A Method for Predicting the Bit Error Rate of Wireless Digital Communication Equipment

Author(s):  
Biao Wang ◽  
Xue-tian Wang ◽  
Hang Li ◽  
Hong-min Gao ◽  
Yong-wei Sun
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Ze Gao ◽  
Lin Lin

With the development of technology and the times, the development of new media technology and interactive installation art has slowly entered the vision of our audience. It is simply “silent art.” The public no longer “retires” like the traditional one, but participates in it and swims with the artists in the world of art. This article is aimed at studying the application of artificial intelligence and wireless network communication to the application of interactive installation art. Through the optimization of various communication equipment and the continuous advancement of various algorithms, we can strengthen the communication and connection between our interactive installation art. This article proposes that with the addition of artificial intelligence and wireless network communication, the interaction between artists and audiences may be more fun, so that we can be more colorful in our lives. The experimental results in this article show that when performing wireless network communication, the communication delay rate of the intelligent algorithm with artificial intelligence is much lower than that of the one without it, which shows that they can better transmit information to the control end. When affected by the outside world, the bit error rate of wireless network communication will increase, however, the artificial intelligence algorithm is added to his impact range, and his bit error rate increase is obviously not so high. In the process of wireless network communication, the improved algorithm is definitely better than the nonimproved algorithm in terms of energy consumption, communication delay, and bit error rate. Through the enhancement of signals and the selection of materials for communication equipment, these are all in continuous progress, and in this respect, are in continuous exploration. Compared with other algorithms, the ml algorithm has improved positioning accuracy by about 70%, 65%, and 30%. Increasing the number of nodes in the transmission signal can greatly reduce the number of hops between nodes, correspondingly reducing the hop distance error, correspondingly reducing the distance estimation error, and improving the positioning accuracy. It can solve the technical barriers of interactive installation art faster.


The digital communication technologies have gained immense significance as it provides secure and error free services. One of the major advantages of digital communication is that they are much resistant to transmitted as well as interpreted errors. For ensuring the security of data, the most suitable method is to use spread spectrum technique. The spread spectrum technique has gained immense popularity for use in various systems as the spreading of the spectral bandwidth offer many advantages, including the establishment of secure communications, increasing resistance to interference, noise rejection, and so on. The signals which are modulated by using these techniques cannot be jammed and are very hard to interfere. This paper presents the results of investigation of BPSK based direct sequence spread spectrum systems for Additive White Gaussian Noise (AWGN) and undersea channels. The bit error rate performance of BPSK based direct sequence spread spectrum systems has been simulated for the AWGN channel and the results have been plotted.


2015 ◽  
Vol 9 (1) ◽  
pp. 41
Author(s):  
Saed Ali Thuneibat ◽  
Huthaifa Al_Issa ◽  
Abdallah Ijjeh

<p>The Bit Error Rate (BER) is a key parameter of the Quality of Service (QoS) for engineers and designers of digital communication systems and networks. At the present  time, a set of models and methods are exist for calculating the BER. But these methods are complex and require large computing cost.</p><p>In this paper, we provide a new model for calculating the BER. This model simplifies the procedures in the existing models and reduces the computing time. In the same time, the proposed model save the accuracy and the state consideration of existing models.</p>


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