Chrome Extension
WeChat Mini Program
Use on ChatGLM

On the Coexistence of Primary and Secondary Users in Spectrum-Sharing Broadcast Channels

IEEE International Conference on Communications (ICC)(2013)CCF C

King Abdullah Univ Sci & Technol | Univ Quebec

Cited 6|Views7
Abstract
In this paper, we consider a broadcast channel in spectrum-sharing networks, where the base station schedules licensed primary users (PUs) and cognitive secondary users (SUs) simultaneously. Based on such a framework, we present a transmission strategy in the light of dirty paper coding. In order to promise the PUs' quality of service (QoS) in the broadcasting, the base station chooses codewords for the users by taking into account that the codewords pertaining to SUs can be pre-subtracted from those pertaining to PUs as if there were no interference from the secondary's data to the primary's data. For the purpose of performance evaluation, by taking capacity behavior and bit error rate (BER) as metrics, we study the achievable data rate regions for both types of users with the introduced design, and analyze the BER performance in corresponding systems implemented with hierarchical modulation. Numerical results substantiate that with flexible management of the spectrum resources, our proposed scheme provides more communication opportunities for SUs while maintaining PUs' QoS at an acceptable level.
More
Translated text
Key words
broadcast channels,cognitive radio,error statistics,modulation coding,network coding,performance evaluation,quality of service,radio spectrum management,radiofrequency interference,BER,PU,QoS,SU,base station scheduling,bit error rate,codeword,cognitive secondary user,dirty paper coding,hierarchical modulation,licensed primary user,performance evaluation,primary data interference,quality of service,secondary data interference,spectrum resource management,spectrum-sharing broadcast channel network
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Related Papers
1977

被引用68 | 浏览

Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest