Practical packet combining for use with cooperative and non-cooperative ARQ schemes in wireless sensor networks

Although it is envisaged that advances in technology will follow a "Moores Law" trend for many years to come, one of the aims of Wireless Sensor Networks (WSNs) is to reduce the size of the nodes as much as possible. The issue of limited resources on current devices may therefore not improve much with future designs as a result. There is a pressing need, therefore, for simple, efficient protocols and algorithms that can maximise the use of available resources in an energy efficient manner. In this thesis an improved packet combining scheme useful on low power, resource-constrained sensor networks is developed. The algorithm is applicable in areas where currently only more complex combining approaches are used. These include cooperative communications and hybrid-ARQ schemes which have been shown to be of major benefit for wireless communications. Using the packet combining scheme developed in this thesis more than an 85% reduction in energy costs are possible over previous, similar approaches. Both simulated and practical experiments are developed in which the algorithm is shown to offer up to approximately 2.5 dB reduction in the required Signal-to-Noise ratio (SNR) for a particular Packet Error Rate (PER). This is a welcome result as complex schemes, such as maximal-ratio combining, are not implementable on many of the resource constrained devices under consideration. A motivational side study on the transitional region is also carried out in this thesis. This region has been shown to be somewhat of a problem for WSNs. It is characterised by variable packet reception rate caused by a combination of fading and manufacturing variances in the radio receivers. Experiments are carried out to determine whether or not a spread-spectrum architecture has any effect on the size of this region, as has been suggested in previous work. It is shown that, for the particular setup tested, the transitional region still has significant extent even when employing a spread-spectrum architecture. This result further motivates the need for the packet combining scheme developed as it is precisely in zones such as the transitional region that packet combining will be of most benefit

物理層に着目した産業用高信頼リアルタイム無線通信に関する研究

学位の種別: 課程博士審査委員会委員 : （主査）東京大学教授 森川 博之, 東京大学准教授 中山 雅哉, 東京大学教授 相田 仁, 東京大学准教授 川原 圭博, 東京大学教授 廣瀬 明University of Tokyo(東京大学

Hybrid Digital-to-Analog Beamforming for Millimeter-Wave Systems with High User Density

Millimeter-wave (mm-Wave) systems with hybrid digital-to-analog beamforming (D-A BF) have the potential to fulfill 5G traffic demands. The capacity of mmWave systems is severely limited as each radio frequency (RF) transceiver chain in current base station (BS) architectures support only a particular user. In order to overcome this problem when high density of users are present, a new algorithm is proposed in this paper. This algorithm operates on the principle of selection combining (SC). This algorithm is compared with the state of the art hybrid D-A BF. The simulation results show that our proposed hybrid D-A BF using SC supports higher density of users per RF chain. Furthermore, our proposed algorithm achieves higher capacity than what is achieved by the current hybrid D-A BF systems

Cooperative MIMO Communications in Wireless Sensor Networks: Energy Efficient Cooperative MAC Protocol

Multiple sensor nodes can be used to transmit and receive cooperatively and such a configuration is known as a cooperative Multiple-Input Multiple-Output (MIMO) system. Cooperative MIMO systems have been proven to reduce both transmission energy and latency in Wireless Sensor Networks (WSNs). However, most current work in WSNs considers only the energy cost for the data transmission component and neglects the energy component responsible for establishing a cooperative mechanism. In this work, both transmission and circuit energies for both components are included in the performance models. Furthermore, in previous work, all sensor nodes are assumed to be always on which could lead to a shorter lifetime due to energy wastage caused by idle listening and overhearing. Low duty cycle MAC protocols have been proposed to tackle this challenge for non-cooperative systems. Also in this work, we propose a new cooperative low duty cycle MAC protocol (CMAC) for two cooperative MIMO schemes: Beamforming (CMACBF) and Spatial Multiplexing (CMACSM). Performance of the proposed CMAC protocol is evaluated in terms of total energy consumption and packet latency for both synchronous and asynchronous scenarios. All the required energy components are taken into consideration in the system performance modeling and a periodic monitoring application model is used. The impact of the clock jitter, the check interval and the number of cooperative nodes on the total energy consumption and latency is investigated. The CMACBF protocol with two transmit nodes is suggested as the optimal scheme when operating at the 250 ms check interval with the clock jitter difference below 0.6Tb where Tb is the bit period corresponding to the system bit rate

