Dissertation•
Space-Time Codes for High Data Rate Wireless Communications
24 Apr 2002-
TL;DR: Results show that remarkable energy and spectral efficiencies are achievable by combining concepts drawn from space-time coding, multiuser detection, array processing and iterative decoding.
Abstract: Space-time codes (STC) are a class of signaling techniques, offering coding and diversity gains along with improved spectral efficiency. These codes exploit both the spatial and the temporal diversity of the wireless link by combining the design of the error correction code, modulation scheme and array processing. STC are well suited for improving the downlink performance, which is the bottleneck in asymmetric applications such as downstream Internet. Three original contributions to the area of STC are presented in this dissertation. First, the development of analytic tools that determine the fundamental limits on the performance of STC in a variety of channel conditions. For trellis-type STC, transfer function based techniques are applied to derive performance bounds over Rayleigh, Rician and correlated fading environments. For block-type STC, an analytic framework that supports various complex orthogonal designs with arbitrary signal cardinalities and array configurations is developed. In the second part of the dissertation, the Virginia Tech Space-Time Advanced Radio (VT-STAR) is designed, introducing a multi-antenna hardware laboratory test bed, which facilitates characterization of the multiple-input multiple-output (MIMO) channel and validation of various space-time approaches. In the third part of the dissertation, two novel space-time architectures paired with iterative processing principles are proposed. The first scheme extends the suitability of STC to outdoor wireless communications by employing iterative equalization/decoding for time dispersive channels and the second scheme employs iterative interference cancellation/decoding to solve the error propagation problem of Bell-Labs Layered Space-Time Architecture (BLAST). Results show that remarkable energy and spectral efficiencies are achievable by combining concepts drawn from space-time coding, multiuser detection, array processing and iterative decoding.
Citations
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TL;DR: This paper examines the basic building block of cooperative diversity systems, a simple fading relay channel where the source, destination, and relay terminals are each equipped with single antenna transceivers and shows that space-time codes designed for the case of colocated multiantenna channels can be used to realize cooperative diversity provided that appropriate power control is employed.
Abstract: Cooperative diversity is a transmission technique, where multiple terminals pool their resources to form a virtual antenna array that realizes spatial diversity gain in a distributed fashion. In this paper, we examine the basic building block of cooperative diversity systems, a simple fading relay channel where the source, destination, and relay terminals are each equipped with single antenna transceivers. We consider three different time-division multiple-access-based cooperative protocols that vary the degree of broadcasting and receive collision. The relay terminal operates in either the amplify-and-forward (AF) or decode-and-forward (DF) modes. For each protocol, we study the ergodic and outage capacity behavior (assuming Gaussian code books) under the AF and DF modes of relaying. We analyze the spatial diversity performance of the various protocols and find that full spatial diversity (second-order in this case) is achieved by certain protocols provided that appropriate power control is employed. Our analysis unifies previous results reported in the literature and establishes the superiority (both from a capacity, as well as a diversity point-of-view) of a new protocol proposed in this paper. The second part of the paper is devoted to (distributed) space-time code design for fading relay channels operating in the AF mode. We show that the corresponding code design criteria consist of the traditional rank and determinant criteria for the case of colocated antennas, as well as appropriate power control rules. Consequently space-time codes designed for the case of colocated multiantenna channels can be used to realize cooperative diversity provided that appropriate power control is employed.
2,032 citations
Cites background or methods from "Space-Time Codes for High Data Rate..."
...the single-relay case consists of satisfying the classical rank and determinant criteria for colocated antennas [2],...
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...circularly symmetric complex Gaussian behavior widely used in the MIMO literature [2], [24], [25]....
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...Hence, optimum signal design for the relay case consists of constructing a space–time code satisfying the classical rank and determinant criteria [2], as well as ensuring proper power control (diversity is achieved in the effective SNR )....
