Error Probability In Wireless Communication
Contents |
Advanced search) All papers Titles Authors Abstracts Full text Help pages Full-text links: Download: PDF Other formats (license) Current browse context: cs.IT
Bit Error Rate Example
Probability in Wireless Sensor Networks with Imperfect Sensing and Communication for Different Decision Rules Authors: Pedro H. J. Nardelli, Iran Ramezanipour, Hirley Alves, Carlos H. M. de Lima, Matti Latva-aho (Submitted on 10 Aug 2015
Bit Error Rate Vs Snr
(v1), last revised 16 Feb 2016 (this version, v2)) Abstract: This paper presents a framework to evaluate the probability that a decision error event occurs in wireless sensor networks, including sensing and communication errors. We consider a scenario where sensors need to identify whether a given event has occurred based on its periodic, noisy, observations of a given signal. Such information about the signal needs to be sent to bit error rate pdf a fusion center that decides about the actual state at that specific observation time. The communication links -- single- or multi-hop -- are modeled as binary symmetric channels, which may have different error probabilities. The decision at the fusion center is based on OR, AND, K-OUT-OF-N and MAJORITY Boolean operations on the received signals associated to individual sensor observations. We derive closed-form equations for the average decision error probability as a function of the system parameters (e.g. number of sensors and hops) and the input signal characterization. Our analyses show the best decision rule is closely related to the frequency that the observed events occur and the number of sensors. In our numerical example, we show that the AND rule outperforms MAJORITY if such an event is rare and there is only a handful number of sensors. Conversely, if there is a large number of sensors or more evenly distributed event occurrences, the MAJORITY is the best choice. We further show that, while the error probability using the MAJORITY rule asymptotically goes to 0 with increasing number of sensors, it is also more susceptible to higher channel error probabilities. Subjects: Information Theory (cs.IT) Citeas: arXiv:1508.02253 [cs.IT] (or arXiv:1508.02253v2 [cs.IT] for this version) Submission histo
be challenged and removed. (March 2013) (Learn how and when to remove this template message) 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 Error Rate Matlab
bit synchronization errors. The bit error rate (BER) is the number of bit errors per unit acceptable bit error rate time. The bit error ratio (also BER) is the number of bit errors divided by the total number of transferred bits during a studied packet error rate time interval. BER is a unitless performance measure, often expressed as a percentage.[1] The bit error probability pe is the expectation value of the bit error ratio. The bit error ratio can be considered as an approximate estimate of the https://arxiv.org/abs/1508.02253 bit error probability. This estimate is accurate for a long time interval and a high number of bit errors. Contents 1 Example 2 Packet error ratio 3 Factors affecting the BER 4 Analysis of the BER 5 Mathematical draft 6 Bit error rate test 6.1 Common types of BERT stress patterns 7 Bit error rate tester 8 See also 9 References 10 External links Example[edit] As an example, assume this transmitted bit sequence: 0 1 1 0 0 0 https://en.wikipedia.org/wiki/Bit_error_rate 1 0 1 1 and the following received bit sequence: 0 0 1 0 1 0 1 0 0 1, The number of bit errors (the underlined bits) is, in this case, 3. The BER is 3 incorrect bits divided by 10 transferred bits, resulting in a BER of 0.3 or 30%. Packet error ratio[edit] The packet error ratio (PER) is the number of incorrectly received data packets divided by the total number of received packets. A packet is declared incorrect if at least one bit is erroneous. The expectation value of the PER is denoted packet error probability pp, which for a data packet length of N bits can be expressed as p p = 1 − ( 1 − p e ) N {\displaystyle p_{p}=1-(1-p_{e})^{N}} , assuming that the bit errors are independent of each other. For small bit error probabilities, this is approximately p p ≈ p e N . {\displaystyle p_{p}\approx p_{e}N.} Similar measurements can be carried out for the transmission of frames, blocks, or symbols. Factors affecting the BER[edit] In a communication system, the receiver side BER may be affected by transmission channel noise, interference, distortion, bit synchronization problems, attenuation, wireless multipath fading, etc. The BER may be improved by choosing a strong signal strength (unless this causes cross-talk and more bit errors), by choosing a slow and robust modulation scheme or line coding scheme, and by applying channel coding schemes
be down. Please try the request again. Your cache administrator is webmaster. Generated Thu, 13 Oct 2016 02:05:01 GMT by s_ac4 (squid/3.5.20)