報告番号: 甲29525 ; 学位授与年月日: 2013-03-25 ; 学位の種別: 博士 ; 学位の種類: 博士（科学） ; 学位記番号: 博創域第870号 ; 研究科・専攻: 新領域創成科学研究科複雑理工学専攻

シャノンによる情報通信のマグナカルタ “A mathematical theory of communication” が発表されてから60年以上を経た．本稿では，シャノンが最初に創造した情報理論の枠組みについて解説した後，いつだれによって基本定理の厳密な証明がなされたか，並びに情報理論がどのような発展の経路をたどってシャノンの後にどこまで到達したかについて解説している．

|We compute the capacity of wireless Orthogonal Frequency Division Multiplexing (OFDM)-based spatial multiplexing systems in delay spread environments. Introducing an abstract model to characterize the statistical properties of the space-time channel, we provide Monte-Carlo methods for estimating the capacity cumulative distribution function, expected capacity, and outage capacity of the OFDM-based spatial multiplexing system for the case where the channel is unknown at the transmitter and perfectly known at the receiver. We provide bounds on capacity, and we study the in uence of physical parameters such as the amount of delay spread, angles of arrival, scattering radius, and line-of-sight component, and system parameters such as the number of antennas and antenna spacing on capacity. Applying our methods to spatial versions of the standard channels taken from the GSM recommendations allows us to make statements about achievable data rates of OFDM-based spatial multiplexing systems in practical broadband propagation environments.

| The development of theory for multilevel coding during the last 20 years is reminded. Several design rules are compared and the capacity region of multilevel codes is outlined. We discuss the dimensionality of the constituent signal constellation and compare di erent labeling strategies by means of random coding exponent. Finally, by discussing bit interleaved coded modulation we show that the progress in theory now leads back to the origin of coded modulation.

| The capacity of at fading channels when applying diierentially encoding with non{coherent reception and no channel state information available at the receiver is considered. Numerical results indicate the gains achievable by multiple symbol detection in the case of slowly time{varying channels and provide a comparison among schemes with diierent potential bandwidth eeciencies.

| Coded modulation for noncoherent transmission over slowly time{variant at fading channels without channel state information is considered. We focus on di erentially encoded M{ary PSK with multiple{symbol di erential detection (MSDD). Interleaving of blocks of symbols is used as a compromise between the con icting requirements of exploiting the channel coherence time and providing diversity for decoding. We study multilevel coding (MLC) which is perfectly matched to the overall vector channel. As already well{known for coherent transmission, properly designed MLC is proved to be asymptotically optimum in the noncoherent case, too. A favorable strategy for labeling of signal points is given. As a promising alternative to MLC, bit{interleaved coded modulation (BICM) is addressed. But since no Gray labeling is possible, BICM can only marginally bene t from MSDD. Conversely, in case of strict decoding delay constraints, MLC su ers from component codes with very short code length. To overcome this drawback, we propose hybrid coded modulation schemes, which are able to combine the advantages of MLC and BICM, respectively. For performance assessment, we evaluate both the achievable channel capacity and the random coding exponent associated with noncoherent coded modulation. Moreover, we show that in multilevel coding and multistage decoding (MSD) the complexity of MSDD can be reduced signi cantly. Remarkably, the performance gain of MSDD can be exploited almost completely with practically no increase in computational complexity compared to conventional di erential detection.

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von Neumann's trick for generating an absolutely unbiased coin from a biased one is this: 1. Toss the biased coin twice, getting 00, 01, 10, or 11. 2. If 00 or 11 occur, go back to step 1; else 3. Call 10 a H, 01 a T. Since p[H] = p[1]*p[0] = p[T], the output is unbiased. Example: 00 10 11 01 01 /spl I.oarr/ H T T. Peter Elias gives an algorithm to generate an independent unbiased sequence of Hs and Ts that nearly achieves the Entropy of the one-coin source. His algorithm is excellent, but certain difficulties arise in trying to use it (or the original von Neumann scheme) to generate bits in expected linear time from a Markov chain. In this paper, we return to the original one-coin von Neumann scheme, and show how to extend it to generate an independent unbiased sequence of Hs and Ts from any Markov chain in expected linear time. We give a right and wrong way to do this. Two algorithms A and B use the simple von Neumann trick on every state of the Markov chain. They differ in the time they choose to announce the coin flip. This timing is crucial.