Zero-padding Network Coding and Compressed Sensing for Optimized Packets Transmission

Ubiquitous Internet of Things (IoT) is destined to connect everybody and everything on a never-before-seen scale. Such networks, however, have to tackle the inherent issues created by the presence of very heterogeneous data transmissions over the same shared network. This very diverse communication, in turn, produces network packets of various sizes ranging from very small sensory readings to comparatively humongous video frames. Such a massive amount of data itself, as in the case of sensory networks, is also continuously captured at varying rates and contributes to increasing the load on the network itself, which could hinder transmission efficiency. However, they also open up possibilities to exploit various correlations in the transmitted data due to their sheer number. Reductions based on this also enable the networks to keep up with the new wave of big data-driven communications by simply investing in the promotion of select techniques that efficiently utilize the resources of the communication systems. One of the solutions to tackle the erroneous transmission of data employs linear coding techniques, which are ill-equipped to handle the processing of packets with differing sizes. Random Linear Network Coding (RLNC), for instance, generates unreasonable amounts of padding overhead to compensate for the different message lengths, thereby suppressing the pervasive benefits of the coding itself. We propose a set of approaches that overcome such issues, while also reducing the decoding delays at the same time. Specifically, we introduce and elaborate on the concept of macro-symbols and the design of different coding schemes. Due to the heterogeneity of the packet sizes, our progressive shortening scheme is the first RLNC-based approach that generates and recodes unequal-sized coded packets. Another of our solutions is deterministic shifting that reduces the overall number of transmitted packets. Moreover, the RaSOR scheme employs coding using XORing operations on shifted packets, without the need for coding coefficients, thus favoring linear encoding and decoding complexities. Another facet of IoT applications can be found in sensory data known to be highly correlated, where compressed sensing is a potential approach to reduce the overall transmissions. In such scenarios, network coding can also help. Our proposed joint compressed sensing and real network coding design fully exploit the correlations in cluster-based wireless sensor networks, such as the ones advocated by Industry 4.0. This design focused on performing one-step decoding to reduce the computational complexities and delays of the reconstruction process at the receiver and investigates the effectiveness of combined compressed sensing and network coding

Radio resource allocation for overlay D2D-based vehicular communications in future wireless networks