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Journal Article•
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TL;DR: An analytical approach for symbol error ratio (SER) analysis of the SM algorithm in independent identically distributed Rayleigh channels results closely match and it is shown that SM achieves better performance in all studied channel conditions, as compared with other techniques.
Abstract: Spatial modulation (SM) is a recently developed transmission technique that uses multiple antennas. The basic idea is to map a block of information bits to two information carrying units: 1) a symbol that was chosen from a constellation diagram and 2) a unique transmit antenna number that was chosen from a set of transmit antennas. The use of the transmit antenna number as an information-bearing unit increases the overall spectral efficiency by the base-two logarithm of the number of transmit antennas. At the receiver, a maximum receive ratio combining algorithm is used to retrieve the transmitted block of information bits. Here, we apply SM to orthogonal frequency division multiplexing (OFDM) transmission. We develop an analytical approach for symbol error ratio (SER) analysis of the SM algorithm in independent identically distributed (i.i.d.) Rayleigh channels. The analytical and simulation results closely match. The performance and the receiver complexity of the SM-OFDM technique are compared to those of the vertical Bell Labs layered space-time (V-BLAST-OFDM) and Alamouti-OFDM algorithms. V-BLAST uses minimum mean square error (MMSE) detection with ordered successive interference cancellation. The combined effect of spatial correlation, mutual antenna coupling, and Rician fading on both coded and uncoded systems are presented. It is shown that, for the same spectral efficiency, SM results in a reduction of around 90% in receiver complexity as compared to V-BLAST and nearly the same receiver complexity as Alamouti. In addition, we show that SM achieves better performance in all studied channel conditions, as compared with other techniques. It is also shown to efficiently work for any configuration of transmit and receive antennas, even for the case of fewer receive antennas than transmit antennas.
1,996 citations
Cites background from "Space-Time Codes for High Data Rate..."
...However, the maximum spectral efficiency of full-diversity STC systems is one symbol per symbol duration for any number of transmit antennas [9]....
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TL;DR: In this article, an overview of MIMO systems with antenna selection is presented, where the antenna diversity is used to increase the capacity of the system and the use of the multiple antennas for the transmission of parallel data streams is discussed.
Abstract: Multiple-input-multiple-output (MIMO) wireless systems are those that have multiple antenna elements at both the transmitter and receiver. They were first investigated by computer simulations in the 1980s. Since that time, interest in MIMO systems has exploded. They are now being used for third-generation cellular systems (W-CDMA) and are discussed for future high-performance modes of the highly successful IEEE 802.11 standard for wireless local area networks. MIMO-related topics also occupy a considerable part of today's academic communications research. The multiple antennas in MIMO systems can be exploited in two different ways. One is the creation of a highly effective antenna diversity system; the other is the use of the multiple antennas for the transmission of several parallel data streams to increase the capacity of the system. This article presented an overview of MIMO systems with antenna selection. The transmitter, the receiver, or both use only the signals from a subset of the available antennas. This allows considerable reductions in the hardware expense.
931 citations
Cites background from "Space-Time Codes for High Data Rate..."
...Practical schemes, like layered space-time (ST) receiver structures [8]–[10] combined with space-time codes [11] allow us to approach these capacity limits....
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Book•
14 Nov 2003
TL;DR: In this paper, the authors provide an in-depth insight into hybrid multiple access techniques based on multi-carrier (MC) transmission, and present numerous hybrid access and air interface architectures including OFDM/CDMA, MC-CDMA and MT-CDMAC over new techniques such as space-time coding and software radio.
