Performance of FFH/BFSK Systems with Convolutional Coding and Soft Decision Viterbi Decoding Over Rician Fading Channels with Partial-Band Noise Interference
Author | : |
Publisher | : |
Total Pages | : 80 |
Release | : 1995 |
ISBN-10 | : OCLC:227852488 |
ISBN-13 | : |
Rating | : 4/5 (88 Downloads) |
Download or read book Performance of FFH/BFSK Systems with Convolutional Coding and Soft Decision Viterbi Decoding Over Rician Fading Channels with Partial-Band Noise Interference written by and published by . This book was released on 1995 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 (FFH(BFSK) spread spectrum system is performed. The signal is transmitted through a Rician fading channel with partial band noise interference. The receiver structures examined are the conventional receiver with no diversity, the conventional receiver with diversity and the assumption of perfect side information, and the self normalized combining receiver with diversity. The self normalized receiver minimizes the effects of hostile partial band interference, while diversity alleviates the effects of fading. It is found that with the implementation of soft decision viterbi decoding the performance of the self normalized receiver is improved dramatically for moderate coded bit energy to partialband noise power spectral density ratio (EbNI). Coding drives the jammer to a full band jamming strategy for worst case performance. Nearly worst case jamming occurs when barrage jamming is employed and there is no diversity even in cases where there is very strong direct signal. Performance improves as the constraint length of the convolutional code is increased. For the most powerful convolutional codes, performance is seen to degrade slightly with increasing diversity except in instances of a very weak direct signal. Also, soft decision decoding is found to be superior to hard decision decoding by approximately 4 dB at moderate Eb/NI.