The future mobile communication networks are expected to cope with growing local usage patterns especially in dense urban areas at more affordable deployment and operation expenses. Beyond leveraging small cell architectures and advanced radio access technologies; more radio spectrum are expected to be required to achieve the desired techno-economic targets. However, securing efficient radio spectrum resources remain a challenging task especially in the bands with favored propagation characteristics. Therefore, the research activity has been directed towards discussing the benefits and needs for more flexible and local spectrum authorization schemes. This thesis work is meant to be a contribution to this ongoing discussion from a techno-economic perspective  that aim to investigate three main questions: (i) how can the need for and benefit of local spectrum authorization schemes be valued from the perspective of established mobile network operators, and (ii) Will the shift towards more flexible and local spectrum authorization schemes impact the existing mobile service ecosystem and in what manner. In chapter three, the role and value of the different local spectrum authorization schemes in shaping an economic viable provision strategy for the targeted local mobile services in future dense urban areas are investigated. For this purpose, the opportunity cost approach is used to evaluate the elasticity of substitution between the spectrum resources and network infrastructure. The main results in chapter three indicate the economic incentives to deploy more small cells based on local spectrum authorization schemes are subject to the additional deployment and operation costs that can be avoided if a macro-cell layer is deployed instead. However, the backhaul links costs and additional radio equipment cost for aggregating spectrum resources in different bands at the small cell level will have high impact on the anticipated  engineering value. Nonetheless; in dense and very dense deployment scenarios of small cells, where the density of radio sites is equal or larger than the active mobile subscribers' density, access more spectrum resources based on local authorization schemes will have a key role in providing the targeted high mean instantaneous data rate per active end-subscriber. Moreover, established actors (e.g. incumbent MNOs) experiencing shortage in their licensed spectrum resources can evaluate the spectrum value base on their ability to offer the targeted mobile services in strategic spotty local areas. While in chapter four, the possible business and cooperation models around local shared spectrum authorization from the perspectives of established mobile network operators (MNOs) and emerging local network operators (LNOs) are identified. From the perspective of an established MNO, the strategic value of the flexible spectrum authorization option could be very high in certain local environments with potential high return on investment (ROI). On the other hand, emerging actors can benefit from the flexible spectrum authorization options to focus on the niche market in certain local areas. Other viable business models for an emerging actor rest with the possibility to enter into different cooperation agreements to deploy and operate dedicated local mobile infrastructure on behalf established mobile network operators; especially in situations where the deployment of mobile networks brings extra activities and overheads to the MNOs.  Moreover, by allowing other actors, rather than the traditional mobile network operators, to access spectrum resource at a reasonable or no cost, one of the major traditional investment barriers in mobile market will be relaxed and consequently more independent business models may emerge. As an example, actors with sufficient technical expertise such as network equipment vendors may exploit local shared spectrum resources to provide tailored local mobile services and enter into different roaming agreements with established mobile network operators. / <p>QC 20170411</p>

At present, Artificial Intelligence (AI) systems have been adopted in many different domains such as healthcare, robotics, automotive, telecommunication systems, security, and finance for integrating intelligence in their services and applications. The intelligent personal assistant such as Siri and Alexa are examples of AI systems making an impact on our daily lives. Since many AI systems are data-driven systems, they require large volumes of data for training and validation, advanced algorithms, computing power and storage in their development process. Collaboration in the AI development process (AI engineering process) will reduce cost and time for the AI applications in the market. However, collaboration introduces the concern of privacy and piracy of intellectual properties, which can be caused by the actors who collaborate in the engineering process.  This work investigates the non-functional requirements, such as privacy and security, for enabling collaboration in AI service chains. It proposes an architectural design approach for collaborative AI engineering and explores the concept of the pipeline (service chain) for chaining AI functions. In order to enable controlled collaboration between AI artefacts in a pipeline, this work makes use of virtualisation technology to define and implement Virtual Premises (VPs), which act as protection wrappers for AI pipelines. A VP is a virtual policy enforcement point for a pipeline and requires access permission and authenticity for each element in a pipeline before the pipeline can be used.  Furthermore, the proposed architecture is evaluated in use-case approach that enables quick detection of design flaw during the initial stage of implementation. To evaluate the security level and compliance with security requirements, threat modeling was used to identify potential threats and vulnerabilities of the system and analyses their possible effects. The output of threat modeling was used to define countermeasure to threats related to unauthorised access and execution of AI artefacts.

