Preben Mogensen

Bio: Preben Mogensen is an academic researcher from Aalborg University. The author has contributed to research in topics: Telecommunications link & Scheduling (computing). The author has an hindex of 64, co-authored 512 publications receiving 16042 citations. Previous affiliations of Preben Mogensen include Nokia & Bell Labs.

Downlink performance of channel estimation and tracking with high mobile speed in UMTS

Abstract: The effect of high mobile speed in UMTS is examined in this paper. A theoretical analysis is carried out in order to find the optimum slot structure for UMTS. This analysis is supported by numerical results. Several channel estimation algorithms have been examined and the best performance is reached, when the downlink slot structure is changed.

Impact of TCP flow control on the radio resource management of WCDMA networks

Abstract: The present paper highlights the performance of the transport control protocol over WCDMA networks. The TCP flow control adjusts the transmission rate to the network and receiver's capacity. Due to this protocol self-adaptation to the transmission conditions of the links involved in the TCP connection, the protocol performance can not be disconnected from the underlying network. In WCDMA networks, the RRM assigns the radio resources to the UE in the cell, which directly impacts the TCP throughput performance. The results show that the allocation of high bit rate dedicated channels to small file downloads (such as Web pages) produce poor channelization code efficiency compared to allocating low bit rate channels. Under certain conditions, for large file downloads (such as ftp) the code efficiency and throughput performance improve significantly due to the protocol nature to fully utilize the bottleneck capacity. This protocol performance suggests a radio resource allocation strategy for DCH channels, which increases the bit rate stepwise as the file transmission evolves starting from a low bit rate.

Optimum technique for encoding and decoding physical resource block locations

Abstract: An apparatus, such as a user equipment, includes a resource unit RU measurement unit coupled to an output of a wireless receiver; an encoder configurable to encode information descriptive of M perceived best ones of N RUs, where each individual RU is assigned a unique number from a set {1, 2,...,N} where there are sets: Formula (I), Formula (II), where each vector in set Formula (III) refers to a unique RU combination and where there are Formula (IV) elements in the set Formula (III); and a wireless transmitter configurable to transmit the encoded information to a wireless network apparatus, such as a base station. The base station includes a decoder operable to decode the encoded information.

The Impact of RLC Delivery Sequence on FTP Performance in UMTS

Abstract: The Radio Link Control (RLC) protocol of Universal Mobile Telecommunication System (UMTS) provides an option for inor out-of-sequence delivery of Service Data Units (SDUs) to upper layers. In this paper, the impact of this setting on the performance of File Transport Protocol (FTP) sessions is investigated. The investigations are carried out using a real-time emulation platform, and Transmission Control Protocol (TCP) with and without Selective Acknowledgement/Forward Acknowledgment (SACK/FACK) options. The results show that out-of-sequence delivery has a negative impact at higher bandwidths and TCP FACK exacerbates the problem. This is mainly due to the aggressive retransmission strategy employed by FACK, which considers the gaps in a SACK report caused by reordering as lost segments and retransmits them immediately.

Short-term variations of the mobile channel and the GSM signal

Abstract: Measurements of complex impulse responses and transmission of pan-European mobile telephone system GSM timeslots have been carried out in different environments. The short-term variations of the mobile channel have been simulated on computer for comparison. Power, time and phase gradients put demands on the receiver. The variations of these parameters are discussed in theoretical, numerical, and experimental terms. The experimentally obtained values of power gradients are on the order 10 dB between two frames at the 1% level, while the variation from one timeslot to the next is on the order 3 dB at normal speeds of about 50 km/h. Theoretically obtained values show considerably higher variations. The distributions of time-jitter as a function of different environments are also given. >

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

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.).

Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays

Abstract: Multiple-input multiple-output (MIMO) technology is maturing and is being incorporated into emerging wireless broadband standards like long-term evolution (LTE) [1]. For example, the LTE standard allows for up to eight antenna ports at the base station. Basically, the more antennas the transmitter/receiver is equipped with, and the more degrees of freedom that the propagation channel can provide, the better the performance in terms of data rate or link reliability. More precisely, on a quasi static channel where a code word spans across only one time and frequency coherence interval, the reliability of a point-to-point MIMO link scales according to Prob(link outage) ` SNR-ntnr where nt and nr are the numbers of transmit and receive antennas, respectively, and signal-to-noise ratio is denoted by SNR. On a channel that varies rapidly as a function of time and frequency, and where circumstances permit coding across many channel coherence intervals, the achievable rate scales as min(nt, nr) log(1 + SNR). The gains in multiuser systems are even more impressive, because such systems offer the possibility to transmit simultaneously to several users and the flexibility to select what users to schedule for reception at any given point in time [2].

Cognitive Radio An Integrated Agent Architecture for Software Defined Radio

Abstract: An Integrated Agent Architecture for Software Defined Radio. Rapid-prototype cognitive radio, CR1, was developed to apply these.The modern software defined radio has been called the heart of a cognitive radio. Cognitive radio: an integrated agent architecture for software defined radio. Http:bwrc.eecs.berkeley.eduResearchMCMACR White paper final1.pdf. The cognitive radio, built on a software-defined radio, assumes. Radio: An Integrated Agent Architecture for Software Defined Radio, Ph.D. The need for software-defined radios is underlined and the most important notions used for such. Mitola III, Cognitive radio: an integrated agent architecture for software defined radio, Ph.D. This results in the set-theoretic ontology of radio knowledge defined in the. Cognitive Radio An Integrated Agent Architecture for Software.This article first briefly reviews the basic concepts about cognitive radio CR. Cognitive Radio-An Integrated Agent Architecture for Software Defined Radio. Cognitive Radio RHMZ 2007. Software-defined radio SDR idea 1. Cognitive radio: An integrated agent architecture for software.Cognitive Radio SOFTWARE DEFINED RADIO, AND ADAPTIVE WIRELESS SYSTEMS2 Cognitive Networks. 3 Joseph Mitola III, Cognitive Radio: An Integrated Agent Architecture for Software Defined Radio Stockholm.