6 research outputs found

    Best Arm Identification Based Beam Acquisition in Stationary and Abruptly Changing Environments

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    We study the initial beam acquisition problem in millimeter wave (mm-wave) networks from the perspective of best arm identification in multi-armed bandits (MABs). For the stationary environment, we propose a novel algorithm called concurrent beam exploration, CBE, in which multiple beams are grouped based on the beam indices and are simultaneously activated to detect the presence of the user. The best beam is then identified using a Hamming decoding strategy. For the case of orthogonal and highly directional thin beams, we characterize the performance of CBE in terms of the probability of missed detection and false alarm in a beam group (BG). Leveraging this, we derive the probability of beam selection error and prove that CBE outperforms the state-of-the-art strategies in this metric. Then, for the abruptly changing environments, e.g., in the case of moving blockages, we characterize the performance of the classical sequential halving (SH) algorithm. In particular, we derive the conditions on the distribution of the change for which the beam selection error is exponentially bounded. In case the change is restricted to a subset of the beams, we devise a strategy called K-sequential halving and exhaustive search, K-SHES, that leads to an improved bound for the beam selection error as compared to SH. This policy is particularly useful when a near-optimal beam becomes optimal during the beam-selection procedure due to abruptly changing channel conditions. Finally, we demonstrate the efficacy of the proposed scheme by employing it in a tandem beam refinement and data transmission scheme

    Receiver Design for Physical Broadcast Channel in 5G NR

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    The 5th Generation Wireless Technology known as New Radio or NR is being developed by 3GPP (3rd Generation Partnership Project) since past few years which aims to address scenarios from Mobile Broadband to highly reliable communication with very low latency. Key advances in 5G include advanced antenna systems like Massive MI-MO, operations in higher frequency bands and achievable uplink and downlink high data rates in GBps. The Radio air interface of 5G NR includes physical layer and other higher layers as well. With the focus on physical layer, the technical specifications for NR released by 3GPP provide means to state-of-art realization and implementation of physical channels for both uplink and downlink. In NR, SS/PBCH block(SSB) consists of Synchronization signal(SS) and Physical Broadcast channel(PBCH). SSB is used to carry out cell search and identification to initialize a connection between UE and eNB. It also helps to manage handovers and beam sweeping for the radio coverage within the cell. The report aims at a detailed description on PBCH design, transmission and reception subject to a time varying wireless channel. PBCH transmitter is designed based on the technical specifications by 3GPP for 5G NR. PBCH data is generated and loaded with Demodulation reference signal(DMRS) for channel estimation at receiver.The combined data thus generated is mapped on sub-carriers and converted to time domain frames using Inverse Fourier transform (IFFT) as 5G NR is uses OFDM for both uplink and downlink transmissions. The time frames generated are convoluted with a time varying channel. The time varying channel is fast fading and follows Rayleigh distribution simulated using Jake’s model and Vehicle-A type power delay profile. AWGN noise based on SNR value is added which represents the environment noise and attenuation. The distorted and attenuated signal at the receiver is converted to frequency domain using FFT. Channel estimation is performed using DMRS. The channel equalization equalizes the time varying channel effect on the symbols and is further decoded to obtain PBCH payload.Finally the performance of the PBCH receiver is analyzed at low SNR values