Many high-end sophisticated devices are being replaced by small single-board IoT devices. It is estimated that by the year 2025 there will be about 75 billion IoT connected devices worldwide. This project buttresses the earlier statements. The project will be focused on how to deploy a complex AI face-recognition model on a simple, less power consumption, single-board IoT device Raspberry Pi3. Also, to simplify the whole process of deploying the AI model on Raspberry Pi3 by dockerizing. By just pulling the respective docker image and running it on the end device (Raspberry Pi3), we can make face recognition happen. Finally, the obtained results will be sent to the cloud (Fiware) using NGSI API. Instead of sending the whole video feed to the Cloud platform and performing the computing there, we managed to perform the computing at the edge and then send the results to the cloud and making the results accessible to requested users.

No description available.

Compuverde’s software-defined storage product uses multicast for the communication between servers in a cluster. The product makes use of IP UDP multicast for sending status messages between the servers that forms the storage cluster. The storage clusters capacity and performance scales linear to the number of servers in the cluster. The problem is that the multicast traffic also increases with the number of nodes. All nodes send to all other nodes in the cluster. In this document, we present a proposal on evaluation of IP multicast behavior in a network congested with traffic similar to that produced by Compuverde’s product. IP multicast is a method of sending Internet Protocol (IP) datagrams to a group of interested receivers in a single transmission. In order to provide an efficient, timely, and global many-to-many distribution of data, and as such may become the broadcast medium of choice in the future, IP multicasting is used[1]. The main benefit of IP Multicast is that it reduces the bandwidth consumption when data from a sender must reach multiple receivers. We are interested in studying the effects on the network when we send multicast packets at a rate closed to the operational limit of the switch. To be able to study this behavior at larger scale Compuverde’s will provide a cluster with 48 servers all connected to the same switch. In addition, we will compare the behavior of IPv4 multicast traffic to that of IPv6. Aims and Objectives: Our aim of my thesis is mainly to focus on IP multicast and compare the IPv4 multicast performance results to the results from IPv6 multicast. In addition, a C++ tool for generating multicast traffic will be developed on Linux. A detailed study on IP multicast (IPv4, IPv6). Detailed study on the design and efficient implementation of a multicast traffic generating tool. Detailed study on the switch that will be used in the project. Additional switches may be provided by BTH. Detailed study on the pattern of dropped packets when traffic rate approaches operational limit and other related impairments on QoS metrics (e.g., CPU utilization). Methods: The method is to develop a tool that will generate multicast load towards servers in a cluster. The data sent as multicast packets shall consist of information that will make it possible to detect packet loss on the receiving servers if the network gets congested. The first version of the tool shall use existing socket classes that are based on the IPv4 protocol and shall be written in C++. The tool shall be able to run in two modes at the same time: client mode and server mode. The server part of the tool shall subscribe to a predefined multicast address and receive incoming multicast packages. The client part of the tool shall send data packages to the same predefined multicast address at a configurable rate that will increase over time. The data in the packet that will be sent shall be constructed in a way that lets the receiver (server) detect if a packet is lost in transmission. The load should start small with a small number of servers in the cluster, and then in steps scale up the number of servers, until a maximum of 48 servers is reached. The rate that the multicast packets is sent should also be increased, until the switch gets overloaded and starts to drop packets. The pattern of how packets are dropped should be observed. For example such as, if it is biggerlarge chunks of packets that get dropped or if it is every second packet that gets dropped. The second version of the tool shall support IPv6 multicast. The second round of tests should be performed in a way that makes them comparable to the results from the IPv4 tests so it is possible to draw conclusions if one protocol performs better or is more reliable. Result: The maximum number of IPv4 packets a switch can handle is 140 packets per second. The maximum number of IPv6 packets a switch can handle is 6 packets per second. The CPU utilization is more while multicasting the IPv4 packets than while multicasting IPv6 packets by using switch, 95 Nodes. Conclusion: The IPv4 is most efficient protocol than IPv6 protocol while sending the packets at very high data rate. The CPU utilization is more higher for sending with the IPv6 protocol packets than with the IPv4 protocol. / <p>no</p>

