scholarly journals Unification of Broadband and Broadcast Mobile Services using Cognitive Radio

2021 ◽  
pp. 71-75
Author(s):  
V. Annapoorani ◽  
S. Sureshkumar ◽  
Srisaravanapathimurugesan ◽  
M. Manoj ◽  
K. Prabhu
Keyword(s):  
Cognitive Radio ◽  
Dynamic Spectrum Access ◽  
Large Scale ◽  
High Reliability ◽  
Multiple Input Multiple Output ◽  
Future Generation ◽  
Research Areas ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Overall Performance

The networks in future generation uses the confluence of multi-media, broadband, and broadcast services, Cognitive Radio (CR) networks are located as a preferred paradigm to bring up with spectrum functionality traumatic conditions. CRS addresses the ones troubles via dynamic spectrum access. However, the precept traumatic conditions faced through manner of manner of the CR pertain to accomplishing spectrum overall performance. At the end, spectrum overall performance improvement models based on spectrum sensing and sharing models have attracted quite a few research hobby in modern-day years, which incorporates CR mastering models, network densification architectures, and Massive Multiple Input Multiple Output (MIMO), and beamforming techniques. This paper deals with a survey of modern CR spectrum overall improvement performance models and techniques which helps ultra-high reliability with low latency communications which might be resilient to surges in web page site visitors and competition for spectrum. These models and techniques, mainly speaks about permit a big form of functionality beginning from extra superb mobiliary broadband to large-scale Internet of Things (IoT) type communications. It also provides a research correlation for many of the regular periods of a spectrum block, as well as the realistic statistics rate, the models which are used in this paper are applicable in an ultra-high frequency band. This study provides a super compare of CRs and direction for future investigations into newly identified 5G research areas, such as in business enterprise and academia.

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.

High spatiotemporal radar observation of the polar summer mesosphere using MAARSY in a MIMO configuration

2021 ◽  
Author(s):  
Ralph Latteck ◽  
Jorge Chau ◽  
Miguel Urco ◽  
Juha Vierinen ◽  
Victor Avsarkisov
Keyword(s):  
Large Scale ◽  
Middle Atmosphere ◽  
Multiple Input Multiple Output ◽  
Horizontal Resolution ◽  
Neutral Wind ◽  
Stratified Turbulence ◽  
Turbulent Dissipation ◽  
Radar Echoes ◽  
Multiple Input ◽  
Input Multiple Output

<p>Atmospheric structures due to gravity waves, turbulence, Kelvin Helmholtz instabilities, etc. in the mesosphere are being studied with a varying of ground-based and satellite-based instruments. At scales less than 100 km, they are mainly studied with airglow imagers, lidars, and radars. Typical radar observations have not been able to resolve spatial and temporal ambiguities due to the strength of radar echoes, the size of the system, and/or the nature of the atmospheric irregularities. In this work we observed spatially and temporally resolved structures of PMSE with unprecedented horizontal resolution, using the improved radar imaging accuracy of the Middle Atmosphere Alomar Radar System (MAARSY) with the aid of a multiple-input multiple output (MIMO) technique. The studies are performed in both the brightness of the mesospheric echoes and their Doppler velocities. The resolutions achieved are less than 1 km in the horizontal direction, less than 300m in altitude, and less than 1 minute in time, in an area of ~15km x 15km around 85km of altitude. We present a couple of wavelike monochromatic events, one drifting with the background neutral wind, and one propagating against the neutral wind. Horizontal wavelengths, periods, and vertical and temporal coverage of the events are described and discussed. A theory of stratified turbulence is employed in the present study. In particular, it is shown that the structure that propagates with the background wind is a large-scale turbulent KHI event.  Some important turbulence characteristics, such as a turbulent dissipation rate, buoyancy Reynolds number, and Froude number, support our conclusion.</p>

scholarly journals Deep Scanning—Beam Selection Based on Deep Reinforcement Learning in Massive MIMO Wireless Communication System

Electronics ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 1844
Author(s):  
Minhoe Kim ◽  
Woongsup Lee ◽  
Dong-Ho Cho
Keyword(s):  
Communication Systems ◽  
Large Scale ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Q Learning ◽  
Multiple Input ◽  
Beam Selection ◽  
Input Multiple Output ◽  
Optimal Beam ◽  
Resource Allocation Scheme

In this paper, we investigate a deep learning based resource allocation scheme for massive multiple-input-multiple-output (MIMO) communication systems, where a base station (BS) with a large scale antenna array communicates with a user equipment (UE) using beamforming. In particular, we propose Deep Scanning, in which a near-optimal beamforming vector can be found based on deep Q-learning. Through simulations, we confirm that the optimal beam vector can be found with a high probability. We also show that the complexity required to find the optimum beam vector can be reduced significantly in comparison with conventional beam search schemes.

scholarly journals 3D Multiple Input Multiple Output Large-Scale Antenna Systems

2020 ◽  
Vol 55 (6) ◽  
Author(s):  
Saif Saad Hameed ◽  
Fouad H. Awad ◽  
Adnan Yousif Dawod ◽  
Ayoob Abdulmunem Abdulhameed
Keyword(s):  
Large Scale ◽  
Random Noise ◽  
Multiple Input Multiple Output ◽  
Least Square ◽  
Noise Sources ◽  
Estimation Algorithms ◽  
High Data ◽  
Data Rates ◽  
Multiple Input ◽  
Input Multiple Output