Mobilfunknetze der nächsten Generation ermöglichen einen weitverbreiteten Einsatz von Device-to-Device Kommunikation, der direkten Kommunikation zwischen zellularen Endgeräten. Für viele Anwendungsfälle zur direkten Kommunikation zwischen Endgeräten sind eine deterministische Latenz und die hohe Zuverlässigkeit von zentraler Bedeutung. Dienste zur direkten Kommunikation (D2D) für in der Nähe befindliche Endgeräte sind vielversprechend die hohen Anforderungen an Latenz und Zuverlässigkeit für zukünftige vertikale Anwendungen zu erfüllen. Eine der herausragenden vertikalen Anwendungen ist die Fahrzeugkommunikation, bei der die Fahrzeuge sicherheitskritische Meldungen direkt über D2D-Kommunikation austauschen, die dadurch zur Reduktion von Verkehrsunfällen und gleichzeitig von Todesfällen im Straßenverkehrt beiträgt. Neue Techniken zur effizienteren Zuweisung von Funkressourcen in der D2D-Kommunikation haben in letzter Zeit in Industrie und Wissenschaft große Aufmerksamkeit erlangt. Zusätzlich zur Allokation von Ressourcen, wird die Energieeffizienz zunehmend wichtiger, die normalerweise im Zusammenhang mit der Ressourcenallokation behandelt wird. Diese Dissertation untersucht verschiedener Ansätze der Funkressourcenzuweisung und Energieeffizienztechniken in der LTE und NR V2X Kommunikation. Im Folgenden beschreiben wir kurz die Kernideen der Dissertation. Meist zeichnen sich D2D-Anwendungen durch ein relativ geringes Datenvolumen aus, die über Funkressourcen übertragen werden. In LTE können diese Funkressourcen aufgrund der groben Granularität für die Ressourcenzuweisung nicht effizient genutzt werden. Insbesondere beim semi-persistenten Scheduling, bei dem eine Funkressource über einen längeren Zeitraum im Overlay D2D festgelegt wird, sind die Funkressourcen für solche Anwendungen nicht ausgelastet. Um dieses Problem zu lösen, wird eine hierarchische Form für das Management der Funkressourcen, ein sogenanntes Subgranting-Schema, vorgeschlagen. Dabei kann ein nahegelegener zellularer Nutzer, der sogenannte begünstigte Nutzer, ungenutzten Funkressourcen, die durch Subgranting-Signalisierung angezeigt werden, wiederzuverwenden. Das vorgeschlagene Schema wird bewertet und mit "shortening TTI", einen Schema mit reduzierten Sendezeitintervallen, in Bezug auf den Zellendurchsatz verglichen. Als nächster Schritt wird untersucht, wie der begünstigten Benutzer ausgewählt werden kann und als Maximierungsproblem des Zellendurchsatzes im Uplink unter Berücksichtigung von Zuverlässigkeits- und Latenzanforderungen dargestellt. Dafür wird ein heuristischer zentralisierter, d.h. dedizierter Sub-Granting-Radio-Ressource DSGRR-Algorithmus vorgeschlagen. Die Simulationsergebnisse und die Analyse ergeben in einem Szenario mit stationären Nutzern eine Erhöhung des Zelldurchsatzes bei dem Einsatz des vorgeschlagenen DSGRR-Algorithmus im Vergleich zu einer zufälligen Auswahl von Nutzern. Zusätzlich wird das Problem der Auswahl des begünstigten Nutzers in einem dynamischen Szenario untersucht, in dem sich alle Nutzer bewegen. Wir bewerten den durch das Sub-Granting durch die Mobilität entstandenen Signalisierungs-Overhead im DSGRR. Anschließend wird ein verteilter Heuristik-Algorithmus (OSGRR) vorgeschlagen und sowohl mit den Ergebnissen des DSGRR-Algorithmus als auch mit den Ergebnissen ohne Sub-Granting verglichen. Die Simulationsergebnisse zeigen einen verbesserten Zellendurchsatz für den OSGRR im Vergleich zu den anderen Algorithmen. Außerdem ist zu beobachten, dass der durch den OSGRR entstehende Overhead geringer ist als der durch den DSGRR, während der erreichte Zellendurchsatz nahe am maximal erreichbaren Uplink-Zellendurchsatz liegt. Zusätzlich wird die Ressourcenallokation im Zusammenhang mit der Energieeffizienz bei autonomer Ressourcenauswahl in New Radio (NR) Mode 2 untersucht. Die autonome Auswahl der Ressourcen wird als Verhältnis von Summenrate und Energieverbrauch formuliert. Das Ziel ist den Stromverbrauch der akkubetriebenen Endgeräte unter Berücksichtigung der geforderten Zuverlässigkeit und Latenz zu minimieren. Der heuristische Algorithmus "Density of Traffic-based Resource Allocation (DeTRA)" wird als Lösung vorgeschlagen. Bei dem vorgeschlagenen Algorithmus wird der Ressourcenpool in Abhängigkeit von der Verkehrsdichte pro Verkehrsart aufgeteilt. Die zufällige Auswahl erfolgt zwingend auf dem dedizierten Ressourcenpool beim Eintreffen aperiodischer Daten. Die Simulationsergebnisse zeigen, dass der vorgeschlagene Algorithmus die gleichen Ergebnisse für die Paketempfangsrate (PRR) erreicht, wie der sensing-basierte Algorithmus. Zusätzlich wird der Stromverbrauch des Endgeräts reduziert und damit die Energieeffizienz durch die Anwendung des DeTRA-Algorithmus verbessert. In dieser Arbeit werden Techniken zur Allokation von Funkressourcen in der LTE-basierten D2D-Kommunikation erforscht und eingesetzt, mit