    Control of The Over-The-Air measurements system

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    Abstract. Mobile technology is constantly on the move, and it is constantly under development as more efficient and sophisticated telecommunication solutions are needed. As the technology evolves the measurement systems needs to evolve as well. The mobile technology is on the brink of upheaval as we are moving from 4th Generation of wireless communication systems (4G) to 5th Generation of wireless communication systems (5G). The new mobile technology 5G brings new higher frequency bands and new technologies such as massive multiple-input multiple-output and beamforming (BF). In 5G, over-the-air (OTA) measurements are more important because it is virtually impossible to obtain reliable measurement results of BF performance. As the number of antenna elements increases and the antenna spacing decreases, it is very difficult to connect each antenna element to the measuring device with a cable. In this thesis we made tool to control a whole OTA measurement system. The tool is Python code that is run from the Windows desktop with access to the OTA measurement system. The Python code controls which antennas are taken into measurement, connects those to spectrum analyser, configures spectrum analyser and vector signal analyser and measures the power level for the desired beam set. Once the measurement results are collected, it draws a heatmap that visualizes the performance of the BF. The measurements were done by using different number of transmitted beams on the same radio unit. Each configuration was measured multiple times to ensure the stability and reliability of the system. The number of transmitted beams in measurement were 2, 4 and 6. From the plotted heatmaps it was concluded that in all measurements all synchronization signal block (SSB) beams were visible and the directions of the SSB beams were as expected. However, in all measurements the power of SSB beam 1 was slightly lower than the other SSB beams which refers to minor issue in beamforming. As expected, when the number of transmitted beams were 2, the half-power bandwidth (HPBW) was wider and the directivity lower than with 4 or 6 transmitted beams. In measurement results with 2 beams, we had unexpected power drop in the location of antenna 2 in the second SSB beam. With 4 or 6 transmitted beams we measured approximately same HPBW and directivity. The radiation patterns were also as expected. The performance with 6 beams were better in terms of coverage. With 6 transmitted beams we observed more closely mapped beams which ensures that the user equipment can seamlessly move from beam to another without drop in the signal-to-noise ratio. With 6 beams we also observed slightly wider sector coverage than with 4 transmitted beams. Ilmarajapinta mittausten ohjaus. TiivistelmÀ. Mobiiliteknologia on jatkuvasti liikkeellÀ ja sitÀ kehitetÀÀn jatkuvasti, kun tarvitaan entistÀ tehokkaampia ja kehittyneempiÀ tietoliikenneratkaisuja. Tekniikan kehittyessÀ myös mittausjÀrjestelmiÀ on kehitettÀvÀ. Mobiiliteknologia on mullistuksen partaalla, kun olemme siirtymÀssÀ 4. sukupolven langattomista viestintÀjÀrjestelmistÀ (4G) 5. sukupolven langattomiin viestintÀjÀrjestelmiin (5G). Uusi mobiiliteknologia 5G tuo uusia korkeampia taajuuskaistoja ja uusia teknologioita, kuten massiivinen moniantennitekniikka ja keilanmuodostus (BF). 5G:ssÀ ilmarajapinta (OTA) -mittaukset ovat tÀrkeÀmpiÀ, koska pelkÀstÀÀn kaapeleilla on kÀytÀnnössÀ mahdotonta saada luotettavia mittaus tuloksia BF-suorituskyvystÀ. Kun antennielementtien mÀÀrÀ kasvaa ja niiden vÀliset etÀisyydet pienenevÀt, on hyvin vaikeaa liittÀÀ jokainen antennielementti mittauslaitteeseen. TÀssÀ opinnÀytetyössÀ teimme työkalun koko OTA-mittausjÀrjestelmÀn ohjaamiseen. Työkalu on Python-koodi, joka ajetaan Windowsin työpöydÀltÀ, jolla on pÀÀsy OTA-mittausjÀrjestelmÀÀn. Python-koodilla ohjataan mitkÀ antennit otetaan mittaukseen, kytkee ne spektrianalysaattoriin, konfiguroi spektrianalysaattorin ja vektorisignaalianalysaattorin sekÀ mittaa tehotason halutulle keilaryhmÀlle. Kun mittaustulokset on kerÀtty, se piirtÀÀ lÀmpökartan, joka visualisoi BF:n suorituskyvyn. Mittaukset tehtiin lÀhettÀmÀllÀ eri mÀÀrÀ keiloja eri mittauksessa samalla radioyksiköllÀ. Jokainen sÀteilykuvio mitattiin useita kertoja jÀrjestelmÀn vakauden ja luotettavuuden varmistamiseksi. LÀhetettyjen keilojen lukumÀÀrÀt olivat kaksi, neljÀ ja kuusi. PiirretyistÀ lÀmpökartoista pÀÀteltiin, ettÀ kaikissa mittauksissa kaikki synkronointisignaalilohkon (SSB) keilat olivat nÀkyvissÀ ja SSB-keilojen suunnat olivat kuten odotettu. Kuitenkin kaikissa mittauksissa ensimmÀisen SSB-keilan teho oli hieman pienempi kuin muiden SSB-keilojen, mikÀ viittaa lievÀÀn vikaan keilanmuodostuksessa. Kuten odotettiin, kahdella lÀhetetyllÀ SSB-keilalla puolen tehon kaistanleveys (HPBW) oli leveÀmpi ja suuntaavuus pienempi kuin neljÀllÀ ja kuudella lÀhetetyllÀ SSB-keilalla. Kun lÀhetettiin vain kaksi SSB-keilaa, havaittiin odottamaton tehon putoaminen toisen antennin kohdalla toisen SSB-keilan mittauksessa. NeljÀllÀ ja kuudella lÀhetetyillÀ SSB-keiloilla oli suunnilleen sama HPBW ja suuntaavuus. Molempien tapauksien sÀteilykuvio oli odotusten mukainen. Kuudella lÀhetetyllÀ keilalla suorituskyky oli parempi kattavuuden suhteen. Keilat olivat myös mittauksessa tiiviimmin yhdessÀ, mikÀ varmistaa, ettÀ kÀyttÀjÀ voi siirtyÀ saumattomasti keilasta toiseen ilman signaali-kohinasuhteen putoamista. Kuudella lÀhetetyllÀ keilalla myös sektoripeitto oli hieman laajempi kuin neljÀllÀ lÀhetetyllÀ keilalla

