Efficient Fast-Convolution-Based Waveform Processing for 5G Physical Layer

This paper investigates the application of fast-convolution (FC) filtering schemes for flexible and effective waveform generation and processing in the fifth generation (5G) systems. FC-based filtering is presented as a generic multimode waveform processing engine while, following the progress of 5G new radio standardization in the Third-Generation Partnership Project, the main focus is on efficient generation and processing of subband-filtered cyclic prefix orthogonal frequency-division multiplexing (CP-OFDM) signals. First, a matrix model for analyzing FC filter processing responses is presented and used for designing optimized multiplexing of filtered groups of CP-OFDM physical resource blocks (PRBs) in a spectrally well-localized manner, i.e., with narrow guardbands. Subband filtering is able to suppress interference leakage between adjacent subbands, thus supporting independent waveform parametrization and different numerologies for different groups of PRBs, as well as asynchronous multiuser operation in uplink. These are central ingredients in the 5G waveform developments, particularly at sub-6-GHz bands. The FC filter optimization criterion is passband error vector magnitude minimization subject to a given subband band-limitation constraint. Optimized designs with different guardband widths, PRB group sizes, and essential design parameters are compared in terms of interference levels and implementation complexity. Finally, extensive coded 5G radio link simulation results are presented to compare the proposed approach with other subband-filtered CP-OFDM schemes and time-domain windowing methods, considering cases with different numerologies or asynchronous transmissions in adjacent subbands. Also the feasibility of using independent transmitter and receiver processing for CP-OFDM spectrum control is demonstrated

DECT-2020 New Radio: The Next Step Towards 5G Massive Machine-Type Communications

Massive machine type communications (mMTC) is one of the cornerstone services that have to be supported by 5G systems. 3GPP has already introduced LTE-M and NB-IoT, often referred to as cellular IoT, in 3GPP Releases 13, 14, and 15 and submitted these technologies as part of 3GPP IMT-2020 (i.e., 5G) technology submission to ITU-R. Even though NB-IoT and LTE-M have shown to satisfy 5G mMTC requirements defined by ITU-R, it is expected that these cellular IoT solutions will not address all aspects of IoT and ongoing digitalization, including the support for direct communication between "things" with flexible deployments, different business models, as well as support for even higher node densities and enhanced coverage. In this paper, we introduce the DECT-2020 standard recently published by ETSI for mMTC communications. We evaluate its performance and compare it to the existing LPWAN solutions showing that it outperforms those in terms of supported density of nodes while still keeping delay and loss guarantees at the required level.Comment: Author-Submitted Paper to IEEE Communications Magazine, 7 pages, 4 figures, 2 table

Fast Real-World Implementation of a Direction of Arrival Method for Constrained Embedded IoT Devices

Direction of arrival (DOA) methods are found in many applications, and in the case of the Internet of Things (IoT), it is used for indoor localization. However, the implementation of DOA in IoT devices poses a real challenge, since they are computationally expensive complex numerical methods that could easily lead to resource starvation, unacceptable execution time, and rapid depletion of batteries of small constrained embedded systems typically found in IoT networks. This paper contributes to alleviating that problem, it presents a fast low-power optimized version of a DOA method called Unitary TLS ESPRIT. The optimization exploits the radio communication system design to avoid two time-consuming executions of eigendecomposition, and instead, it applies two simple Power Method algorithms. The result is a lightweight version of ESPRIT that can attain sub-millisecond execution time. To prove the solution’s viability, we carried out experiments on energy consumption, memory footprint, accuracy, and execution time for three floating-point formats in a commercial constrained embedded IoT device series without any operating system and software layers. Experiments show the solution satisfies the hardware requirements and the floating-point precision fully operated by the Floating-Point Unit is found to be the best option.acceptedVersionPeer reviewe

Performance Assessment of DECT-2020 NR and Classic DECT Coexistence Mechanisms

The recently standardized ETSI DECT-2020 New Radio (NR) technology promises to enable operator-independent Internet-of-Things (IoT) services. One of the supported operating bands is the 1880 - 1900 MHz band where IoT devices use one or more 1.728 MHz wide channels for multi-hop communications. It has been shown that such systems scale well to satisfy the requirements of 5G massive machine-type communications (mMTC). During the standardization process, the coexistence with classic DECT technology was addressed but the benefits of different options have not been deeply explored. In this paper, by utilizing system-level simulation techniques we evaluate several coexistence solutions for DECT-2020 and classic DECT systems including conventional listen-before-talk access (LBT), last-minute scan, and scheduling-based mechanisms. Our numerical results illustrate that the standard LBT operation ensures excellent performance with no more than 2% of packet drops for classic DECT, and still results in satisfactory DECT-2020 operation under 25% of resources allocated to classic DECT. The use of last-minute-scan leads to drastic performance degradation of DECT-2020 (by more than 10% in terms of packet drops) as compared to the standard LBT-only operation. Finally, a scheduling-based mechanism allows to improve the LBT performance for DECT-2020 devices by 2-5%.Peer reviewe

Direction of Arrival Method for L-Shaped Array with RF Switch : An Embedded Implementation Perspective

This paper addresses the challenge of implementing Direction of Arrival (DOA) methods for indoor localization using Internet of Things (IoT) devices, particularly with the recent direction- finding capability of Bluetooth. DOA methods are complex numerical methods that require significant computational resources and can quickly deplete the batteries of small embedded systems typically found in IoT networks. To address this challenge, the paper presents a novel Unitary R-D Root MUSIC for L-shaped arrays that is tailor-made for such devices utilizing a switching protocol defined by Bluetooth. The solution exploits the radio communication system design to speed up execution, and its root-finding method circumvents complex arithmetic despite being used for complex polynomials. The paper carries out experiments on energy consumption, memory footprint, accuracy, and execution time in a commercial constrained embedded IoT device series without operating systems and software layers to prove the viability of the implemented solution. The results demonstrate that the solution achieves good accuracy and attains an execution time of a few milliseconds, making it a viable solution for DOA implementation in IoT devices.Peer reviewe

