Improving Decoding Performance of 5G NR PBCH by the Altering Subcarrier Mapping Scheme

Author(s):  
Junseong Kim ◽  
Sungyeol Back ◽  
Suyong Choi ◽  
Wangrok Oh
Author(s):  
Azlina Idris ◽  
Norhayati Abdullah ◽  
Darmawaty Mohd Ali ◽  
Norsuzila Ya'acob ◽  
Hanis Adiba Mohamad

2010 ◽  
Vol 14 (7) ◽  
pp. 638-640 ◽  
Author(s):  
Shaohua Chen ◽  
Fang Liu ◽  
Xin Zhang ◽  
Cong Xiong ◽  
Dacheng Yang

2016 ◽  
Vol E99.B (2) ◽  
pp. 364-369
Author(s):  
Jun-Young WOO ◽  
Kee-Hoon KIM ◽  
Kang-Seok LEE ◽  
Jong-Seon NO ◽  
Dong-Joon SHIN
Keyword(s):  

2015 ◽  
Vol 12 (1) ◽  
pp. 25
Author(s):  
Nur Farahiah Ibrahim ◽  
Zahari Abu Bakar ◽  
Azlina Idris

Channel estimation techniques for Multiple-input Multiple-output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) based on comb type pilot arrangement with least-square error (LSE) estimator was investigated with space-time-frequency (STF) diversity implementation. The frequency offset in OFDM effected its performance. This was mitigated with the implementation of the presented inter-carrier interference self-cancellation (ICI-SC) techniques and different space-time subcarrier mapping. STF block coding in the system exploits the spatial, temporal and frequency diversity to improve performance. Estimated channel was fed into a decoder which combined the STF decoding together with the estimated channel coefficients using LSE estimator for equalization. The performance of the system was compared by measuring the symbol error rate with a PSK-16 and PSK-32. The results show that subcarrier mapping together with ICI-SC were able to increase the system performance. Introduction of channel estimation was also able to estimate the channel coefficient at only 5dB difference with a perfectly known channel.


2012 ◽  
Vol 605-607 ◽  
pp. 2561-2568
Author(s):  
Qin Wang ◽  
Shou Ning Qu ◽  
Tao Du ◽  
Ming Jing Zhang

Nowadays, document retrieval was an important way of academic exchange and achieving new knowledge. Choosing corresponding category of database and matching the input key words was the traditional document retrieval method. Using the method, a mass of documents would be got and it was hard for users to find the most relevant document. The paper put forward text quantification method. That was mining the features of each element in some document, which including word concept, weight value for position function, improved weights characteristic value, text distribution function weights value and text element length. Then the word’ contributions to this document would be got from the combination of five elements characteristics. Every document in database was stored digitally by the contribution of elements. And a subject mapping scheme was designed in the paper, which the similarity calculation method based on contribution and association rule was firstly designed, according to the method, the documents in the database would be conducted text clustering, and then feature extraction method was used to find class subject. When searching some document, the description which users input would be quantified and mapped to some class automatically by subject mapping, then the document sequences would be retrieved by computing the similarity between the description and the other documents’ features in the class. Experiment shows that the scheme has many merits such as intelligence, accuracy as well as improving retrieval speed.


2018 ◽  
Vol 67 (4) ◽  
pp. 3674-3678 ◽  
Author(s):  
Husam Elfadil ◽  
Mehdi Maleki ◽  
Hamid Reza Bahrami

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