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

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    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

    On feasibility of the UE power saving signal for the 5G new radio

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    Abstract. The objective of this thesis is to study and evaluate physical layer signals and channels to achieve the user equipment (UE) power saving in the 3rd generation partnership project (3GPP) new radio (NR). The fifth generation (5G) mobile network has strict objectives regarding power consumption and performance. The UE power consumption also has a big impact on the end user’s quality of experience (QoE) and future deployment of NR devices. Therefore, it is very important to study ways to reduce UE power consumption. One feasible power saving technique is the usage of so-called power saving signal or channel, which triggers the UE to transition to the active mode from the power saving mode. The first part of this work provides an overview of general properties of the NR and its physical downlink signals and channels, as well as the UE operation and power consumption in the connected mode. Then, examples of existing power saving techniques are discussed and a new scheme of the wake-up mechanism and the UE power saving signal/wake-up signal (WUS) is described. Lastly, different design options for the power saving signal are described and their detection performance is studied. The power saving signal options of this thesis can be divided into physical downlink control channel (PDCCH) based and sequence-based signals/channels. In the PDCCH based option, the power saving indication is carried as a payload of the PDCCH. Studied sequence-based options are the secondary synchronization signal (SSS), the PDCCH demodulation reference signal (DMRS), the channel state information reference signal (CSI-RS) and a UE-specific sequence that is mapped to all radio resources allocated for the PDCCH. The detection of the latter is done in time domain, and the detection of the other sequences is done in frequency domain. The detection performance of these signals/channels is compared based on link-level simulation results. Simulations were done with a Matlab-based simulator. They show the impact of the frequency- and time-selectivity and implementation impairments. Based on the numerical results, the impact of the UE speed up to 120 km/h and the carrier frequency offset (CFO) up to 400 Hz can be neglected with all the options except CSI-RS. It was shown that the sequence-based WUS options tend to suffer from the frequency-selective radio channel. By making decisions within the channel’s coherence bandwidth and using precoder cycling, the negative impact of the channel can be reduced. With these techniques, PDCCH DMRS outperforms all the other sequence-based options. However, in terms of detection performance, the PDCCH based power saving signal/channel is the most robust option of this set of candidates.PÀÀtelaitteen