Accession Number:

ADA280041

Title:

Error Probabilities of FFH/BFSK with Noise Normalization and Soft Decision Viterbi Decoding in a Fading Channel with Partial-Band Jamming

Descriptive Note:

Master's thesis

Corporate Author:

NAVAL POSTGRADUATE SCHOOL MONTEREY CA

Personal Author(s):

Report Date:

1994-03-01

Pagination or Media Count:

74.0

Abstract:

An error probability analysis of a communications link employing convolutional coding with soft decision Viterbi decoding implemented on a fast frequency-hopped, binary frequency-shift keying FFHBFSK spread spectrum system is performed. The signal is transmitted through a frequency nonselective, slowly fading channel with partial-band jamming. Noise normalization combining is employed at the receiver to alleviate the effects of partial-band jamming. The received signal amplitude of each hop is modeled as a Rician process, and each hop is assumed to fade independently. It is found that with the implementation of soft decision Viterbi decoding that the performance of the receiver is improved dramatically when the coded bit energy to partial-band noise power spectral density ratio EbN1 is greater than 10dB. At higher Eb N1, the asymptotic error improves dramatically and varies from 10 to the -6 power to 10 to the -12 power depending on the constraint length v, number of hopsbit L, and the strength of the direct signal alpha22alpha2. In addition, nearly worst case jamming occurs when the jammer uses a full band jamming strategy, even when Ll and there is a very strong direct signal alpha22alpha 2 100. Due to noncoherent combining losses, when the hopper bit ratio is increased, there is some degradation at moderate EbN1. Furthermore, when a stronger code is used i.e., the constraint length is longer, performance improves, especially for high EbN1 where the asymptotic error is reduced. Finally, soft decision decoding improves performance over hard decision decoding from 4 to 8dB At moderate EbN1 depending on the code rate and with a much lower asymptotic error at high EbN1. Fast frequency hopping, Noise normalization, Convolutional coding.

Subject Categories:

  • Statistics and Probability
  • Radiofrequency Wave Propagation
  • Radio Communications

Distribution Statement:

APPROVED FOR PUBLIC RELEASE