Performance of Coded FH/MFSK in a Worst-Case Tone Jamming Channel
Author | : P. J. Crepeau |
Publisher | : |
Total Pages | : 31 |
Release | : 1984 |
ISBN-10 | : OCLC:227624972 |
ISBN-13 | : |
Rating | : 4/5 (72 Downloads) |
Download or read book Performance of Coded FH/MFSK in a Worst-Case Tone Jamming Channel written by P. J. Crepeau and published by . This book was released on 1984 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: Several block and convolutional coding options are considered which are applicable to the noncoherent detection of FH/MFSK (Frequency Hopped/Multiple Frequency Shift Keying) signals in the presence of tone jamming. The tone jamming model used in this report is the worst-case tone jamming for an uncoded system. Using decoded probability of bit error as a performance criterion, we show that large signaling alphabets yield poor performance in a tone jamming environment. Furthermore, when hard-decision quantization is used, the degradation of a coded system in tone jamming over worst-case partial band noise jamming is the same as the corresponding degradation for the uncoded system: 4.3 dB for M=2, 6.3 dB for M=4, 8.3 dB for M=8, and increasing thereafter without bound as M approaches infinity. The poor performance of coded systems with hard-decisions in tone jamming can be improved by about 10 dB by using soft-decision quantization assisted by perfect jammer state side-information. For the binary case the results obtained by using soft-decision quantization are about 1 dB better than those obtained for the partial band noise channel, showing that the worst-case channel for the uncoded system is not necessarily the worst-case channel for a coded system when side-information is available. The use of small alphabets and soft-decision quantization is recommended for coded FH/MFSK systems in a tone jamming environment. A major issue to be addressed in future studies concerns the type of soft-decision decoding to be used. An approach is needed that is realizable and will give performance close to that of pure soft-decisions with side-information while being free of the problems associated with obtaining perfect side information.