Massive MIMO for Internet of Things (IoT) Connectivity

Massive MIMO is considered to be one of the key technologies in the emerging 5G systems, but also a concept applicable to other wireless systems. Exploiting the large number of degrees of freedom (DoFs) of massive MIMO essential for achieving high spectral efficiency, high data rates and extreme spatial multiplexing of densely distributed users. On the one hand, the benefits of applying massive MIMO for broadband communication are well known and there has been a large body of research on designing communication schemes to support high rates. On the other hand, using massive MIMO for Internet-of-Things (IoT) is still a developing topic, as IoT connectivity has requirements and constraints that are significantly different from the broadband connections. In this paper we investigate the applicability of massive MIMO to IoT connectivity. Specifically, we treat the two generic types of IoT connections envisioned in 5G: massive machine-type communication (mMTC) and ultra-reliable low-latency communication (URLLC). This paper fills this important gap by identifying the opportunities and challenges in exploiting massive MIMO for IoT connectivity. We provide insights into the trade-offs that emerge when massive MIMO is applied to mMTC or URLLC and present a number of suitable communication schemes. The discussion continues to the questions of network slicing of the wireless resources and the use of massive MIMO to simultaneously support IoT connections with very heterogeneous requirements. The main conclusion is that massive MIMO can bring benefits to the scenarios with IoT connectivity, but it requires tight integration of the physical-layer techniques with the protocol design.Comment: Submitted for publicatio

UAV-enabled wireless-powered Iot wireless sensor networks

Future massive internet of thing (IoT) networks will enable the vision of smart cities, where it is anticipated that a massive number of sensor devices, in the order of tens of millions devices, ubiquitously deployed to monitor the environment. Main challenges in such a network are how to improve the network lifetime and design an e cient data aggregation process. To improve the lifetime, using low-power passive sensor devices have recently shown great potential. Ambient backscattering is a novel technology which provides low-power long-range wireless communication expanding the network lifetime signi cantly. On the other hand, in order to collect the sensed data from sensor devices deployed over a wide area, unmanned aerial vehicles (UAVs) has been considered as a promising technology, by leveraging the UAV's high mobility and line-of-sight (LOS) dominated air-ground channels. The UAV can act as data aggregator collecting sensed data from all sensors. In this thesis, we consider medium-access control (MAC) policies for two sensor data collection scenarios. First, the objective is to collect individual sensor data from the eld. The challenge in this case is to determine how a large number of sensors should access the medium so that data aggregation process performed in a fast and reliable fashion. Utilizing conventional orthogonal medium access schemes (e.g., time-division vi multiple access (TDMA) and frequency-division multiple access (FDMA)), is highly energy consuming and spectrally ine cient. Hence, we employ non-orthogonal multiple access (NOMA) which is envisaged as an essential enabling technology for 5G wireless networks especially for uncoordinated transmissions. In Chapter 2, we develop a framework where the UAV is used as a replacement to conventional terrestrial data collectors in order to increase the e ciency of collecting data from a eld of passive backscatter sensors, and simultaneously it acts as a mobile RF carrier emitter to activate backscatter sensors. In the MAC layer, we employ uplink power-domain NOMA scheme to e ectively serve a large number of passive backscatter sensors. Our objective is to optimize the path, altitude, and beamwidth of the UAV such that the network throughput is maximized. In Chapter 3, we consider the scenario where there are a separate data collector and RF carrier emitter such that the former is a gateway on the ground and the latter is a single UAV hovering over the eld of backscatter sensors. Secondly, we consider a case where only a function of sensed data is of interest rather than individual sensor values. A new challenge arises where the problem is to design a communication policy to improve the accuracy of the estimated function. Recently, over-the-air computation (AirComp) has emerged to be a promising solution to enable merging computation and communication by utilizing the superposition property of wireless channels, when a function of measurements are desired rather than individual in massive IoT sensor networks. One of the key challenges in AirComp is to compensate the e ects of channel. Motivated by this, in Chapter 4, we propose a UAV assisted communication framework to tackle this problem by a simple to implement sampling-then-mapping mechanism

Disaster warning system: Satellite feasibility and comparison with terrestrial systems. Volume 2: Final report

For abstract, see Vol. 1

Models of Control Channels in the LTE System

Dizertační práce se zabývá zpracováním signálu fyzických řídicích kanálů systému LTE a vyšetřováním bitové chybovosti při přenosu řídicí informace z vysílače do přijímače v závislosti na podmínkách příjmu. Práce je rozdělena do dvou hlavních částí. První část práce je zaměřena na simulaci přenosu řídicí informace LTE v základním pásmu. Jsou zde prezentovány vytvořené simulátory řídicích kanálů ve směru uplink i downlink. Simulace jsou provedeny pro všechny druhy nastavení systému a základní modely přenosového prostředí. Jsou zde popsány výsledky vlivu použití MIMO technologií na kvalitu příjmu řídicí informace především v únikových kanálech. Druhá část práce je zaměřena na možnost nasazení systému LTE ve sdíleném pásmu ISM (2.4 GHz). Jsou zde představeny základní koncepce použití, na jejichž základě je vytvořen scénář simulací. Kapitola dále popisuje tvorbu simulátoru koexistence LTE a systému Wi-Fi v přeneseném pásmu ISM 2.4GHz. Jsou zde uvedeny výsledky simulací koexistence LTE a rušivého systému Wi-Fi provedených dle vytvořeného scénáře. Výsledky simulací koexistence LTE a Wi-Fi jsou ověřeny měřením v laboratorních podmínkách. Toto porovnání je důležité z hlediska optimalizace simulátoru koexistence. Dle výsledků obou typů simulací a měření jsou stanovena provozní doporučení, která mají přispět k bezpečnému a spolehlivému vysílání a příjmu řídicích informací LTE i při nepříznivých podmínkách příjmu.The doctoral thesis is focused on a signal processing in the LTE physical control channels and performance analysis of control information transmission according to receiving conditions. The thesis is divided into two parts. The first part deals with simulation of the transmission of control information in baseband. The created simulators for uplink and downlink are presented. The simulations are performed for all possible system settings and various channel models. The MIMO influence on a quality of control information reception under fading channels is also presented. The second part of the thesis is focused on LTE utilization in shared channel ISM (2.4 GHz). The basic LTE application concept for ISM band is presented. This concept is fundamental to created simulation scenario. The chapter also presents the LTE and Wi-Fi coexistence simulator in 2.4 GHz ISM passband. The coexistence simulation are presented according to simulation scenario and the results are shown. The simulated coexistence analysis results are verified in laboratory environment. The comparison of the simulated and the measured coexistence analysis results is crucial for further optimization of the coexistence simulator. Recommendations for optimal and reliable operation of LTE are specified according to the simulated and the measured results. Recommendations should be useful to the reliable transmission of LTE control information in bad receiving conditions.