With the advent of new 5G networks, the interest in connecting house-hold to the Internet via mobile networks has increased. One such way toconnect users is using completely stationary antennas. This use-case iscalled Fixed Wireless Access (FWA) and is seen as promising, cost-efficient means of expanding internet connectivity. Stationary users connected at high frequencies, such as 28 GHz, leads to a special use-case and environment for 5G New Radio (NR). This thesis investigates the characteristics of these FWA deployments and the control signaling on the physical layer of NR. The overhead and feasibility of eachsignal is considered. A FWA deployment in the 28 GHz band with 64 users is simulated with different line-of-sight settings and receiver placements. It is concluded that direct line-of-sight to the base station is vital for high user and cell throughput and that there are significant drawbacks of placing the receiver indoors. New algorithms for Channel State Information Reference Signal (CSI-RS) transmission for both beam management and link adaptation are proposed and evaluated. The beam management algorithms do not displayany significant performance gains over the default sweeping algorithm. Closer investigation of simulation results shows that several beams can have almost equal signal strength with the chosen antenna set up, minimizing potential gains of quickly adapting to environmental changes. Results show there are clear benefits of using an aperiodic and adaptive transmission scheme for CSI-RS transmissions over a fixed-rate transmission scheme, yielding a 7% increase in user goodput at similar levels of overhead.

The development of information and communication technologies (ICT) provides the means for reaching global connectivity that can help humanity progress and prosper. This comes with high demands on data traffic and number of connected devices which are rapidly growing and need to be met by technological development. Massive MIMO, where MIMO stands for multiple-input multiple-output, is envisioned as a fundamental component of next generation wireless communications for its ability to provide high spectral and energy efficiency, SE and EE, respectively. The key feature of this technology is the use of a large number of antennas at the base stations (BS) to spatially multiplex several user equipments (UEs). In the development of new technologies like Massive MIMO, many design alternatives need to be evaluated and compared in order to find the best operating point with a preferable tradeoff between high performance and low cost. In this thesis, two alternative designs for signal processing and hardware in Massive MIMO are studied and compared with the baseline operation in terms of SE, EE, and power consumption. The first design is called superimposed pilot (SP) transmission and is based on superimposing pilot and data symbols to remove the overhead from pilot transmission and reduce pilot contamination. The second design is mixed analog-to-digital converters (ADCs) and it aims at balancing high performance and low complexity by allowing different ADC bit resolutions across the BS antennas. The results show that the baseline operation of Massive MIMO, properly optimized, is the preferred choice. However, SP and mixed ADCs still have room for improvement and further study is needed to ascertain the full capabilities of these alternative designs. / <p>Mindre typografiska fel är korrigerade i den elektroniska versionen. / Minor typographic errors are corrected in the electronic version.</p>

No description available.

