Fading channels: information-theoretic and communications aspects

Biglieri, E.; Proakis, J.G.; Shamai, Shlomo

doi:10.1109/18.720551

Cited by 1,648 publications

(1,362 citation statements)

References 409 publications

(590 reference statements)

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“…Traditionally, the capacity of fading channels is studied under various transmit power constraints, and the corresponding optimal and suboptimal power allocation policies are given in, e.g., [6], [7], [8].…”

Section: Introductionmentioning

confidence: 99%

Optimal power allocation for fading channels in cognitive radio networks: Ergodic capacity and outage capacity

Kang

Liang

Nallanathan

et al. 2009

IEEE Trans. Wireless Commun.

594

456

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A cognitive radio network (CRN) is formed by either allowing the secondary users (SUs) in a secondary communication network (SCN) to opportunistically operate in the frequency bands originally allocated to a primary communication network (PCN) or by allowing SCN to coexist with the primary users (PUs) in PCN as long as the interference caused by SCN to each PU is properly regulated. In this paper, we consider the latter case, known as spectrum sharing, and study the optimal power allocation strategies to achieve the ergodic capacity and the outage capacity of the SU fading channel under different types of power constraints and fading channel models. In particular, besides the interference power constraint at PU, the transmit power constraint of SU is also considered.Since the transmit power and the interference power can be limited either by a peak or an average constraint, various combinations of power constraints are studied. It is shown that there is a capacity gain for SU under the average over the peak transmit/interference power constraint. It is also shown that fading for the channel between SU transmitter and PU receiver is usually a beneficial factor for enhancing the SU channel capacities. Index TermsCognitive radio, power control, ergodic capacity, outage capacity, delay-limited capacity, spectrum sharing, interference power constraint, fading channel.

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Section: Introductionmentioning

confidence: 99%

Optimal power allocation for fading channels in cognitive radio networks: Ergodic capacity and outage capacity

Kang

Liang

Nallanathan

et al. 2009

IEEE Trans. Wireless Commun.

594

456

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“…This entails a high degree of selectivity, which can be modeled as continuous but more often is modeled simply as a succession of blocks [1]. While artificial, a block-fading structure further simplifies the setting while retaining its essence.…”

Section: A Ergodic Settingmentioning

confidence: 99%

“…[1] and references therein). This characterization is difficult because the physical mechanisms that underlie fading are intricate, and thus not easily modeled in a way that facilitates analysis and insights.…”

Section: Motivationmentioning

confidence: 99%

Fading models and metrics for contemporary wireless systems

Jindal

Lozano

2010

2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers

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Abstract-The purpose of this paper is to examine (i) some of the models commonly used to represent fading, and (ii) the information-theoretic metrics most commonly used to evaluate performance over those models. We raise the question of whether these models and metrics remain adequate in light of the advances that wireless systems have undergone over the last two decades. Weaknesses are pointed out, and ideas on possible fixes are put forth. I. MOTIVATIONMultipath fading is one of the most essential attributes of wireless channels and, as such, the characterization of its impact on fundamental communication limits has been the object of much scrutiny (cf.[1] and references therein). This characterization is difficult because the physical mechanisms that underlie fading are intricate, and thus not easily modeled in a way that facilitates analysis and insights. Recognizing this, a few canonical settings that offer a compromise between realism and tractability have become established over time. These settings, involving models for the fading, operational assumptions, and metrics, have served the research community very well for years. The question addressed in this paper is whether these settings remain adequate in light of the rapid advances experienced by wireless systems in their characteristics and operating conditions. II. CANONICAL SETTINGSIn the settings object of our interest, fading is modeled as a stochastic process. The marginal modeling is not problematic: the central limit theorem applied to the sum of a large number of multipath components yields a theoretical Rayleigh distribution for the amplitude, and experimental measurements have repeatedly confirmed the validity of this distribution [2].It is the modeling of the fading dynamics that presents the most complications. From an information-theoretic vantage, what is of essence is the selectivity of the fading over each codeword and the two most common canonical settings idealize this selectivity in limiting senses:• Ergodic setting. The fading varies ergodically over the span of each codeword.• Quasi-static setting. The fading is fixed over the span of each codeword, and varies only from codeword to codeword. Both these settings represent an admittedly drastic simplification of reality, deemed necessary in order to enable rigorous mathematical treatment. We next elaborate on these two settings, with emphasis on the operational assumptions that have to do with channel-state information (CSI) availability at the transmitter. A. Ergodic SettingIn this setting, each codeword is subject to the entire distribution of the fading. This entails a high degree of selectivity, which can be modeled as continuous but more often is modeled simply as a succession of blocks [1]. While artificial, a block-fading structure further simplifies the setting while retaining its essence.The ergodic setting has a well-defined capacity in the Shannon sense [1], the so-called "ergodic capacity", which entails an expectation over the fading distribution. The ergodic capacity can...

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“…Although widely used in physics [6], computer vision [7,8], communications [9], and many other fields, the application of information theoretic concepts is still in its early stage in medical image analysis. Few notable exceptions include using cross and joint entropy for image registration [10,11], the Rényi entropy for measuring the heart rate Gaussianity [12], and the Shannon entropy for analyzing heart period variability [13].…”

Section: Introductionmentioning

confidence: 99%

Heart Motion Abnormality Detection via an Information Measure and Bayesian Filtering

Punithakumar

Ayed

et al. 2009

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009

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Abstract. This study investigates heart wall motion abnormality detection with an information theoretic measure of heart motion based on the Shannon's differential entropy (SDE) and recursive Bayesian filtering. Heart wall motion is generally analyzed using functional images which are subject to noise and segmentation inaccuracies, and incorporation of prior knowledge is crucial in improving the accuracy. The Kalman filter, a well known recursive Bayesian filter, is used in this study to estimate the left ventricular (LV) cavity points given incomplete and noisy data, and given a dynamic model. However, due to similarities between the statistical information of normal and abnormal heart motions, detecting and classifying abnormality is a challenging problem which we proposed to investigate with a global measure based on the SDE. We further derive two other possible information theoretic abnormality detection criteria, one is based on Rényi entropy and the other on Fisher information. The proposed method analyzes wall motion quantitatively by constructing distributions of the normalized radial distance estimates of the LV cavity. Using 269×20 segmented LV cavities of short-axis magnetic resonance images obtained from 30 subjects, the experimental analysis demonstrates that the proposed SDE criterion can lead to significant improvement over other features that are prevalent in the literature related to the LV cavity, namely, mean radial displacement and mean radial velocity.

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Fading channels: information-theoretic and communications aspects

Cited by 1,648 publications

References 409 publications

Optimal power allocation for fading channels in cognitive radio networks: Ergodic capacity and outage capacity

Optimal power allocation for fading channels in cognitive radio networks: Ergodic capacity and outage capacity

Fading models and metrics for contemporary wireless systems

Heart Motion Abnormality Detection via an Information Measure and Bayesian Filtering

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