A universal decoding procedure is proposed for memoryless Gaussian channels with deterministic interfering signals from a certain class. The universality of the proposed decoder is in the sense of being independent of...
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A universal decoding procedure is proposed for memoryless Gaussian channels with deterministic interfering signals from a certain class. The universality of the proposed decoder is in the sense of being independent of the channel parameters and the unknown interfering signal, and at the same time attaining the same randomcoding error exponent as the optimal maximum likelihood (ML) decoder, which utilizes full knowledge of the channel parameters and the interfering signal. The proposed decoding rule can be regarded as a continuous-alphabet version of the universal maximum mutual information (MMI) decoder.
In this correspondence, we compute the randomcoding error exponent for coded modulation transmitted over a flat, memoryless, Rayleigh fading channel. In addition, estimates of code lengths required to achieve a certa...
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In this correspondence, we compute the randomcoding error exponent for coded modulation transmitted over a flat, memoryless, Rayleigh fading channel. In addition, estimates of code lengths required to achieve a certain error probability are determined and compared to those required for the additive white Gaussian noise channel. Finally, the effect of receiver antenna diversity is also considered as a method to compensate for fading and is shown to have a significant, positive impact on the error exponent. The results we obtain represent an information theoretic view that complements the existing literature on performance of coded modulation over fading channels with receiver diversity.
Reliability functions characterize the asymptotic behavior of the error probability for transmission of data on a channel. Holevo introduced the quantum channel, and gave an expression for a random-coding lower bound ...
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Reliability functions characterize the asymptotic behavior of the error probability for transmission of data on a channel. Holevo introduced the quantum channel, and gave an expression for a random-coding lower bound involving an auxiliary function. Holevo, Ogawa, and Nagaoka conjectured that this auxiliary function is concave. Here we give a proof of this conjecture.
This work establishes the exact exponent for the soft-covering phenomenon of a memoryless channel under the total variation metric. The exponent, established herein, is a strict improvement (in both directions) on bou...
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ISBN:
(纸本)9781538647813
This work establishes the exact exponent for the soft-covering phenomenon of a memoryless channel under the total variation metric. The exponent, established herein, is a strict improvement (in both directions) on bounds found in the literature. This complements the recent literature establishing the exact exponent under the relative entropy metric;however, the proof techniques have significant differences, neither bound trivially implies the other. This result implies new and improved bounds for various problems that use soft-covering as their achievability argument, including new lower bounds for the resolvability exponent and the secrecy exponent in the wiretap channel.
In many blind watermarking proposals, the unwatermarked host data is viewed as unavoidable interference. Recently, however, it has been shown that blind watermarking corresponds to communication with side information ...
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ISBN:
(纸本)0819439924
In many blind watermarking proposals, the unwatermarked host data is viewed as unavoidable interference. Recently, however, it has been shown that blind watermarking corresponds to communication with side information (i.e., the host data) at the encoder. For a Gaussian host data and Gaussian channel, Costa showed that blind watermarking can theoretically eliminate all interference from the host data. Our previous work presented a practical blind watermarking scheme based on Costa's idea and called "scalar Costa scheme" (SCS). SCS watermarking was analyzed theoretically and initial experimental results were presented. This paper discusses further practical implications when implementing SCS. We focus on the following three topics: (A) high-rate watermarking, (B) low-rate watermarking, and (C) restrictions due to finite codeword lengths. For (A), coded modulation is applied for a rate of I watermark bit per host-data element, which is interesting for information-hiding applications. For (B), low rates can be achieved either by repeating watermark bits or by projecting them in a random direction in signal space (spread-transform SCS). We show that spread-transform SCS watermarking performs better than SCS watermarking with repetition coding. For (C), Gallager's random-codingexponent is used to analyze the influence of codeword length on SCS performance.
The problem of determining the limits of a pattern or object recognition system can often be approached from Information Theoretic point of view. Given source encoded data, the constrained recognition capacity and ran...
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ISBN:
(纸本)9781424422463
The problem of determining the limits of a pattern or object recognition system can often be approached from Information Theoretic point of view. Given source encoded data, the constrained recognition capacity and randomcoding bound are fundamental characteristics of a recognition channel. They indicate the limiting relationship between the number of classes that a recognition system can maintain, the length of encoded data describing an object/pattern (or its template) at a specific level of noise and distortion and the probability of recognition error. We define recognition channel as an environment that transforms an object template into a query template to be recognized. In this work we assume that images are encoded using an empirical version of Karhunen-Loeve expansion known in the literature as Principal Component Analysis (PCA). We numerically evaluate the empirical capacity and randomcoding bound of a PCA-based recognition system using two datasets, FRGC 2006 and COIL-100. We further analyze the relationship between these performance measures and the probability of information outage often used in practice to characterize capabilities of a nonergodic communication channel. Our conclusions are supported by the results of the numerical analysis.
Coded modulation for noncoherent transmission over slowly time-variant flat fading channels without channel state information is considered. We focus on differentially encoded M-ary PSK with multiple-symbol differenti...
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Coded modulation for noncoherent transmission over slowly time-variant flat fading channels without channel state information is considered. We focus on differentially encoded M-ary PSK with multiple-symbol differential detection (MSDD). Interleaving of blocks of symbols is used as a compromise between the conflicting 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 benefit from MSDD. Conversely, in case of strict decoding delay constraints, MLC suffers 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 significantly. Remarkably, the performance gain of MSDD can be exploited almost completely with practically no increase in computational complexity compared to conventional differential detection.
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