Performance of soft metrics for convolutional coded asynchronous fast FHSS-MA networks using BFSK under Rayleigh fading

Performance of robust soft decoding metrics is examined for use in convolutional coded asynchronous fast frequency-hop spread-spectrum multiple-access networks using binary frequency-shift keying under Rayleigh fading channels. For comparison, maximum-likelihood metrics based on a Gaussian approximation are derived. Significant gains are observed compared to hard decision decoding by using appropriate soft metrics.