recent progress in the field, it is also suitable as a supplement to student with a strong background in mathematics who wants to existing texts for a course in information theory or a course in rate find out what coding theory is all about before tackling a broader distortion theory. treatise in this field. This monograph contains a series of lectures given by the author in July, 1973 at the Summer School on Data Transmission at the " International Centre for Mechanical Sciences, " Udine, Italy. Apart from omitting the fact that only binary block codes are discussed, the title accurately describes the contents of the monograph. The first chapter gives the definition and examples of binary block codes, followed by a brief discussion of the use of codes in communication systems. This chapter ends with Shannon's coding theorem for the binary symmetric channel and a mention of existing upper and lower bounds on the minimum distance of block codes. Chapter 2 is a short introduction to linear block codes and their associated generator and parity-check matrices. The encoding procedure and decoding technique using the standard array for the code are discussed briefly. In this chapter, a number of theorems are stated without proof. Chapter 3 is a thorough discussion of the Golay code. Several properties of this code are given, including those associated with t-designs. Two decoding algorithms for the Golay code are presented , one due to Berlekamp and another, a threshold decoding algorithm, due to Goethals. In this chapter, the author provides proofs for some, but not all, of the stated theorems. Chapter 4 is devoted to the proof of the MacWilliams's identities and of Gleason's theorem which relates the weight enum-erators of self-dual codes to the weight enumerators of the extended Hamming and Golay codes. The last chapter is devoted to cyclic codes. After presenting some of the general theory, the author gives a brief description of Hamming, Bose-Chaudhuri-Hocquenghem (BCH), Reed-Solomon, and Justesen codes. The classical Peterson decoding technique for binary BCH codes is presented, and reference is made to Berlekamp's iterative decoding algorithm. In each chapter, the author provides the reader with numerous examples which well illustrate the theory presented. At the end of each chapter he gives suggestions for further reading. There are 113 references in this monograph of 78 pages which makes it a very good source of references. But what is more …

recent progress in the field, it is also suitable as a supplement to student with a strong background in mathematics who wants to existing texts for a course in information theory or a course in rate find out what coding theory is all about before tackling a broader distortion theory. treatise in this field. This monograph contains a series of lectures given by the author in July, 1973 at the Summer School on Data Transmission at the " International Centre for Mechanical Sciences, " Udine, Italy. Apart from omitting the fact that only binary block codes are discussed, the title accurately describes the contents of the monograph. The first chapter gives the definition and examples of binary block codes, followed by a brief discussion of the use of codes in communication systems. This chapter ends with Shannon's coding theorem for the binary symmetric channel and a mention of existing upper and lower bounds on the minimum distance of block codes. Chapter 2 is a short introduction to linear block codes and their associated generator and parity-check matrices. The encoding procedure and decoding technique using the standard array for the code are discussed briefly. In this chapter, a number of theorems are stated without proof. Chapter 3 is a thorough discussion of the Golay code. Several properties of this code are given, including those associated with t-designs. Two decoding algorithms for the Golay code are presented , one due to Berlekamp and another, a threshold decoding algorithm, due to Goethals. In this chapter, the author provides proofs for some, but not all, of the stated theorems. Chapter 4 is devoted to the proof of the MacWilliams's identities and of Gleason's theorem which relates the weight enum-erators of self-dual codes to the weight enumerators of the extended Hamming and Golay codes. The last chapter is devoted to cyclic codes. After presenting some of the general theory, the author gives a brief description of Hamming, Bose-Chaudhuri-Hocquenghem (BCH), Reed-Solomon, and Justesen codes. The classical Peterson decoding technique for binary BCH codes is presented, and reference is made to Berlekamp's iterative decoding algorithm. In each chapter, the author provides the reader with numerous examples which well illustrate the theory presented. At the end of each chapter he gives suggestions for further reading. There are 113 references in this monograph of 78 pages which makes it a very good source of references. But what is more …

n source and destination pairs randomly located in a fixed area want to communicate with each other. It is well known that classical multihop architectures that decode and forward packets can deliver at most a radicn-scaling of the aggregate throughput. The performance is limited by the mutual interference between communicating nodes. We show however that a linear scaling of the capacity with n can in fact be achieved by more intelligent node cooperation and distributed MIMO communication. The key ingredient is a hierarchical and digital architecture for nodal exchange of information for realizing the cooperation.

j I This report contains a compromise optimum design for the low data rate users of the Tracking and Data Relay Satellite System (TDRSS). Design goals for the TDRSS are employed in this report to arrive at the transponder design. Multi path, P.. F. I . , antenna ` pattern anomolies, other user signals, and other definable degrading factors are included as trade-off parameters in the design 1 Synchronization, emergency voice, user stabilization, polarization I diversity and error control coding are also considered and their impact on the transponder design is evaluated.