The channel could be evaluated by utilizing several estimation algorithms. The various patterns of pilot arrangements for the channel appreciation are a huge problem in channel appreciation techniques since all the processes depends on it; this paper discusses improvements in channel selection. The Least Square and Least Square Mean methods are common, simple ways to begin to estimate a channel; however, they are less efficient than more complex approaches. Due to the boost in demand with high data rates in communications, developers continue to invent new methods and mechanisms to adjust the capacity and the accuracy of the communication network. One of the primary troubles in wireless communication is the communication channel, which is affected by nonlinear and random noise sources, which decrease the quality of the service on the network; in this case, the channel must be equalized to increase performance with minimal error. In this paper, a Massive Multiple Input Multiple Output was designed and simulated in order to estimate the channel and the performance of the network through using Least Square and Least Square Mean.

scholarly journals Τεχνοοικονομική διαχείριση κινητών δικτύων πέμπτης γεννιάς (5G) και εξής

2021 ◽  
Author(s):  
Anastasia Κόλλια. Αναστασία
Keyword(s):  
Cloud Computing ◽  
Cognitive Radio ◽  
Massive Mimo ◽  
Multiple Input Multiple Output ◽  
Network Function Virtualization ◽  
Software Defined Networks ◽  
Network Function ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Antenna Systems

Σήμερα, η χρήση κινητών δικτύων αποτελεί αναπόσπαστο κομμάτι της καθημερινότητας. Οι χρήστες χρησιμοποιούν το κινητό τόσο για κλήσεις και μηνύματα όσο και για κοινωνικά δίκτυα, βίντεο, ταινίες, εφαρμογές ασκήσεις και φυσικής κατάστασης, παιχνίδια, εφαρμογές γραφείου, ημερολόγια κλπ. Η χρηστικότητα των συσκευών όχι μόνο έχει αλλάξει άρδην τα τελευταία χρόνια, αλλά αναμένεται να μεταβληθεί ακόμα περισσότερο ιδίως όταν εφαρμογές Internet of Things (IoT) προστεθούν στην ήδη διευρυμένη χρήση των κινητών συσκευών. Ακόμα, εμφανίζεται η τάση προσθήκης στο δίκτυο άλλων απλών οικιακών συσκευών και άλλου επιπρόσθετου εξοπλισμού π.χ. ιατρικών μικροσυσκευών, συσκευών παρακολούθησης, καμερών ασφαλείας κλπ. Η διδακτορική αυτή διατριβή αποτελεί μία συνολική μελέτη και περιλαμβάνει ένα πλαίσιο σχετικά με την πέμπτη γενιά κινητής τηλεπικοινωνίας. Αναλύεται η κατάσταση των Τηλεπικοινωνιών στην Ελλάδα σε βάθος. Ακόμα, περιγράφονται οι σημαντικότερες έννοιες και τα πιο βασικά βήματα και οι σημαντικότερες εξελίξεις των υπαρχουσών γενεών κινητών δικτύων επικοινωνίας. Επιπρόσθετα, περιγράφεται το θεωρητικό πλαίσιο για τα κινητά δίκτυα επικοινωνίας, καθώς και διάφοροι όροι, που είναι απαραίτητοι για την κατανόηση της παρούσας διατριβής. Αναλύονται διεξοδικά οι σημαντικότερες τεχνολογίες, που αποτελούν δομικούς λίθους για την ανάπτυξη, αλλά και την εξέλιξη στη δόμηση και ύπαρξη της 5G γενιάς κινητής τηλεπικοινωνίας, όπως έχει ήδη περιγραφεί από πλήθος ερευνητικών δράσεων και περιλαμβάνουν τις τεχνολογίες: Υπέρπυκνες Αρχιτεκτονικές (Ultra-dense), Distributed Antenna Systems (DAS), Network Function Virtualization (NFV), Software Defined Networks (SDN), Massive Multiple Input Multiple Output (MIMO), Cognitive Radio (CR), Milimeter Wave (mmWave), Cloud Computing και IoT και σύγκριση με τις σημερινές τεχνολογίες. Παρατίθενται τεχνο-οικονομικά μοντέλα, με βάση τις πιο σημαντικές τεχνολογίες, που συντελούν στην ανάπτυξη και προώθηση της 5G. Τα μοντέλα αυτά αποτελούν σημαντικό όπλο, ώστε οι πάροχοι να επενδύσουν σε νέες τεχνολογίες, να έχουν κέρδη και να καινοτομούν. Για το σκοπό αυτό επεξηγούνται τα αρχιτεκτονικά μοντέλα, τα μαθηματικά μοντέλα, οι παράμετροι, που επιλέγονται αλλά και τα αντίστοιχα πειράματα, που διεξάγονται για τις τεχνολογίες Ultra-density, DAS, NFV, SDN, Massive MIMO, CR, mmWave. Συνοψίζονται τα κυριότερα συμπεράσματα βάση των επιμέρους μελετών, που πραγματοποιήθηκαν στα πλαίσια της παρούσας διατριβής και προτείνονται ιδέες για μελλοντική έρευνα στον τομέα. Στα πλαίσια αυτά φιλοδοξείται ότι η συγκεκριμένη εργασία θα αποτελέσει ένα βασικό εργαλείο πληροφόρησης και ενημέρωσης για την επιστημονική και τηλεπικοινωνιακή κοινότητα σε ό,τι αναφορά στην τεχνο-οικονομική ανάλυση των τεχνολογιών, που αποτελούν τους θεμέλιους λίθους για τα δίκτυα Πέμπτης γενιάς.

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