Abstract: From the Publisher:
Frequency spectrum is a limited and valuable resource for wireless communications. A good example can be observed among network operators in Europe for the prices to pay for UMTS-frequency bands. Therefore, the first goal when designing future wireless communication systems (e.g. 4G - fourth generation) has to be the increase in spectral efficiency. The development in digital communications in the past years has enabled efficient modulation and coding techniques for robust and spectral efficient data, speech, audio and video transmission. These are the multi-carrier modulation (e.g. OFDM) and the spread spectrum technique (e.g. DS-CDMA), where OFDM was chosen for broadcast applications (DVB, DAB) as well as for broadband wireless indoor standards (ETSI HIPERLAN-II, IEEE-802.11) and the DS-CDMA was selected in mobile communications (IS-95, third generation mobile radio systems world wide, UMTS/IMT 2000).
Since 1993 various combinations of multi-carrier (MC) modulation and the spread spectrum (SS) technique have been introduced and the field of MC-SS communications has become an independent and important research topic with increasing activities. New application fields have been proposed such as high rate cellular mobile, high rate wireless indoor and LMDS. It has been shown that MC-SS offers the high spectral efficiency, robustness and flexibility that is required for the next generation systems. Meanwhile, different alternative hybrid schemes such as OFDM/OFDMA, MC-TDMA, etc. have been deeply analysed and adopted in different international standards (ETSI-BRAN, IEEE-802 & MMAC).
Multi-Carrier & Spread-Spectrum: Analysis of Hybrid Air Interfaces draws together all ofthe above mentioned hybrid schemes therefore providing a greatly needed resource for system engineers, telecommunication designers and researchers in order to enable them to develop, build and deploy several schemes based on MC-transmission for the next generation systems (which will be an integration of broadband multimedia services covering both 4G mobile and fixed wireless systems).
Offers a complete treatment of multi-carrier, spread-spectrum (SS) and time division multiplexing (TDM) techniquesProvides an in-depth insight into hybrid multiple access techniques based on multi-carrier (MC) transmissionPresents numerous hybrid multiple access and air interface architectures including OFDM/CDMA, MC-CDMA, MC-DS-CDMA and MT-CDMACovers new techniques such as space-time coding and software radio
Telecommunications engineers, hardware & software system designers and researchers as well as students, lecturers and technicians will all find this an invaluable addition to their bookshelf.
886 citations
TL;DR: A transmit preprocessing technique for the downlink of multiuser multiple-input multiple-output (MIMO) systems is introduced and results demonstrate the potential of the technique in terms of performance and capacity.
Abstract: We introduce a transmit preprocessing technique for the downlink of multiuser multiple-input multiple-output (MIMO) systems. It decomposes the multiuser MIMO downlink channel into multiple parallel independent single-user MIMO downlink channels. Some key properties are that each equivalent single-user MIMO channel has the same properties as a conventional single-user MIMO channel, and that increasing the number of transmit antennas of the multiuser system by one increases the number of spatial channels to each user by one. Simulation results are also provided and these results demonstrate the potential of our technique in terms of performance and capacity.
883 citations
References
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TL;DR: This final installment of the paper considers the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now.
Abstract: In this final installment of the paper we consider the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now. To a considerable extent the continuous case can be obtained through a limiting process from the discrete case by dividing the continuum of messages and signals into a large but finite number of small regions and calculating the various parameters involved on a discrete basis. As the size of the regions is decreased these parameters in general approach as limits the proper values for the continuous case. There are, however, a few new effects that appear and also a general change of emphasis in the direction of specialization of the general results to particular cases.
65,425 citations
Book•
01 Jan 1991TL;DR: The author examines the role of entropy, inequality, and randomness in the design of codes and the construction of codes in the rapidly changing environment.