ion of the flow of information in the system. In a distributed network of sensors, the sensing system may be comprised of multiple sensors that are physically disjoint or distributed in time or space, and that work cooperatively. Compared to a single sensor platform, a network has the advantages of diversity (different sensors offer complementary 3.9. FUSION IN THE CONTEXT OF INFORMATION THEORY 5 viewpoints), and redundancy (reliability and increased resolution of the measured quantity) [24]. In fact, it has been rigorously established from the theory of distributed detection that higher reliability and lower probability of detection error can be achieved when observation data from multiple, distributed sources is intelligently fused in a decision making algorithm, rather than using a single observation data set [44]. Intuitively, any practical sensing device has limitations on its sensing capabilities (e.g. resolution, bandwidth, efficiency, etc.). Thus, descriptions built on the data sensed by a single device are only approximations of the true state of nature. Such approximations are often made worse by incomplete knowledge and understanding of the environment that is being sensed and its interaction with the sensor. These uncertainties, coupled with the practical reality of occasional sensor failure greatly compromises reliability and reduces confidence in sensor measurements. Also, the spatial and physical limitations of sensor devices often means that only partial information can be provided by a single sensor. A network of sensors overcomes many of the shortcomings of a single sensor. However new problems in efficient information management arise. These may be categorized into two broad areas [30]: 1. Data Fusion: This is the problem of combining diverse and sometimes conflicting information provided by sensors in a multi-sensor system, in a consistent and coherent manner. The objective is to infer the relevant states of the system that is being observed or activity being performed. 2. Resource Administration: This relates to the task of optimally configuring, coordinating and utilizing the available sensor resources, often in a dynamic, adaptive environment. The objective is to ensure efficient use of the sensor platform for the task at hand. In comparison to lumped-parameter sensor systems (Figure 3.9.1), the issues mentioned Efficiency, in this context, is very general and can refer to power, bandwidth, overhead, throughput, or a variety of other performance metrics, depending upon the particular application. 6 CHAPTER 3. INFORMATION FUSION above for multi-sensor systems can be diagrammed as shown in Figure 3.9.2 [24].

i ii iii ABSTRACT Convolutional encoding is a forward error correction technique that is used for correction of errors at the receiver end. The two decoding algorithms used for decoding the convolutional codes are Viterbi algorithm and Sequential algorithm. Sequential decoding has advantage that it can perform very well with long constraint length. Viterbi decoding is the best technique for decoding the convolutional codes but it is limited to smaller constraint lengths. It has been widely deployed in many wireless communication systems to improve the limited capacity of the communication channels. The Viterbi algorithm, is the most extensively employed decoding algorithm for convolutional codes.. The availability of wireless technology has revolutionized the way communication is done in our world today. With this increased availability comes increased dependence on the underlying systems to transmit information both quickly and accurately. Because the communications channels in wireless systems can be much more hostile than in " wired " systems, voice and data must use forward error correction coding to reduce the probability of channel effects corrupting the information being transmitted. A new type of coding, called Viterbi coding, can achieve a level of performance that comes closer to theoretical bounds than more conventional coding systems. The Viterbi Algorithm, an application of dynamic programming, is widely used for estimation and detection problems in digital communications and signal processing.It is used to detect signals in communications channels with memory, and to decode sequential error control codes that are used to enhance the performance of digital communication systems. iv Though various platforms can be used for realizing Viterbi Decoder including Field Programmable Gate Arrays (FPGAs) , Complex Programmable Logic Devices (CPLDs) or Digital Signal Processing (DSP) chips but in this project benefits of using an FPGA to Implement Viterbi Decoding Algorithm has been described. FPGAs are a technology that gives the designer flexibility of a programmable solution, the performance of a custom solution and lowering overall cost. The advantages of the FPGA approach to DSP Implementation include higher sampling rates than are available from traditional DSP chips, lower costs than an ASIC. The FPGA also adds design flexibility and adaptability with optimal device utilization conserving both board space and system power that is often not the case with DSP chips.

