Timo Hämäläinen

Bio: Timo Hämäläinen is an academic researcher from University of Jyväskylä. The author has contributed to research in topics: Quality of service & Encoder. The author has an hindex of 38, co-authored 560 publications receiving 7648 citations. Previous affiliations of Timo Hämäläinen include Dalian Medical University & Nokia.

An Efficient and Privacy-Preserving Blockchain-Based Authentication Scheme for Low Earth Orbit Satellite-Assisted Internet of Things

Abstract: Recently, integrating satellite networks (e.g., low-Earth-orbit (LEO) satellite constellation) into the Internet of Things (IoT) ecosystem has emerged as a potential paradigm to provide more reliable, ubiquitous, and seamless network services. The LEO satellite networks serves as a key enabler to transform the connectivity across industries and geographical border. Despite the convenience brought from the LEO satellite networks, it arises security concerns, in which the essential one is to secure the communication between the IoT devices and the LEO satellite network. However, some challenges inheriting from the LEO satellite networks need to be considered, which are: the dynamic topology; the resource-constraint satellites; the relative long latency; and multiple beams authentication. In particular, the centralized authentication schemes are no longer suitable for the emerging LEO satellite-assisted IoT ecosystem. In this article, we first introduce the architecture of the LEO satellite network-assisted IoT ecosystem. Then, we propose an efficient and privacy-preserving blockchain-based authentication scheme. The proposed authentication scheme takes the advantages of certificateless encryption and consortium blockchain to provide lightweight key pair computation without appealing devices’ information and efficient signature querying and verification. In addition, a fast authentication mechanism is implemented in the scheme in order to reduce the time complexity from querying a certain record for the authentication within a satellite among multiple beams. With the analysis of the storage and computation complexity, the performance evaluation demonstrates the effectiveness of the proposed scheme.

Time-critical multimedia components and cell delay jitter

Abstract: The delivery of multimedia services easily faces the problem of guaranteeing the required delay performance for delay sensitive service components. The problem is especially severe with isochronous service components, such as voice and video. The transport network should guarantee, e.g., required bit rate, end-to-end delay, delay variation and error ratio performance, for each tributary of a multimedia service stream regardless of the other traffic or the number of network nodes transversed en route. In this paper, we study the change of delay variation of constant bit rate traffic in the presence of Poisson and MMPP (Markov-modulated Poisson process) distributed background load. A simulation model is deduced and simulation results, based on the model, are presented. Finally, some confirming measurement results are given.

Packet scheduling with revenue optimization and weighted delay minimization

Abstract: In this paper we propose an adaptive packet scheduling model for networks providing quality of service. The model minimizes the weighted mean delays of the connections for specified pricing classes (gold, silver, and bronze), while also maximizing the revenue of the service provider. In this scenario a call admission control (CAC) mechanism is used for guaranteeing specified mean delay characteristics for the different service classes. A closed form analytic and optimal solution is derived for the weights of the scheduler. The scenario is independent of the statistical assumptions for the connections, and is therefore robust against erroneous estimates of the traffic characteristics

Multi-Antenna Covert Communication With Jamming in the Presence of a Mobile Warden

Abstract: Covert communication can hide the information transmission process from the warden to prevent adversarial eavesdropping. However, it becomes challenging when the warden can move. In this paper, we propose a covert communication scheme against a mobile warden, which maximizes the connectivity throughput between a multi-antenna transmitter and a full-duplex jamming receiver with the covert outage probability (COP) limit. First, we analyze the monotonicity of the COP to obtain the optimal location the warden can move. Then, under this worst situation, we optimize the transmission rate, the transmit power and the jamming power of covert communication to maximize the connection throughput. This problem is solved in two stages. Under this worst situation, we first maximize the connection probability over the transmit-to-jamming power ratio within the maximum allowed COP for a fixed transmission rate. Then, the Newton’s method is applied to maximize the connection throughput via optimizing the transmission rate iteratively. Simulation results are presented to evaluate the effectiveness of the proposed scheme.

Better performance of mobile devices in time-frequency dispersive channels using well-localized bases

Abstract: The main aim of this paper is to show on the conceptual level the practical and commercial benefits of signal construction and processing technology based on orthogonal frequency and time domains multiplexing (OFTDM). This technology utilizes mathematical framework of special orthogonal bases with the best time-frequency localization. Higher spectral and energy efficiency of telecommunication systems together with robustness against complex realistic channel conditions are achieved. In particular, the level of interference between subcarrier channels in time and in frequency domain is minimized. This approach can have wide implementation in wideband mobile networks (WiMAX, LTE), digital television (DVB-T/H) and other telecommunication systems.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

Machine learning

Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

Survey of Wireless Indoor Positioning Techniques and Systems

Abstract: Wireless indoor positioning systems have become very popular in recent years. These systems have been successfully used in many applications such as asset tracking and inventory management. This paper provides an overview of the existing wireless indoor positioning solutions and attempts to classify different techniques and systems. Three typical location estimation schemes of triangulation, scene analysis, and proximity are analyzed. We also discuss location fingerprinting in detail since it is used in most current system or solutions. We then examine a set of properties by which location systems are evaluated, and apply this evaluation method to survey a number of existing systems. Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.

The Self-Organizing Map

Abstract: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.