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].

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Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays

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Table Of Integrals Series And Products

Information Theory and Reliable Communication

The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

[서평]「Applied Cryptography」

The presence of both multiple-access interference (MAI) and intersymbol interference (ISI) constitutes a major impediment to reliable communications in multipath code-division multiple-access (CDMA) channels. In this paper, an iterative receiver structure is proposed for decoding multiuser information data in a convolutionally coded asynchronous multipath DS-CDMA system. The receiver performs two successive soft-output decisions, achieved by a soft-input soft-output (SISO) multiuser detector and a bank of single-user SISO channel decoders, through an iterative process. At each iteration, extrinsic information is extracted from detection and decoding stages and is then used as a priori information in the next iteration, just as in turbo decoding. Given the multipath CDMA channel model, a direct implementation of a sliding-window SISO multiuser detector has a prohibitive computational complexity. A low-complexity SISO multiuser detector is developed based on a novel nonlinear interference suppression technique, which makes use of both soft interference cancellation and instantaneous linear minimum mean-square error filtering. The properties of such a nonlinear interference suppressor are examined, and an efficient recursive implementation is derived. Simulation results demonstrate that the proposed low complexity iterative receiver structure for interference suppression and decoding offers significant performance gain over the traditional noniterative receiver structure. Moreover, at high signal-to-noise ratio, the detrimental effects of MAI and ISI in the channel can almost be completely overcome by iterative processing, and single-user performance can be approached.

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Iterative (turbo) soft interference cancellation and decoding for coded CDMA

In this chapter, we address scenarios where the tasks of (modulo-type) precoding for the multiple-input/multiple-output (MIMO) broadcast channel, network coding with its associated finite-field matrix channel, and channel coding meet or complement each other. By enlightening dualities, similarities, and differences between the areas and corresponding schemes, a deeper understanding of their mutual interaction is gained. Moreover, this allows for a transfer of schemes and strategies from one field to another one. Exemplarily, schemes operating at the intersection of complex-valued and finite-field/modulo processing are addressed. First, an overview on modulo-type precoding and its latest version via finite-field preprocessing is given; the connections and specific restrictions of the different approaches are illustrated. The advantages of modulo-type precoding are addressed when additional requirements, such as per-antenna power constraints and a reduced degree of coordination in a network MIMO scenario, are imposed. Finally, the application of precoding to finite-field channels is discussed, either as differential network coding or as selection precoding.

Modulo-Type Precoding for Networks

In this paper a numerical method is presented, which finds a tight lower bound for the mutual information between a binary and an arbitrary finite random variable with joint distributions that have variational distance to a known joint distribution not greater than a known value. This lower bound can be applied to mutual information estimation with confidence intervals.

A tight lower bound on the mutual information of a binary and an arbitrary finite random variable as a function of the variational distance

Precoding at the transmitter side has been proved to be a very efficient strategy for channel equalization in single-carrier digital transmission schemes. It enables the application of coded modulation in a seamless fashion. A drawback of precoding is that the signal at the input of the decision device exhibits a huge dynamic range. Based on dynamics shaping, a combined precoding/shaping technique introduced previously (see Fischer, R. et al., IEEE JSAC, p.1622-33, 1995), a new shaping strategy is developed. This technique enables a flexible trade-off between (i) reduction of the average transmit power, (ii) avoidance of peaks in the transmit signal in order to facilitate a line driver implementation, and (iii) restriction of the maximum amplitude at the receiver side to a prescribed value. Over a wide range, all three demands can be met simultaneously. As the scheme is fully compatible with Tomlinson-Harashima precoding, it can replace the precoder even in existing and standardized schemes. Simulation results for a typical DSL scenario show the achievable gains.

Signal shaping for reduction of peak-power and dynamic range in precoding schemes

Spatially Coupled Low-Density Parity-Check (SC-LDPC) codes offer excellent decoding performance and can be elegantly decoded with a Windowed Decoder (WD). We determine an efficient WD configuration with low control overhead. For fair comparisons, we normalize all configurations to the same maximal computational complexity, which is an important measure of the decoding effort in packet-based data communication systems. We determine an optimized configuration from a joint evaluation of the window size, the window update strategy, and parity check-based Early Termination (ET). Firstly, we use a variable node-centered update strategy, which omits updates of messages in some parts of the decoding window. With the complexity normalization, the window size can be increased compared to a check node-centered update strategy, which uniformly updates all messages in the decoding window. Secondly, we only require the satisfaction of the top-most parity-check equations in each window to move to the next position more quickly. Using a surprisingly large window size, the resulting WD halves the average decoding complexity of the block decoder while maintaining a rather small gap in the decoding performance.

Comparison of Windowed-Decoder Configurations for Spatially Coupled LDPC Codes Under Equal-Complexity Constraints.

Am Beispiel der Kapazitatsformel fur den Additive White Gaussian Noise (AWGN-)Kanal wird gezeigt, welche grundsatzliche Bedeutung der Informationstheorie nach C.E. Shannon beim Ubergang vom Industrie- zum Informationszeitalter in der zweiten Halfte des 20. Jahrhunderts zukommt. Hierzu werden exemplarisch zwei mathematische Konzepte zur Ableitung informationstheoretischer Theoreme behandelt. Aus der Kapazitatsformel werden einfache Beziehungen zum Zusammenhang zwischen Information und Energie sowie elementare Existenzschranken fur analoge und digitale Informationsubertragungssysteme abgeleitet. Allgemeine Betrachtungen zur Bedeutung theoretischer Grundlagen fur technische Entwicklungen schliesen den Beitrag ab.

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Johannes B. Huber

Papers

Modulo-Type Precoding for Networks

A tight lower bound on the mutual information of a binary and an arbitrary finite random variable as a function of the variational distance

Signal shaping for reduction of peak-power and dynamic range in precoding schemes

Comparison of Windowed-Decoder Configurations for Spatially Coupled LDPC Codes Under Equal-Complexity Constraints.

Eine Formel verändert die Welt