽  
Multiple Input ◽  
Interference Signals ◽  
Machine Type Communication ◽  
Mission Critical

<div>In this paper, a successive interference cancellation (SIC) aided K-repetition scheme is proposed to support contention-based mission-critical machine-type communication (MTC) in cell-free (CF) massive multiple-input and multipleoutput (MIMO) systems. With the assistance of a tailored deep neural network (DNN) based preamble multiplicity estimator, the proposed SIC in K-repetition is capable of fully cancelling the interference signals, which leads to the reliability improvement in CF massive MIMO. Simulation results show the accuracy of preamble multiplicity estimation by the proposed DNN, and</div><div>demonstrate that, compared to the existing schemes, the proposed SIC scheme can achieve an improvement of two orders of magnitude in terms of block error rate (BLER) under a given latency constraint. Moreover, when the number of access points (APs) is sufficiently large, employing the proposed SIC scheme provides a great potential to meet ultra-reliable and low-latency requirements, e.g., 10<sup>-5 </sup>BLER and 1 ms access latency, for crowd mission-critical applications, which is far beyond the capabilities of the existing schemes.</div>

scholarly journals On the Application of Massive MIMO Systems to Machine Type Communications

2018 ◽  
Author(s):  
Felipe A. P. de Figueiredo ◽  
Fabbryccio A. C. M. Cardoso ◽  
Ingrid Moerman ◽  
Gustavo Fraidenraichz
Keyword(s):  
Interference Cancellation ◽  
Massive Mimo ◽  
Large Scale ◽  
Mimo Systems ◽  
Detection Methods ◽  
Channel Estimator ◽  
Time Frequency ◽  
Machine Type ◽  
Machine Type Communications ◽  
Optimal Linear

This paper evaluates the feasibility of applying Massive MIMO to tackle the uplink mixed-service communication problem. Under the assumption of an available physical narrowband shared channel (PNSCH), devised to exclusively consume data traffic from Machine Type Communications (MTC) devices, the capacity (i:e:, number of connected devices) of MTC networks and, in turn, that of the whole system, can be increased by clustering such devices and letting each cluster share the same time-frequency physical resource blocks. Following this research line, we study the possibility of employing sub-optimal linear detectors to the problem and present a simple and practical channel estimator that works without previous knowledge of the large-scale channel coefficients. Our simulation results suggest that the proposed channel estimator performs asymptotically as well as the MMSE estimator with respect to the number of antennas and the uplink transmission power. Furthermore, the results also indicate that, as the number of antennas is made progressively larger, the performance of sub-optimal linear detection methods approaches the perfect interference-cancellation bound. The findings presented in this paper shed light on and motivate for new and exciting research lines towards a better understanding of the use of massive MIMO in MTC networks.

scholarly journals Pushing the Limits: Resilience Testing for Mission-Critical Machine-Type Communication

2021 ◽  
Author(s):  
Christian Arendt ◽  
Manuel Patchou ◽  
Stefan Bocker ◽  
Janis Tiemann ◽  
Christian Wietfeld
Keyword(s):  
Machine Type ◽  
Critical Machine ◽  
Machine Type Communication ◽  
Mission Critical

scholarly journals 1.5 Gbit/s FPGA Implementation of a Fully-Parallel Turbo Decoder Designed for Mission-Critical Machine-Type Communication Applications

IEEE Access ◽  
2016 ◽  
Vol 4 ◽  
pp. 5452-5473 ◽  
Author(s):  
An Li ◽  
Peter Hailes ◽  
Robert G. Maunder ◽  
Bashir M. Al-Hashimi ◽  
Lajos Hanzo
Keyword(s):  
Fpga Implementation ◽  
Turbo Decoder ◽  
Machine Type ◽  
Critical Machine ◽  
Machine Type Communication ◽  
Mission Critical

scholarly journals Mission-Critical Machine-Type Communication: An Overview and Perspectives Towards 5G

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 127198-127216 ◽  
Author(s):  
Najib Ahmed Mohammed ◽  
Ali Mohammed Mansoor ◽  
Rodina Binti Ahmad
Keyword(s):  
Machine Type ◽  
Critical Machine ◽  
Machine Type Communication ◽  
Mission Critical

PROBLEM STATEMENT OF JOINT ANTENNA SELECTION AND PRECODING IN MASSIVE MIMO COMMUNICATION SYSTEMS

2021 ◽  
Author(s):  
В.Б. КРЕЙНДЕЛИН ◽  
М.В. ГОЛУБЕВ
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Multiple Input Multiple Output ◽  
Research Areas ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Legal Restrictions ◽  
Multiple Transmission

Совместный с прекодингом автовыбор антенн на приемной и передающей стороне - одно из перспективных направлений исследований для реализации технологий Multiple Transmission and Reception Points (Multi-TRP, множество точек передачи и приема) в системах со многими передающими и приемными антеннами Massive MIMO (Multiple-Input-Multiple-Output), которые активно развиваются в стандарте 5G. Проанализированы законодательные ограничения, влияющие на применимость технологий Massive MIMO, и специфика реализации разрабатываемого алгоритма в миллиметровомдиапа -зоне длин волн. Рассмотрены алгоритмы формирования матриц автовыбора антенн как на передающей, так и на приемной стороне. Сформулирована строгая математическая постановка задачи для двух критериев работы алгоритма: максимизация взаимной информации и минимизация среднеквадратичной ошибки. Joint precoding and antenna selection both on transmitter and receiver sides is one of the promising research areas for evolving toward the Multiple Transmission and Reception Points (Multi-TRP) concept in Massive MIMO systems. This technology is under active development in the coming 5G 3GPP releases. We analyze legal restrictions for the implementation of 5G Massive MIMO technologies in Russia and the specifics of the implementation of the developed algorithm in the millimeter wavelength range. Algorithms of antenna auto-selection matrices formation on both transmitting and receiving sides are considered. Two criteria are used for joint antenna selection and precoding: maximizing mutual information and minimizing mean square error.

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