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http://hfs.sagepub.com/content/54/4/503 The online version of this article can be found at: DOI: 10.1177/0018720811426140 published online 7 December 2011 2012 54: 503 originally Human Factors: The Journal of the Human Factors and Ergonomics Society Jamie C. Gorman, Nancy J. Cooke, Polemnia G. Amazeen and Shannon Fouse Approach Measuring Patterns in Team Interaction Sequences Using a Discrete Recurrence

he design of medium access control (MAC) protocols has traditionally been separated from that of the physical (PHY) layer. To a MAC protocol designer, the PHY layer is a black box satisfying the so-called collision model: when only one user transmits, the packet arrives at the receiving node error free. But when transmissions are simultaneous, packets are lost due to collision. Until recently, the theory of random access was based on such an idealized model, and random access protocols were viewed as collision resolution or collision avoidance techniques. In practice, the collision model is both optimistic and pessimistic: optimistic, for it ignores channel effects such as fading and noise on reception, and pessimistic, because it does not accommodate the possibility that packets may be successfully decoded in the presence of simultaneous transmissions. Given the advances in multiuser communications at the PHY layer, the collision model no longer represents all the characteristics of the PHY layer, missing some of its most important properties. Is there a need to go beyond the collision model for wireless networks? Should the MAC layer assume a multiuser PHY layer and be designed with a cross-layer principle in mind? Is the gain of a cross-layer design significant enough to justify replacing a well-tested protocol with a more sophisticated one? Will the cross-layer design be too complicated to implement, and too sensitive to channel changes to be useful? The idea of cross-layer design has been brought to the fore by the phenomenal growth in wireless applications and a continuing push for broadband access. The fundamental challenge, as noted by Gallager in 1985 [1] and more recently by Ephremides T

by Ebrahim MolavianJazi Among the emerging trends in the wireless industry, the Internet of Things (IoT) and machine-to-machine (M2M) communications are notable examples that prompt power efficient communication schemes that can communicate short packets of timesensitive control information with very low latency. A mathematical analysis and design of networks with such stringent latency requirements, however, cannot rely on conventional information theoretic results which assume asymptotically large blocklengths. In this dissertation, we build upon a recent line of work on non-asymptotic information theory to characterize second-order approximations for channel coding rates over a variety of Gaussian settings at finite blocklength. Our results reveal several interesting insights for practical systems design. For any Gaussian channel at finite blocklength, i.i.d. Gaussian input, although capacityachieving, is not second-order optimal. Good codes must possess certain structures to ensure power efficiency and achieve high rates. For the discrete-input Gaussian channel at low SNR, coded-PSK surprisingly outperforms coded-QAM with common random i.i.d. codes. For the non-ergodic fading channel with short blocklength, the Gaussian noise can have as significant an impact on the outage probability as fading can. And finally, when channel uses are precious, time division multiple access (TDMA) is costly, particularly when the number of users grows. Ebrahim MolavianJazi On the theoretical side, our key contribution is a unified and convenient approach for proving sharp achievability results for a variety of Gaussian settings. We amend the standard method of random coding and typicality decoding to make it applicable to non-i.i.d. inputs and single-user as well as multi-user channels with cost constraints. In particular, we use a new change of measure technique and also apply a convenient yet powerful form of the Central Limit Theorem (CLT), called the CLT for functions, to analyze certain dependent information random variables. In comparison with other sharp achievability methods, our unified approach is more transparent and follows conventional lines of reasoning. To Our Lady of Fatima and Her Peace-Bringing Son ... and to my lovely Hajar

by Brian P. Dunn This dissertation develops a perspective for studying overhead in communication systems that contrasts the traditional viewpoint that overhead is the “nondata” portion of transmissions. By viewing overhead as the cost of constraints imposed on a system, information-theoretic techniques can be used to obtain fundamental limits on system performance. In principle, protocol overhead in practical implementations can then be benchmarked against these fundamental limits in order to identify opportunities for improvement. We examine three sources of overhead that have been studied in both information theory and networking using different models and metrics. For multi-access communication systems, we compute constrained capacity regions for two binary additive channels with feedback and develop inner and outer bounds on the capacity region of the packet collision channel with feedback that appear to be tight numerically. We develop bounds on the protocol overhead required to meet an average delay constraint and then use these bounds to characterize rate-delay tradeoffs for communicating a bursty source over a noisy channel. Finally, we study information-theoretic security in timing channels and show that non-zero secrecy rates can be achieved over the wiretap timing channel using a deterministic encoder.

binary RSC codes can lead to better global performance. The encoding scheme can be designed so that decoding can be achieved closer to the theoretical limit, while showing better performance in the region of low error rates. These results are illustrated with some examples based on double-binary ( ) 8-state and 16-state TCs, easily adaptable to a large range of data block sizes and coding rates. The double-binary 8-state code has already been adopted in several telecommunication standards.