dem Ziel Funkressourcen effizienter zu nutzen. Darüber hinaus ist der in dieser Arbeit vorgestellte Ansatz eine Basis für zukünftige Untersuchungen, wie akkubasierte Endgeräte mit minimalem Stromverbrauch in der NR-V2X-Kommunikation Funkressourcen optimal auswählen können.Next-generation cellular networks are envisioned to enable widely Device-to-Device (D2D) communication. For many applications in the D2D domain, deterministic communication latency and high reliability are of exceptionally high importance. The proximity service provided by D2D communication is a promising feature that can fulfil the reliability and latency requirements of emerging vertical applications. One of the prominent vertical applications is vehicular communication, in which the vehicles disseminate safety messages directly through D2D communication, resulting in the fatality rate reduction due to a possible collision. Radio resource allocation techniques in D2D communication have recently gained much attention in industry and academia, through which valuable radio resources are allocated more efficiently. In addition to the resource allocation techniques, energy sustainability is highly important and is usually considered in conjunction with the resource allocation approach. This dissertation is dedicated to studying different avenues of the radio resource allocation and energy efficiency techniques in Long Term Evolution (LTE) and New Radio (NR) Vehicle-to-Everythings (V2X) communications. In the following, we briefly describe the core ideas in this study. Mostly, the D2D applications are characterized by relatively small traffic payload size, and in LTE, due to coarse granularity of the subframe, the radio resources can not be utilized efficiently. Particularly, in the case of semi-persistent scheduling when a radio resource is scheduled for a longer time in the overlay D2D, the radio resources are underutilized for such applications. To address this problem, a hierarchical radio resource management scheme, i.e., a sub-granting scheme, is proposed by which nearby cellular users, i.e., beneficiary users, are allowed to reuse the unused radio resource indicated by sub-granting signaling. The proposed scheme is evaluated and compared with shortening Transmission Time Interval (TTI) schemes in terms of cell throughput. Then, the beneficiary user selection problem is investigated and is cast as a maximization problem of uplink cell throughput subject to reliability and latency requirements. A heuristic centralized, i.e., dedicated sub-granting radio resource Dedicated Sub-Granting Radio Resource (DSGRR) algorithm is proposed to address the original beneficiary user selection problem. The simulation results and analysis show the superiority of the proposed DSGRR algorithm over the random beneficiary user selection algorithm in terms of the cell throughput in a scenario with stationary users. Further, the beneficiary user selection problem is investigated in a scenario where all users are moving in a dynamic environment. We evaluate the sub-granting signaling overhead due to mobility in the DSGRR, and then a distributed heuristics algorithm, i.e., Open Sub-Granting Radio Resource (OSGRR), is proposed and compared with the DSGRR algorithm and no sub-granting case. Simulation results show improved cell throughput for the OSGRR compared with other algorithms. Besides, it is observed that the overhead incurred by the OSGRR is less than the DSGRR while the achieved cell throughput is yet close to the maximum achievable uplink cell throughput. Also, joint resource allocation and energy efficiency in autonomous resource selection in NR, i.e. Mode 2, is examined. The autonomous resource selection is formulated as a ratio of sum-rate and energy consumption. The objective is to minimize the energy efficiency of the power-saving users subject to reliability and latency requirements. A heuristic algorithm, density of traffic-based resource allocation (DeTRA), is proposed to solve the problem. The proposed algorithm splits the resource pool based on the traffic density per traffic type. The random selection is then mandated to be performed on the dedicated resource pool upon arrival of the aperiodic traffic is triggered. The simulation results show that the proposed algorithm achieves the same packet reception ratio (PRR) value as the sensing-based algorithm. In addition, per-user power consumption is reduced, and consequently, the energy efficiency is improved by applying the DeTRA algorithm. The research in this study leverages radio resource allocation techniques in LTE based D2D communications to be utilized radio resources more efficiently. In addition, the conducted research paves a way to study further how the power-saving users would optimally select the radio resources with minimum energy consumption in NR V2X communications