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Related papers: Bit Error Rate is Convex at High SNR

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Motivated by a wide-spread use of convex optimization techniques, convexity properties of bit error rate of the maximum likelihood detector operating in the AWGN channel are studied for arbitrary constellations and bit mappings, which also…

Information Theory · Computer Science 2010-04-16 Sergey Loyka , Francois Gagnon , Victoria Kostina

Motivated by a recent surge of interest in convex optimization techniques, convexity/concavity properties of error rates of the maximum likelihood detector operating in the AWGN channel are studied and extended to frequency-flat slow-fading…

Information Theory · Computer Science 2016-11-17 Sergey Loyka , Victoria Kostina , Francois Gagnon

Convexity properties of error rates of a class of decoders, including the ML/min-distance one as a special case, are studied for arbitrary constellations, bit mapping and coding. Earlier results obtained for the AWGN channel are extended to…

Information Theory · Computer Science 2016-11-15 Sergey Loyka , Victoria Kostina , Francois Gagnon

Convexity/concavity properties of symbol error rates (SER) of the maximum likelihood detector operating in the AWGN channel (non-fading and fading) are studied. Generic conditions are identified under which the SER is a convex/concave…

Information Theory · Computer Science 2016-11-17 Sergey Loyka , Victoria Kostina , Francois Gagnon

The performance of maximum-likelihood (ML) decoded binary linear block codes is addressed via the derivation of tightened upper bounds on their decoding error probability. The upper bounds on the block and bit error probabilities are valid…

Information Theory · Computer Science 2007-07-13 M. Twitto , I. Sason , S. Shamai

In contrast to a maximum-likelihood decoder, it is often desirable to use an incomplete decoder that can detect its decoding errors with high probability. One common choice is the bounded distance decoder. Bounds are derived for the total…

Information Theory · Computer Science 2012-07-26 Kenneth Andrews , Sam Dolinar

We present a generic approximation of the packet error rate (PER) function of uncoded schemes in the AWGN channel using extreme value theory (EVT). The PER function can assume both the exponential and the Gaussian Q-function bit error rate…

Information Theory · Computer Science 2016-10-19 Aamir Mahmood , Riku Jäntti

The maximum likelihood detection rule for a four-dimensional direct-detection optical front-end is derived. The four dimensions are two intensities and two differential phases. Three different signal processing algorithms, composed of…

Information Theory · Computer Science 2021-05-31 Amir Tasbihi , Frank R. Kschischang

In this paper, we complement Verd\'{u}'s work on spectral efficiency in the wideband regime by investigating the fundamental tradeoff between rate and bandwidth when a constraint is imposed on the error exponent. Specifically, we consider…

Information Theory · Computer Science 2007-07-13 X. Wu , R. Srikant

This paper considers the achievability and converse bounds on the maximal channel coding rate at a given blocklength and error probability over AWGN channels. The problem stems from covert communication with Gaussian codewords. By…

Information Theory · Computer Science 2021-01-01 Xinchun Yu , Shuangqin Wei , Yuan Luo

This work analyzes the high-SNR asymptotic error performance of outage-limited communications with fading, where the number of bits that arrive at the transmitter during any time slot is random but the delivery of bits at the receiver must…

Information Theory · Computer Science 2016-11-17 Somsak Kittipiyakul , Petros Elia , Tara Javidi

Non-volatile memory, such as resistive RAM (RRAM), is an emerging energy-efficient storage, especially for low-power machine learning models on the edge. It is reported, however, that the bit error rate of RRAMs can be up to 3.3% in the…

To support ultra-reliable and low-latency services for mission-critical applications, transmissions are usually carried via short blocklength codes, i.e., in the so-called finite blocklength (FBL) regime. Different from the infinite…

Information Theory · Computer Science 2022-09-30 Yao Zhu , Yulin Hu , Xiaopeng Yuan , M. Cenk Gursoy , H. Vincent Poor , Anke Schmeink

Classical probabilistic rounding error analysis is particularly well suited to stochastic rounding (SR), and it yields strong results when dealing with floating-point algorithms that rely heavily on summation. For many numerical linear…

Numerical Analysis · Mathematics 2025-02-26 El-Mehdi El Arar , Massimiliano Fasi , Silviu-Ioan Filip , Mantas Mikaitis

We consider in this paper the problem of noisy 1-bit matrix completion under a general non-uniform sampling distribution using the max-norm as a convex relaxation for the rank. A max-norm constrained maximum likelihood estimate is…

Machine Learning · Statistics 2013-09-25 T. Tony Cai , Wen-Xin Zhou

A clear understanding the behavior of the error probability (EP) as a function of signal-to-noise ratio (SNR) and other system parameters is fundamental for assessing the design of digital wireless communication systems.We propose an…

Information Theory · Computer Science 2016-11-15 Andrea Conti , Dmitry Panchenko , Sergiy Sidenko , Velio Tralli

We consider the problem of jointly optimum modulation and estimation of a real-valued random parameter, conveyed over an additive white Gaussian noise (AWGN) channel, where the performance metric is the large deviations behavior of the…

Information Theory · Computer Science 2016-11-17 Neri Merhav

Signal to Noise Ratio (SNR) is an important index for wireless communications. There are many methods for increasing SNR. In CDMA systems, spreading sequences are used. We consider the frequency-selective wide-sense-stationary…

Information Theory · Computer Science 2016-10-17 Hirofumi Tsuda , Ken Umeno

Although kernel methods are widely used in many learning problems, they have poor scalability to large datasets. To address this problem, sketching and stochastic gradient methods are the most commonly used techniques to derive efficient…

Machine Learning · Statistics 2022-06-03 Shingo Yashima , Atsushi Nitanda , Taiji Suzuki

The behavior of real quantum hardware differs strongly from the simple error models typically used when simulating quantum error correction. Error processes are far more complex than simple depolarizing noise applied to single gates, and…

Quantum Physics · Physics 2024-08-06 Ian Hesner , Bence Hetényi , James R. Wootton
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