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                            Library & Multimedia
 Performance analysis and enhancement of the next generation cellular networks
NCJ Number
              305920

Author(s)
          Xiang Yu;
                        Chunming Qiao;
                        Xin Wang;
                        Dahai Xu
Date Published

2006
Length
              12 pages
Annotation
              This study examined the impact of long-range- dependent (LRD) data traffic on the statistical characteristics of multi-access interference (MAI) and signal to interreference-plus-noise ratio (SINR) in a code division multiple access (CDMA) network.
Abstract
              As more and more wireless subscribers access the Internet through cellular networks, Internet data traffic, which is known to be long range dependent (LRD), will soon dominate the conventional voice traffic. Through analysis and simulation, the authors show that that the time-scaled MAI and SINR have slow decaying tail distributions due to the LRD data traffic. As a result, the outage probability is larger for data users than that for voice users. To improve the performance of the CDMA network in the presence of LRD data traffic, the authors propose a variable period prediction scheme to predict MAI or the equivalent number of active users. They show that the proposed variable period prediction is not only more accurate for data users but also less memory-consuming than existing fixed period prediction. In addition, rate control based on variable period prediction can achieve lower outage probability and higher throughput for data users than that based on fixed period prediction. (Published abstract provided)
      
  
          Additional Details
Grant Number(s)
        2004-LT-BX-K027


  
  
        
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        NIJ-Sponsored


  
  
        
  Award
        CDMA/IP-based System for Interoperable  Public Safety Radio Communications
    
  
  
Date Published: January 1, 2006
    
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