A New Frame Synchronization Algorithm for Linear Periodic Channels With Memory
| Autor: | Oren Kolaman, Ron Dabora |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Frame synchronization (video)
General Computer Science Computer science Cyclostationary process linear periodically time-varying channels Communications system symbols.namesake Narrowband hypothesis testing Synchronization (computer science) Wireless General Materials Science cyclostationary signals CMA equalizer Computer Science::Information Theory business.industry General Engineering likelihood ratio test Transmission (telecommunications) Gaussian noise Frame synchronization symbols lcsh:Electrical engineering. Electronics. Nuclear engineering business lcsh:TK1-9971 Algorithm |
| Zdroj: | IEEE Access, Vol 8, Pp 133430-133450 (2020) |
| ISSN: | 2169-3536 |
| DOI: | 10.1109/access.2020.3009131 |
| Popis: | Identifying the start time of a sequence of symbols received at the receiver, commonly referred to as frame synchronization, is a critical task for achieving good performance in digital communications systems employing time-multiplexed transmission. In this work we focus on frame synchronization for linear channels with memory, in which the channel impulse response is periodic and the additive Gaussian noise is correlated and cyclostationary. Such channels appear in many communications scenarios, including narrowband power line communications and interference-limited wireless communications. We derive frame synchronization algorithms based on simplifications of the optimal likelihood-ratio test, assuming the channel impulse response is unknown at the receiver, which is applicable to many practical scenarios. The computational complexity of each of the derived algorithms is characterized, and a procedure for selecting nearly optimal synchronization sequences is proposed. The algorithms derived in this work achieve better performance than the noncoherent correlation detector, and, in fact, facilitate a controlled tradeoff between complexity and performance. |
| Databáze: | OpenAIRE |
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