Abstract: Preface to the Second Edition. Preface to the First Edition. Acknowledgments for the Second Edition. Acknowledgments for the First Edition. 1. Introduction and Preview. 1.1 Preview of the Book. 2. Entropy, Relative Entropy, and Mutual Information. 2.1 Entropy. 2.2 Joint Entropy and Conditional Entropy. 2.3 Relative Entropy and Mutual Information. 2.4 Relationship Between Entropy and Mutual Information. 2.5 Chain Rules for Entropy, Relative Entropy, and Mutual Information. 2.6 Jensen's Inequality and Its Consequences. 2.7 Log Sum Inequality and Its Applications. 2.8 Data-Processing Inequality. 2.9 Sufficient Statistics. 2.10 Fano's Inequality. Summary. Problems. Historical Notes. 3. Asymptotic Equipartition Property. 3.1 Asymptotic Equipartition Property Theorem. 3.2 Consequences of the AEP: Data Compression. 3.3 High-Probability Sets and the Typical Set. Summary. Problems. Historical Notes. 4. Entropy Rates of a Stochastic Process. 4.1 Markov Chains. 4.2 Entropy Rate. 4.3 Example: Entropy Rate of a Random Walk on a Weighted Graph. 4.4 Second Law of Thermodynamics. 4.5 Functions of Markov Chains. Summary. Problems. Historical Notes. 5. Data Compression. 5.1 Examples of Codes. 5.2 Kraft Inequality. 5.3 Optimal Codes. 5.4 Bounds on the Optimal Code Length. 5.5 Kraft Inequality for Uniquely Decodable Codes. 5.6 Huffman Codes. 5.7 Some Comments on Huffman Codes. 5.8 Optimality of Huffman Codes. 5.9 Shannon-Fano-Elias Coding. 5.10 Competitive Optimality of the Shannon Code. 5.11 Generation of Discrete Distributions from Fair Coins. Summary. Problems. Historical Notes. 6. Gambling and Data Compression. 6.1 The Horse Race. 6.2 Gambling and Side Information. 6.3 Dependent Horse Races and Entropy Rate. 6.4 The Entropy of English. 6.5 Data Compression and Gambling. 6.6 Gambling Estimate of the Entropy of English. Summary. Problems. Historical Notes. 7. Channel Capacity. 7.1 Examples of Channel Capacity. 7.2 Symmetric Channels. 7.3 Properties of Channel Capacity. 7.4 Preview of the Channel Coding Theorem. 7.5 Definitions. 7.6 Jointly Typical Sequences. 7.7 Channel Coding Theorem. 7.8 Zero-Error Codes. 7.9 Fano's Inequality and the Converse to the Coding Theorem. 7.10 Equality in the Converse to the Channel Coding Theorem. 7.11 Hamming Codes. 7.12 Feedback Capacity. 7.13 Source-Channel Separation Theorem. Summary. Problems. Historical Notes. 8. Differential Entropy. 8.1 Definitions. 8.2 AEP for Continuous Random Variables. 8.3 Relation of Differential Entropy to Discrete Entropy. 8.4 Joint and Conditional Differential Entropy. 8.5 Relative Entropy and Mutual Information. 8.6 Properties of Differential Entropy, Relative Entropy, and Mutual Information. Summary. Problems. Historical Notes. 9. Gaussian Channel. 9.1 Gaussian Channel: Definitions. 9.2 Converse to the Coding Theorem for Gaussian Channels. 9.3 Bandlimited Channels. 9.4 Parallel Gaussian Channels. 9.5 Channels with Colored Gaussian Noise. 9.6 Gaussian Channels with Feedback. Summary. Problems. Historical Notes. 10. Rate Distortion Theory. 10.1 Quantization. 10.2 Definitions. 10.3 Calculation of the Rate Distortion Function. 10.4 Converse to the Rate Distortion Theorem. 10.5 Achievability of the Rate Distortion Function. 10.6 Strongly Typical Sequences and Rate Distortion. 10.7 Characterization of the Rate Distortion Function. 10.8 Computation of Channel Capacity and the Rate Distortion Function. Summary. Problems. Historical Notes. 11. Information Theory and Statistics. 