Probability Of Error Mpam
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Request full-text On convexity of MQAM's and MPAM's bit error probability functionsArticle in International Journal of Communication Systems 22(11):1465-1477 · November 2009 with 17 ReadsDOI: 10.1002/dac.1035 · Source: DBLP1st Naeem Muhammad28.55 · Unknown2nd Daniel Lee30.82
Probability Of Error In Qpsk
· Simon Fraser UniversityAbstractFor MQAM and MPAM with practical values of M bpsk probability of error derivation and Gray mapping, we provide a rigorous proof that the associated bit error probability (BEP) functions are convex of
Bit-error-probability-for-bpsk-modulation
the signal-to-noise ratio per symbol. The proof employs Taylor series expansions of the BEP functions' second derivatives and term-by-term comparisons between positive and negative terms. Convexity results are useful for optimizing qpsk bit error rate communication systems as in optimizing adaptive transmission policies. Copyright © 2009 John Wiley & Sons, Ltd. For MQAM and MPAM with practical values of M and Gray mapping, we provide a rigorous proof that the associated bit error probability (BEP) functions are convex of the SNR per symbol. The proof employs Taylor series expansions of the BEP functions' second derivatives and term-by-term comparisons m ary pam probability of error between positive and negative terms. Convexity results are useful for optimizing communication systems as in optimizing adaptive transmission policies. Copyright © 2009 John Wiley & Sons, Ltd.Do you want to read the rest of this article?Request full-text CitationsCitations2ReferencesReferences11On the Throughput Gain for Rapid Dynamic Symbol Duration Adaptation within Discrete Duration Sets"TABLE I The values of κ forFig. 4 B. M-QAM The bit error probability function of Gray mapped MQAM (M-ary quadrature amplitude modulation) can be generally written in the form of [23] ( ) "[Show abstract] [Hide abstract] ABSTRACT: In this paper, we quantitatively analyze the gain in error-constrained bit throughput achieved by the rapid symbol duration adaptation. We focus on the adaptive system that can choose for each symbol a symbol duration only from a discrete set of symbol durations. The results show that the rapid adaptation with a discrete duration set can often achieve a throughput gain similar to that achieved with a continuous set of durations. The results are especially applicable to spreading gain adaptation in CDMA systems. Full-text · Conference Paper · Oct 2009 Song XueDaniel C. LeeRead full-textOptimal Resource Allocation in Coordinated
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Bit Error Rate Of Bpsk
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Simon Fraser University, Burnaby, BC, Canada V5A 1S6 Published in: ·Journal International Journal of Communication Systems archive Volume 22 Issue 11, November 2009 http://dl.acm.org/citation.cfm?id=1656531.1656537&preflayout=tabs Pages 1465-1477 John Wiley and Sons Ltd. Chichester, UK tableofcontents doi>10.1002/dac.v22:11 2009 Article Bibliometrics ·Downloads (6 Weeks): n/a ·Downloads (12 Months): n/a ·Downloads (cumulative): n/a ·Citation Count: 1 Recent authors with related interests Concepts in this article powered by Concepts inOn convexity of MQAM's and MPAM's bit error probability functions Convex function In mathematics, a real-valued function defined probability of on an interval is called convex (or convex downward or concave upward) if the graph of the function lies below the line segment joining any two points of the graph. Equivalently, a function is convex if its epigraph (the set of points on or above the graph of the function) is a convex set. More generally, this definition of convex functions probability of error makes sense for functions defined on a convex subset of any vector space. morefromWikipedia Function (mathematics) In mathematics, a function is a relation between a set of inputs and a set of potential outputs with the property that each input is related to exactly one output. An example of such a relation is defined by the rule f(x) = x, which relates an input x to its square, which are both real numbers. The output of the function f corresponding to an input x is denoted by f(x) (read "f of x"). If the input is ¿3, then the output is 9, and we may write f(¿3) = 9. morefromWikipedia Bit error rate In digital transmission, the number of bit errors is the number of received bits of a data stream over a communication channel that have been altered due to noise, interference, distortion or bit synchronization errors. The bit error rate or bit error ratio (BER) is the number of bit errors divided by the total number of transferred bits during a studied time interval. BER is a unitless per
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