virransÀÀstösignaalin soveltuvuus 5G:n uuteen radiorajapintaan. TiivistelmĂ€. TĂ€mĂ€n diplomityön tavoitteena on tutkia ja verrata fyysisen kerroksen signaaleja, pÀÀtelaitteen (user equipment, UE) virransÀÀstön toteuttamiseksi 3GPP:n uudessa radiorajapinnassa (New Radio, NR). Viidennen sukupolven (5th generation, 5G) mobiiliverkolla on tiukat tavoitteet virransÀÀstön ja suorituskyvyn osalta. PÀÀtelaitteen virrankulutuksella on myös suuri vaikutus loppukĂ€yttĂ€jĂ€n kokemukseen ja tulevien NR-laitteiden kĂ€yttöönottoon. Siksi onkin erittĂ€in tĂ€rkeÀÀ tutkia mahdollisia tapoja vĂ€hentÀÀ pÀÀtelaitteen virrankulutusta. Yksi mahdollinen virransÀÀstötekniikka on niin sanottu virransÀÀstösignaali, joka herĂ€ttÀÀ pÀÀtelaitteen virransÀÀstötilasta verkkoyhteyteen. Työn ensimmĂ€inen osa kĂ€sittelee NR:n yleisiĂ€ ominaisuuksia, alalinkin fyysisiĂ€ signaaleja ja kanavia, sekĂ€ pÀÀtelaitteen virrankulutusta verkkoyhteydessĂ€. Seuraavaksi kĂ€sitellÀÀn olemassa olevia virransÀÀstötekniikoita, sekĂ€ kĂ€ydÀÀn lĂ€pi uutta herĂ€tys-tyyppistĂ€ mekanismia ja pÀÀtelaitteen virransÀÀstösignaalin/herĂ€tyssignaalin (wake-up signal, WUS) toimintaa. Lopuksi kuvataan erilaisia virransÀÀstösignaalivaihtoehtoja ja tutkitaan niiden havaitsemisen suorituskykyĂ€. Työn virransÀÀstösignaalivaihtoehdot voidaan jakaa alalinkin kontrollikanava- (physical downlink control channel, PDCCH) ja sekvenssipohjaisiin signaaleihin/kanaviin. PDCCH-pohjaisessa vaihtoehdossa virransÀÀstösignaali siirretÀÀn PDCCH:n hyötykuormana. Tutkitut sekvenssipohjaiset vaihtoehdot ovat toissijainen synkronointisignaali (secondary synchronization signal, SSS), PDCCH-demodulaatio-referenssisignaali (demodulation reference signal, DMRS), kanavan tilatieto-referenssisignaali (channel-state information reference signal, CSI-RS), sekĂ€ UE-spesifinen sekvenssi, joka asetetaan PDCCH:n jokaiseen alikantoaaltoon. JĂ€lkimmĂ€isen havaitseminen tehdÀÀn aikatasossa ja muiden sekvenssien havaitseminen tehdÀÀn taajuustasossa. NĂ€iden signaalien/kanavien havaitsemisen suorituskykyĂ€ vertaillaan linkkitason simulointitulosten perusteella. Simulaatiot tehtiin Matlab-pohjaisella simulaattorilla. Ne esittĂ€vĂ€t aika- ja taajuusselektiivisyyden, sekĂ€ toteutuksen epĂ€ideaalisuuksien vaikutusta. Numeeristen tulosten perusteella, UE:n nopeus arvoon 120 km/h ja kantoaaltotaajuussiirto (carrier frequency offset, CFO) 400 Hz:iin asti voidaan jĂ€ttÀÀ huomioimatta, kaikkien muiden paitsi CSI-RS:n tapauksessa. TyössĂ€ osoitettiin, ettĂ€ sekvenssipohjaiset WUS-vaihtoehdot kĂ€rsivĂ€t taajuusselektiivisestĂ€ radiokanavasta. Kanavan negatiivista vaikutusta voidaan pienentÀÀ tekemĂ€llĂ€ pÀÀtöksiĂ€ kanavan koherenssikaistanleveyttĂ€ pienemmissĂ€ osissa, sekĂ€ kĂ€yttĂ€mĂ€llĂ€ syklistĂ€ esikooderia. NĂ€illĂ€ tekniikoilla PDCCH DMRS suoriutuu kaikkia muita sekvenssipohjaisia vaihtoehtoja paremmin. Kuitenkin, havaitsemisen suorituskyvyn perusteella PDCCH-pohjainen virransÀÀstösignaali/kanava on vahvin ehdokas nĂ€istĂ€ vaihtoehdoista
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