11.1 Method of Types. 11.2 Law of Large Numbers. 11.3 Universal Source Coding. 11.4 Large Deviation Theory. 11.5 Examples of Sanov's Theorem. 11.6 Conditional Limit Theorem. 11.7 Hypothesis Testing. 11.8 Chernoff-Stein Lemma. 11.9 Chernoff Information. 11.10 Fisher Information and the Cram-er-Rao Inequality. Summary. Problems. Historical Notes. 12. Maximum Entropy. 12.1 Maximum Entropy Distributions. 12.2 Examples. 12.3 Anomalous Maximum Entropy Problem. 12.4 Spectrum Estimation. 12.5 Entropy Rates of a Gaussian Process. 12.6 Burg's Maximum Entropy Theorem. Summary. Problems. Historical Notes. 13. Universal Source Coding. 13.1 Universal Codes and Channel Capacity. 13.2 Universal Coding for Binary Sequences. 13.3 Arithmetic Coding. 13.4 Lempel-Ziv Coding. 13.5 Optimality of Lempel-Ziv Algorithms. Compression. Summary. Problems. Historical Notes. 14. Kolmogorov Complexity. 14.1 Models of Computation. 14.2 Kolmogorov Complexity: Definitions and Examples. 14.3 Kolmogorov Complexity and Entropy. 14.4 Kolmogorov Complexity of Integers. 14.5 Algorithmically Random and Incompressible Sequences. 14.6 Universal Probability. 14.7 Kolmogorov complexity. 14.9 Universal Gambling. 14.10 Occam's Razor. 14.11 Kolmogorov Complexity and Universal Probability. 14.12 Kolmogorov Sufficient Statistic. 14.13 Minimum Description Length Principle. Summary. Problems. Historical Notes. 15. Network Information Theory. 15.1 Gaussian Multiple-User Channels. 15.2 Jointly Typical Sequences. 15.3 Multiple-Access Channel. 15.4 Encoding of Correlated Sources. 15.5 Duality Between Slepian-Wolf Encoding and Multiple-Access Channels. 15.6 Broadcast Channel. 15.7 Relay Channel. 15.8 Source Coding with Side Information. 15.9 Rate Distortion with Side Information. 15.10 General Multiterminal Networks. Summary. Problems. Historical Notes. 16. Information Theory and Portfolio Theory. 16.1 The Stock Market: Some Definitions. 16.2 Kuhn-Tucker Characterization of the Log-Optimal Portfolio. 16.3 Asymptotic Optimality of the Log-Optimal Portfolio. 16.4 Side Information and the Growth Rate. 16.5 Investment in Stationary Markets. 16.6 Competitive Optimality of the Log-Optimal Portfolio. 16.7 Universal Portfolios. 16.8 Shannon-McMillan-Breiman Theorem (General AEP). Summary. Problems. Historical Notes. 17. Inequalities in Information Theory. 17.1 Basic Inequalities of Information Theory. 17.2 Differential Entropy. 17.3 Bounds on Entropy and Relative Entropy. 17.4 Inequalities for Types. 17.5 Combinatorial Bounds on Entropy. 17.6 Entropy Rates of Subsets. 17.7 Entropy and Fisher Information. 17.8 Entropy Power Inequality and Brunn-Minkowski Inequality. 17.9 Inequalities for Determinants. 17.10 Inequalities for Ratios of Determinants. Summary. Problems. Historical Notes. Bibliography. List of Symbols. Index.
45,034 citations
Book•
01 Jan 1983
25,017 citations
"Space-Time Codes for High Data Rate..." refers methods in this paper
...The probability density function of this random variable is given by [71] fγ(γ) = 1 (nTnR − 1)! 3 SNR rnT ́nTnR γnTnR−1e− γ SNR/rnT ....
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...Performance analysis for the error rate of these schemes was drawn from analysis of receive diversity combining schemes [71, 7]....
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...Unlike linear equalization techniques, APP or Maximum Likelihood Sequence Estimation (MLSE) techniques [109] do not suffer from error propagation or noise enhancement [71]....
