A new probability density function enhancing packet detection analysis for low-SNR links

被引：7
|
作者：
Lu, Guofeng [1 ]
Greenstein, Larry J.
Spasojevic, Predrag
机构：
[1] JP Morgan Chase Corp, Asset Management, New York, NY 10017 USA
[2] Rutgers State Univ, Dept Elect & Comp Engn, WINLAB, N Brunswick, NJ 08902 USA
来源：
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY | 2007年 / 56卷 / 03期
基金：
美国国家科学基金会;
关键词：
orthogonal frequiency-division multiplexing (OFDM); packet detection; ultrawideband (UWB);
D O I：
10.1109/TVT.2007.895592
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Packet detection is the first task that a receiver has to perform in a random access communication scheme. The implementation and evaluation of different packet detection methods depend on the probability density functions (PDFs) of the decision variables and their construction process. This paper provides a new PDF that enables the analysis of one method, due to Schmidl and Cox (SC), in packet detection. The new PDF enables determination of the detection threshold and performance evaluation. The new PDF also avoids the Gaussian assumption in the low-signal-to-noise-ratio (SNR) regime that is typical in the ultrawideband systems and converges to Gaussian for high SNR. Comparison with other packet detection methods shows that the SC method is both robust to channel multipath and provides a good tradeoff between performance and signal processing complexity.
引用
收藏
页码：1230 / 1238
页数：9
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