Beamforming management and beam training in 5G system

Massive multiple-input-multiple-output (MIMO) antenna system with beamforming technique is an integral part of upcoming 5G new radio (NR) system. For the upcoming deployment of 5G NR system in both stand-alone (SA) and non-stand-alone (NSA) structure, beamforming plays an important role to achieve its key features and meet the estimated requirement. To be employed with massive MIMO antenna structure, beamforming will allow 5G system to serve several users at a time with better throughput and spectral usage. Beamforming will also minimize the path loss due to high susceptibility of millimetre wave and provide beamforming gain. For a wide range of benefit scheme, beamforming is currently a hot topic regarding the deployment of 5G. With the advantage of both analog and digital beamforming, hybrid beamforming structure can provide better system benchmark performance in terms of cost and flexibility. Switched beam training and adaptive beam training approaches and algorithms are developed in order to reduce training time, signalling overhead and misdetection probability. Some of the approaches and algorithm are addressed in this thesis. Beamforming management ensures the initiation and sustainability of the established link between transmitter and receiver through different processes. Beam tracking helps to keep track of the receiver devices during mobility. As beamforming is related to antenna configuration, near-field spherical wave front incident problem was ignored, and all the references and examples presented in this topic was obtained with a far-field propagation perspective. To avoid mutual coupling between antenna elements and grating lobe problems in antenna radiation pattern, each element is separated by half of the wavelength. This thesis paper aims to provide a broader view into beamforming scenario, starting from the basics of beamforming to training the beams and management aspects in the hardware part of 5G structure. Another goal is to present the necessity of beamforming in a 5G system by stating different benefits scheme such as spatial diversity, interference suppression, energy efficiency, spectral efficiency and so on. These benefits are justified by evaluating various research paper and MATLAB simulations

Real Coded Genetic Algorithm with Enhanced Abilities for Adaptation Applied to Optimisation of MIMO Systems

This article presents an investigation of real coded Genetic Algorithm Blend Crossover Alpha modification, with enhanced ability for adaptation, applied to minimisation of transmit power in multiple-input multiple-output (MIMO) systems beamforming. The goal is to formulate transmit power minimisation task as a black box software object and evaluate an alternative to currently existing methods for optimisation of transmit energy in multicast system constrained by signal to noise ratio. The novelty of this adaptive methodology for determination of minimal power level within certain Quality of Service criteria is that it guarantees satisfaction of the constraint and 100% feasibility of achieved solutions. In addition this methodology excludes retuning algorithms parameters by using black box model for the problem definition. Experiments are conducted for identification of weight vectors assigned for signal strength and direction. Achieved experimental results are presented and analysed

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

Multi-user MIMO beamforming:implementation, verification in L1 capacity, and performance testing

Abstract. A certain piece of technology takes a lot of effort, research, and testing to reach the productisation phase. Radio features are implemented in layer 1 (L1) before moving to the hardware implementation phase, where their functioning is tested and verified. The target of the thesis is to implement and verify beamforming based multi-user multiple-input multiple-output (MU-MIMO) in L1 capacity and performance testing (PET) environment. The L1 testing environment mainly focuses on 4G and 5G stand-alone (SA) cases, while the focus of this thesis work is only on 5G SA technology, which features beamforming and MU-MIMO. Beamforming and MU-MIMO have been tested in an end-to-end system but not specifically in L1. The L1 testing provides a deeper analysis of beamforming and MU-MIMO in L1 and aids in problem identification at an early productisation phase, saving both time and money. L1 PET has multiple components that work together for L1 data transmission in both uplink (UL) and downlink (DL) directions and handle the verification of the transmitted data. The main components that play a key role in the implementation of multi-user MIMO beamforming concern frame design setup, message setup for UL and DL using correct channels and interfaces, transmission of the generated data in UL and DL, and message capturing at L1 end (whether correct messages are transmitted or not). For verification purposes, methods such as analysing plots from L1 log results based on comparison with radio specifications are used to determine whether the generated test output is correct or not. Finally, performance metrics, such as error vector magnitude (EVM), UE per transmission time interval (TTI), number of layers per UE, channel quality indicator (CQI), physical resource block (PRB) count, and throughput, are evaluated to assess the capacity and performance correctness of the implemented test setup