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...1 Performance Analysis The pair-wise error probability of a maximum-likelihood receiver is well approximated by the Chernoff bound [42, 71, 37] P (c→ e) = P (c→ e | αi,j) ≤ exp(−d2(c, e|αi,j)γ), (4....
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Book•
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TL;DR: In this article, the authors present results of both classic and recent matrix analyses using canonical forms as a unifying theme, and demonstrate their importance in a variety of applications, such as linear algebra and matrix theory.
Abstract: Linear algebra and matrix theory are fundamental tools in mathematical and physical science, as well as fertile fields for research. This new edition of the acclaimed text presents results of both classic and recent matrix analyses using canonical forms as a unifying theme, and demonstrates their importance in a variety of applications. The authors have thoroughly revised, updated, and expanded on the first edition. The book opens with an extended summary of useful concepts and facts and includes numerous new topics and features, such as: - New sections on the singular value and CS decompositions - New applications of the Jordan canonical form - A new section on the Weyr canonical form - Expanded treatments of inverse problems and of block matrices - A central role for the Von Neumann trace theorem - A new appendix with a modern list of canonical forms for a pair of Hermitian matrices and for a symmetric-skew symmetric pair - Expanded index with more than 3,500 entries for easy reference - More than 1,100 problems and exercises, many with hints, to reinforce understanding and develop auxiliary themes such as finite-dimensional quantum systems, the compound and adjugate matrices, and the Loewner ellipsoid - A new appendix provides a collection of problem-solving hints.
23,986 citations
Book•
15 Jan 1996
TL;DR: WireWireless Communications: Principles and Practice, Second Edition is the definitive modern text for wireless communications technology and system design as discussed by the authors, which covers the fundamental issues impacting all wireless networks and reviews virtually every important new wireless standard and technological development, offering especially comprehensive coverage of the 3G systems and wireless local area networks (WLANs).
Abstract: From the Publisher:
The indispensable guide to wireless communicationsnow fully revised and updated!
Wireless Communications: Principles and Practice, Second Edition is the definitive modern text for wireless communications technology and system design. Building on his classic first edition, Theodore S. Rappaport covers the fundamental issues impacting all wireless networks and reviews virtually every important new wireless standard and technological development, offering especially comprehensive coverage of the 3G systems and wireless local area networks (WLANs) that will transform communications in the coming years. Rappaport illustrates each key concept with practical examples, thoroughly explained and solved step by step.
Coverage includes:
An overview of key wireless technologies: voice, data, cordless, paging, fixed and mobile broadband wireless systems, and beyond
Wireless system design fundamentals: channel assignment, handoffs, trunking efficiency, interference, frequency reuse, capacity planning, large-scale fading, and more
Path loss, small-scale fading, multipath, reflection, diffraction, scattering, shadowing, spatial-temporal channel modeling, and microcell/indoor propagation
Modulation, equalization, diversity, channel coding, and speech coding
New wireless LAN technologies: IEEE 802.11a/b, HIPERLAN, BRAN, and other alternatives
New 3G air interface standards, including W-CDMA, cdma2000, GPRS, UMTS, and EDGE
Bluetooth wearable computers, fixed wireless and Local Multipoint Distribution Service (LMDS), and other advanced technologies
Updated glossary of abbreviations and acronyms, and a thorolist of references
Dozens of new examples and end-of-chapter problems
Whether you're a communications/network professional, manager, researcher, or student, Wireless Communications: Principles and Practice, Second Edition gives you an in-depth understanding of the state of the art in wireless technologytoday's and tomorrow's.
17,102 citations
"Space-Time Codes for High Data Rate..." refers background in this paper
...The concept of cellular mobile systems, which was originally proposed in 1968 by AT&T to the Federal Communications Commission (FCC) [3], was based on breaking each market into small geographic zones or “cells” that use a fraction of the total available radio spectrum....
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...The FCC allocated a total of 40 MHz of spectrum in the 800 MHz band to cover 666 full duplex channels....
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