In order to support increasing traffic loads, mobile operators need cost-effective solutions to improve the spectral efficiency of their cellular networks, or to off-load them by diverting some of the load to other networks. Advances in the radio resource management may to some extent reduce the need for costly new deployments. The resource management should not only focus on spectrum efficiency—it should try to meet the service requirements of applications that are expected to contribute large data volumes, such as video streaming. Many of those applications are multicast/broadcast in nature (e.g., mobile TV, data podcasting). Our focus in this thesis is on resource allocation mechanisms that exploit the mobility of users. The mobility induces channel quality fluctuations and creates intermittent connectivity, which both can be used to improve the resource efficiency of wireless multimedia systems. The thesis concentrates on two areas: link-layer resource allocation for video streaming in cellular networks and mobility-assisted content distribution in hybrid cellular/ad-hoc networks. In the area of wireless video streaming, we study bit-rate allocation, statistical multiplexing, and channel-aware scheduling. The bit-rate allocation should provide a distortion-optimal assignment of source, channel, and pilot bit-rates under link capacity constraints. We derive an analytical model that captures the video distortion as a function of the bit-rates and, based on it, we study various bit-rate allocation strategies and their robustness to varying radio conditions. The statistical multiplexing can be used to smooth out the burstiness of video streams and avoid over-provisioning of transport channels. We study the statistical multiplexing gains of H.264 video streams, both in terms of bit-rate requirements and video quality. When multiple flows are multiplexed on a shared transport channel, multi-user scheduling becomes crucial for the performance. Channel-aware scheduling exploits fluctuations in radio conditions to optimize the assignment of channel resources. We study the impact of channel-aware scheduling on the performance of delay-sensitive applications and possible extensions of channel-aware schemes to multicast scenarios. In the area of mobility-assisted content distribution, we study the resource efficiency of mobility-assisted podcasting and we propose an analytical model for pedestrian content distribution. The mobility-assisted podcasting exploits random encounters of mobile terminals equipped with short range radios to forward the podcast episodes, thereby relieving the strain on cellular networks. We provide results on the achievable spectrum and energy savings of such scheme. Finally, we introduce the “street model”, the first building block in a conceived library of analytical models that would be used to study the performance of pedestrian content distribution in some common case scenarios of urban mobility. Based on the “street model”, we study how various system parameters and node mobility affect the efficiency of content distribution in a grid of streets that represents a part of Stockholm’s downtown area. / QC20100618

This thesis considers the joint design of bit loading, precoding and receive filters for a multiple-input multiple-output (MIMO) digital communication system. Both the transmitter and the receiver are assumed to know the channel matrix perfectly. It is well known that, for linear MIMO transceivers, orthogonal transmission (i.e., diagonalization of the channel matrix) is optimal for some criteria such as maximum mutual information. It has been shown that if the receiver uses the linear minimum mean squared error (MMSE) detector, the optimal transmission strategy is to perform bit loading on orthogonal subchannels. In the first part of the thesis, we consider the problem of designing the transceiver in order to minimize the probability of error given maximum likelihood (ML) detection. A joint bit loading and linear precoder design is proposed that outperforms the optimal orthogonal transmission. The design uses lattice invariant operations to transform the channel matrix into a lattice generator matrix with large minimum distance separation at a low price in terms of transmit power. With appropriate approximations, it is shown that this corresponds to selecting lattices with good sphere-packing properties. An algorithm for this power minimization is presented along with a lower bound on the optimization. Apparently, given the optimal ML detector, orthogonal subchannels are (in general) suboptimal. The ML detector may suffer from high computational complexity, which motivates the use of the suboptimal but less complex MMSE detector. An intermediate detector in terms of complexity and performance is the decision feedback (DF) detector. In the second part of the thesis, we consider the problem of joint bit loading and precoding assuming the DF detector. The main result shows that for a DF MIMO transceiver where the bit loading is jointly optimized with the transceiver filters, orthogonal transmission is optimal. As a consequence, inter-symbol interference is eliminated and the DF part of the receiver is actually not required, only the linear part is needed. The proof is based on a relaxation of the discrete set of available bit rates on the individual subchannels to the set of positive real numbers. In practice, the signal constellations are discrete and the optimal relaxed bit loading has to be rounded. It is shown that the loss due to rounding is small, and an upper bound on the maximum loss is derived. Numerical results are presented that confirm the theoretical results and demonstrate that orthogonal transmission and the truly optimal DF design perform almost equally well. An algorithm that makes the filter design problem especially easy to solve is presented. As a byproduct from the work on decision feedback detectors we also present some work on the problem of optimizing a Schur-convex objective under a linearly shifted, or skewed, majorization constraint. Similar to the case with a regular majorization constraint, the solution is found to be the same for the entire class of cost functions. Furthermore, it is shown that the problem is equivalent to identifying the convex hull under a simple polygon defined by the constraint parameters. This leads to an algorithm that produces the exact optimum with linear computational complexity. As applications, two unitary precoder designs for MIMO communication systems that use heterogenous signal constellations and employ DF detection at the receiver are presented. / QC 20100624