Lautapelin kääntäminen mobiilialustalle ja konversioiden käytettävyys

Opinnäytetyöni tarkoituksena on tutkia lautapelin kääntämistä mobiilialustalle ja kääntämisprosessin eri vaiheita. Kääntämisprosessi toteutettiin Unity 3D:tä käyttäen ja siinä käytetään C# -ohjelmointikieltä. Opinnäytetyön teoriaosuudessa keskitytään lautapelikonversioiden historiaan ja nykytilanteeseen. Opinnäytetyössä kerrotaan myös siitä, onko lautapelikäännösten tekeminen kannattavaa ja miksi näin on. Lisäksi työssä käydään läpi myös konversioissa ilmeneviä ongelmia mobiilialustoja käytettäessä. Teknisessä osuudessa käytetään esimerkkinä Arkham Horror -lautapelistä tehtyä käännöstä ja siinä kiinnitetään huomiota siihen, kuinka pelistä voidaan tehdä mobiilialustoilla toimiva. Työssä käydään myös läpi konversion tekemisessä olevat vaiheet ja lopullisessa konversiossa olevat mekaniikat. Opinnäytetyön tuloksena syntyi toimiva lautapelikonversio Android Horror, jota voidaan pelata yksinpelinä erilaisilla Android-mobiililaitteilla.The purpose of my thesis is to study the conversion of board games to a mobile platform and to examine the different phases of the conversion process. The conversion was carried out by using Unity 3D and C# -programming language was used in it. In the theoretical part of the thesis, the focus is set to the history of board game conversions and to their current state. The profitability of the board game conversions is also discussed. The problems occurring in the conversions whilst using mobile platforms will be also dealt with. In the technical part a conversion of Arkham Horror will be used, which was made as an example and the focus is set on how to make a working game for mobile platforms. The phases of conversion making and the mechanics in the final version of the conversion are also covered. The result of the project was a game called Android Horror, which can be played in single player on different Android-mobile devices

Keypro Oy:n tukiprosessien sujuvuuden kehittäminen Lean-menetelmien avulla

Tämä opinnäytetyö perehtyy Keypro Oy:n tukitiimin toimintaan ja selvittää kuinka nykyistä tukiprosessia voitaisiin parantaa laatujohtamisen menetelmillä. Työn tarkoituksena oli vähentää tukitikettien läpivientiin menevää aikaa ja täten vähentää SLA-rikkeiden määrää. Kehittämistyö tehtiin toimintatutkimuksena, jonka apuna käytettiin kyselyä, seminaareja ja aivoriihtä. Kyselyllä selvitettiin alkutilannetta, seminaareilla levitettiin tietoa ja aivoriihessä kerättiin ratkaisuvaihtoehtoja prosessin kehittämiseen. Prosessikehityksen apuvälineinä käytettiin Lean, Six sigma ja Lean six sigma menetelmiin kuuluvaa DMAIC-prosessikehitystyökalua. Opinnäytetyön tuloksena saatiin valmis DMAIC-lomake, jonka avulla saatiin parannettua tukitikettien läpimenoaikoja verrattuna vuotta aiempaan tilanteeseen. Tuloksena valmistui osittain myös sisäinen ohjekirja, jota voidaan käyttää apuna tukitikettien ratkaisussa ja henkilöstön kouluttamisessa

Transparent Tx and Rx Waveform Processing for 5G New Radio Mobile Communications

Several different waveform processing techniques have been studied and proposed for the 5G new radio (NR) physical layer, to support new mixed numerology and asynchronous services. The evaluation and comparison of these different techniques is commonly based on matched waveform processing in the transmitter and receiver units. In this article, it is shown that different techniques can be flexibly mixed, making it possible to separately optimize complexity-performance trade-offs for transmitter and receiver implementations. Mixing different waveform processing techniques is possible by setting adequate requirements for transmitter and receiver baseband processing allowing transparent design. We provide the basic framework of how transmitter and receiver units can be independently applied and evaluated in the context of transparent design and an extensive set of examples of the achievable radio link performance with unmatched transmitter and receiver waveform processing. The discussed approach and solutions simplify standardization, improve transparent transmitter and receiver coexistence, and enable a future-proof evolution path for performance improvements in 5G NR physical layer hardware and algorithm design.acceptedVersionPeer reviewe

Implementation of Embedded Multiple Signal Classification Algorithm for Mesh IoT Networks

Angle-of-Arrival (AoA) methods are an Internet of Things (IoT) application, which could be used, for example, in indoor localization. Anchor nodes have an array of antennas and could send the data via Ethernet cable to the cloud that calculates AoA. However, having cable connections means high installation costs, and constantly transferring big chunks of data over some IoT networks, such as mesh, is energy inefficient. The solution of this paper consists in executing AoA locally in anchor nodes. Thus, the paper presents an implementation of a Multiple Signal Classification (MUSIC) algorithm tailor- made for embedded system devices. It calculates a complex eigendecomposition via an equivalent real formulation. It has a detailed memory analysis of the implemented solution that shows its memory requirements satisfy commercial embedded systems for IoT, such as Nordic semiconductor System-on-Chip (SoC) of nRF52 Series and all their SoCs with direction-finding capability. Experiments show that reducing the floating-point precision to shrink its memory footprint does not impact the accuracy. It also shows that minimizing the execution time of its time-consuming peak-finding operation has a few effects on accuracy.acceptedVersionPeer reviewe