5G URLLC: Tekniikka ja teollisuussovellukset

Koska mobiiliverkkojen käyttö on jatkuvassa kasvussa ja internetissä olevien laitteiden määrä on moninkertaistunut viime vuosina, tarvitaan uusia, moderneja ratkaisuja tukemaan entistä yksilöllisempiä tarpeita sekä keinoja hallita alati kasvavaa datan määrää. Viidennen sukupolven mobiiliviestintäteknologia eli 5G on kykenevä vastaamaan näihin haasteisiin, ja se avaa paljon ovia myös uusille sovelluksille, joita voidaan hyödyntää monialaisesti. Tämän kandidaatintyön tarkoituksena on perehtyä syvemmin 5G:n potentiaaliin sekä sen myötä syntyneisiin mahdollisuuksiin eri käytännön aloilla ja sovelluskohteissa. Lisäksi työssä tarkastellaan URLLC:tä (engl. Ultra-Reliable, Low-Latency Communications) ja sen merkitystä osana 5G:n tärkeimpiä teknologioita. Tutkielma tehtiin kirjallisuuskatsauksena, ja aineistona käytettiin muun muassa tieteellisiä artikkeleita sekä muita tekstilähteitä. 5G on uusi mobiiliverkkoteknologia, joka toimii edellisiä teknologioita suuremmilla taajuuskaistoilla. Tämän ansiosta sitä voidaan hyödyntää eri tavoin, ja kapasiteetti riittää kattamaan suuretkin tietoliikennemäärät. Koska URLLC yhdessä muiden 5G:n avainteknologioiden kanssa mahdollistaa luotettavan ja nopean tiedonsiirron, näkyy 5G:n luomat parannukset muun muassa vapaa-aikaan, maatalouteen ja teollisuuteen liittyvissä käyttökohteissa hyvinkin selkeästi. Työssä keskitytään pääasiassa teollisuuden sovelluksiin, sillä 5G:n myötä myös teollisuus on kokenut suuren muutoksen, ja puhutaankin teollisuuden neljännestä vallankumouksesta. Teollisuus keskittyy entistä enemmän digitaalisiin sovelluksiin, joita 5G yhdessä URLLC:n kanssa mahdollistaa. Näitä ovat esimerkiksi teollisuusautomaatio, reaaliaikaiset järjestelmät ja koneoppiminen. Tutkielma osoittaa, että 5G:n merkitys teollisuuden saralla on korvaamattoman arvokas. Kustannustehokkaina sekä joustavina pidetyt langattomat tiedonsiirtomenetelmät voivat korvata entiset langalliset järjestelmät ja näin ollen parantaa tuotannon ja teollisuuden luotettavuutta, tehokkuutta ja adaptiivisuutta. Tyypillisimpänä haasteena 5G-teknologiaan liittyen on sen käyttöönotto. Uuden teknologian myötä vanhoja laitteita joudutaan päivittämään, langattoman tiedonsiirron varmistamiseksi saatetaan joutua tekemään fyysisiäkin muutoksia työtiloissa ja henkilöstöä tulee perehdyttää uusiin toimintamalleihin. 5G-teknologiassa on kuitenkin tavoiteltu sen jatkuvuutta, eli kun käyttöönottoon liittyvät haasteet saadaan suoritettua, ei isoja muutoksia tarvitse enää hetkeen tehdä

Analysis of TCP performance for LTE-5G Millimeter Wave Dual Connectivity

The goal of this work is the analysis of the performance of the transport control protocol (TCP) in a Dual connectivity (DC) system, where both LTE and 5G millimeter wave (mmWave) were used in the radio access network, while a single user travels across the scenario. Since the user is moving, the interaction between the mmWave base stations (BSs) must be very efficient to avoid congestion events. This makes the analysis of DC very important. Simulation models based on open-source software frameworks were used to evaluate the performance of Dual connectivity for a 5G non-standalone (NSA) solution, where all the 5G base station traffic goes through the LTE base station. The scenarios proposed were defined in terms of non-line-of-sight/line-of-sight (NLOS/LOS) scenario, medium/high traffic, which are used to evaluate different TCP congestion control algorithms. The performance was then evaluated in terms of goodput, packet delivery ratio, standard deviation of bytes in-flight, and round-trip time. Simulation results showed that the number of bytes in-flight grows with high rates and large latencies caused by inter-BS communication. The mmWave medium is very sensitive to channel conditions specially in the middle point between mmWave BSs causing ping-pong effect during a handover (HO). At the beginning of the simulation some nodes overflow due to the aggressive slow start mechanisms, which turn to be very problematic for high traffic rates. In that sense, TCP Cubic proves to be a much reliable congestion control algorithm since it implements a hybrid slow start method

Beamforming management and beam training in 5G system

Massive multiple-input-multiple-output (MIMO) antenna system with beamforming technique is an integral part of upcoming 5G new radio (NR) system. For the upcoming deployment of 5G NR system in both stand-alone (SA) and non-stand-alone (NSA) structure, beamforming plays an important role to achieve its key features and meet the estimated requirement. To be employed with massive MIMO antenna structure, beamforming will allow 5G system to serve several users at a time with better throughput and spectral usage. Beamforming will also minimize the path loss due to high susceptibility of millimetre wave and provide beamforming gain. For a wide range of benefit scheme, beamforming is currently a hot topic regarding the deployment of 5G. With the advantage of both analog and digital beamforming, hybrid beamforming structure can provide better system benchmark performance in terms of cost and flexibility. Switched beam training and adaptive beam training approaches and algorithms are developed in order to reduce training time, signalling overhead and misdetection probability. Some of the approaches and algorithm are addressed in this thesis. Beamforming management ensures the initiation and sustainability of the established link between transmitter and receiver through different processes. Beam tracking helps to keep track of the receiver devices during mobility. As beamforming is related to antenna configuration, near-field spherical wave front incident problem was ignored, and all the references and examples presented in this topic was obtained with a far-field propagation perspective. To avoid mutual coupling between antenna elements and grating lobe problems in antenna radiation pattern, each element is separated by half of the wavelength. This thesis paper aims to provide a broader view into beamforming scenario, starting from the basics of beamforming to training the beams and management aspects in the hardware part of 5G structure. Another goal is to present the necessity of beamforming in a 5G system by stating different benefits scheme such as spatial diversity, interference suppression, energy efficiency, spectral efficiency and so on. These benefits are justified by evaluating various research paper and MATLAB simulations