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Conditional probability density function based signal detection for OFDM-based transform domain communication systems
| Content Provider | Semantic Scholar |
|---|---|
| Author | Huang, Biao Wang, Jun Tang, Wanbin Li, Shaoqian |
| Copyright Year | 2010 |
| Abstract | The orthogonal frequency division multiplexing-based transform domain communication system (OFDM-TDCS) is a promising candidate for signaling transmission in Cognitive Radio (CR) networks. An important issue of OFDM-TDCS system is the effective signal detection scheme design when channel coding is applied. In this paper, a class of new hard-demodulation (HD) and soft-demodulation (SD) algorithms are proposed in a unified signal detection framework. Although HD is based on the maximum likelihood (ML) estimation while SD is to calculate the log-likelihood ratio (LLR) of each coded bit, both of them are derived from an identical conditional probability density function. To further improve the implementation efficiency of SD detector, a code table is established to facilitate the needed searching operation. Finally, simulations under IEEE 802.22 Profile C channel validate the proposed signal detection detectors in terms of bit error rate (BER). |
| Starting Page | 1 |
| Ending Page | 5 |
| Page Count | 5 |
| File Format | PDF HTM / HTML |
| DOI | 10.4108/crnet.2010.3 |
| Alternate Webpage(s) | http://eudl.eu/pdf/10.4108/crnet.2010.3 |
| Alternate Webpage(s) | https://doi.org/10.4108/crnet.2010.3 |
| Journal | 2010 5th International ICST Conference on Communications and Networking in China |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
