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Table Of Integrals Series And Products

Space-Time Block Coding for Wireless Communications

In studying the performance of coded communications over memoryless channels (with or without fading), the results are given as upper bounds on the average bit error probability (BEP). In principle, there are three different approaches to arriving at these bounds, all of which employ obtaining the so-called pairwise error probability , or the probability of choosing one symbol sequence over another for a given pair of possible transmitted symbol sequences, followed by a weighted summation over all pairwise events. In this chapter, we will focus on the results obtained from the third approach since these provide the tightest upper bounds on the true performance. The first emphasis will be placed on evaluating the pairwise error probability with and without CSI, following which we shall discuss how the results of these evaluations can be used via the transfer bound approach to evaluate average BEP of coded modulation transmitted over the fading channel.

Coded Communication over Fading Channels

The estimation of sparse shallow-water acoustic communication channels and the impact of estimation performance on the equalization of phase coherent communication signals are investigated. Given sufficiently wide transmission bandwidth, the impulse response of the shallow-water acoustic channel is often sparse as the multipath arrivals become resolvable. In the presence of significant surface waves, the multipath arrivals associated with surface scattering fluctuate rapidly over time, in the sense that the complex gain, the arrival time, and the Dopplers of each arrival all change dynamically. A sparse channel estimation technique is developed based on the delay-Doppler-spread function representation of the channel. The delay-Doppler-spread function may be considered as a first-order approximation to the rapidly time-varying channel in which each channel component is associated with Doppler shifts that are assumed constant over an averaging interval. The sparse structure of the delay-Doppler-spread function is then exploited by sequentially choosing the dominant components that minimize a least squares error. The advantage of this approach is that it captures both the channel structure as well as its dynamics without the need of explicit dynamic channel modeling. As the symbols are populated with the sample Dopplers, the increase in complexity depends on the channel Doppler spread and can be significant for a severely Doppler-spread channel. Comparison is made between nonsparse recursive least squares (RLS) channel estimation, sparse channel impulse response estimation, and estimation using the proposed approach. The results are demonstrated using experimental data. In training mode, the proposed approach shows a 3-dB reduction in signal prediction error. In decision-directed mode, it improves significantly the robustness of the performance of the channel-estimate-based equalizer against rapid channel fluctuations.

Estimation of Rapidly Time-Varying Sparse Channels

Error performance is one of the main performance measures and the derivation of its closed-form expression has proved to be quite involved for certain communication systems operating over composite fading channels. In this letter, a unified closed-form expression, applicable to different binary modulation schemes, for the bit error rate of dual-branch selection diversity based systems undergoing independent but not necessarily identically distributed generalized-K fading is derived in terms of the extended generalized bivariate Meijer G-function.

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A New Formula for the BER of Binary Modulations with Dual-Branch Selection over Generalized-K

The performance of digital communication systems over generalized-K (K/sub G/) fading channels is analyzed and evaluated. Novel closed form expressions for the SNR statistics, the average Shannon's channel capacity and the bit error rate (BER) are derived. These expressions are used to study important performance criteria such as the outage performance, the average capacity and the BER for a great variety of modulation formats in K/sub G/ fading channels. The proposed mathematical analysis is accompanied with various performance evaluation results, which demonstrate the usefulness of the proposed approach.

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On the performance analysis of digital communications over generalized-K fading channels

Filter bank-based multicarrier communications (FBMC) have recently attracted increased interest in both wired (e.g., xDSL, PLC) and wireless (e.g., cognitive radio) applications, due to their enhanced flexibility, higher spectral efficiency, and better spectral containment compared to conventional OFDM. A particular type of FBMC, the so-called FBMC/OQAM or OFDM/OQAM system, consisting of pulse shaped OFDM carrying offset QAM (OQAM) symbols, has received increasing attention due to, among other features, its higher spectral efficiency and implementation simplicity. It suffers, however, from an imaginary inter-carrier/inter-symbol interference that complicates signal processing tasks such as channel estimation. This paper focuses on channel estimation for OFDM/OQAM systems based on a known preamble. A review of the existing preamble structures and associated channel estimation methods is given, for both single- (SISO) and multiple-antenna (MIMO) systems. The various preambles are compared via simulations in both mildly and highly frequency selective channels.

Preamble-based Channel Estimation in OFDM/OQAM Systems: A Review

Review: Preamble-based channel estimation in OFDM/OQAM systems: A review

In this paper the problem of semisupervised hyper spectral unmixing is considered. More specifically, the unmixing process is formulated as a linear regression problem, where the abundance's physical constraints are taken into account. Based on this formulation, a novel hierarchical Bayesian model is proposed and suitable priors are selected for the model parameters such that, on the one hand, they ensure the nonnegativity of the abundances, while on the other hand they favor sparse solutions for the abundances' vector. Performing Bayesian inference based on the proposed hierarchical Bayesian model, a new low-complexity iterative method is derived, and its connection with Gibbs sampling and variational Bayesian inference is highlighted. Experimental results on both synthetic and real hyperspectral data illustrate that the proposed method converges fast, favors sparsity in the abun dances' vector, and offers improved estimation accuracy compared to other related methods.

/pdf/a-novel-hierarchical-bayesian-approach-for-sparse-j3basherfd.pdf

A Novel Hierarchical Bayesian Approach for Sparse Semisupervised Hyperspectral Unmixing

In this correspondence, preamble-based least squares (LS) channel estimation in orthogonal frequency division multiplexing (OFDM) systems of the QAM and offset QAM (OQAM) types is considered. The construction of optimal (in the mean squared error (MSE) sense) preambles is investigated, for sparse (a subset of pilot tones, surrounded by nulls) preambles. The two OFDM systems are compared for the same transmit power, which, for cyclic prefix (CP) based OFDM/QAM, also includes the power spent for CP transmission. OFDM/OQAM, with a sparse preamble consisting of equipowered and equispaced pilots embedded in zeros, turns out to perform at least as well as CP-OFDM. Simulations results are presented that verify the analysis.

/pdf/preamble-based-channel-estimation-for-cp-ofdm-and-ofdm-oqam-2nuu9ictu6.pdf

Athanasios A. Rontogiannis

Papers

On the performance analysis of digital communications over generalized-K fading channels

Preamble-based Channel Estimation in OFDM/OQAM Systems: A Review

Review: Preamble-based channel estimation in OFDM/OQAM systems: A review

A Novel Hierarchical Bayesian Approach for Sparse Semisupervised Hyperspectral Unmixing

Preamble-Based Channel Estimation for CP-OFDM and OFDM/OQAM Systems: A Comparative Study