ld need Eb/N1 = 14.21 dB with K = 2, and the worst case jam- mer would be n = 1 band multitone. In this sense, the (7,1) binary convo- lutional code is about 4 dB more powerful than the best repetition code against worst case jamming of FH/MFSK systems. Figure 2.83 examines the relative sensitivity of several coded FH/MFSK systems to variations in the partial-band noise fill factor p, for the specific case of K = 4 and Eb/N, = 10 dB. The p-axis uses a logarithmic scale SO that equal length intervals anywhere correspond to identical relative (e.g., percent) variations in p. From the communicator's viewpoint, a highly peaked curve is desirable because this implies that small deviations in p away from Pwc produce large reductions in jamming effectiveness. However, all three systems exhibit approximately the same sensitivity to changes in p. Note though that Pwc = .75 for uncoded signalling with optimum diver- sity, Pwc = .30 for 16-ary orthogonal convolutional coding, and Pwc = .15 for the dual-4, rate 1/2 convolutional code; furthermore, all three systems achieve comparable performance. This observation suggests a more sophis- ticated hybrid coding scheme for defeating partial-band noise jamming. Consider a two-way FH/16-FSK system which can select any of the cod- ing schemes of Figure 2.83. The receivers in this link must be able to mon- itor the jamming parameter p (e.g., by performing a fast Fourier transform over the entire spread-spectrum bandwidth). As an example, if one of the receivers determines that it is being jammed with partial-band noise for which p = .75, it could request that the transmitter at the other end of the DUAL- K, RATE 1/3 CONVOLUTIONAL CODES WC n= I BAND MULTITONE WC PARTIAL- BAND NOISE Eb/Nu,dB Figure 2.82. Impact of type of jamming on performance of dual-K, rate 1/3 convo- lutional codes with FH/MFSK signalling as a function of K. Assumes soft decision energy detection, linear combining metric, and perfect jamming state side information. Table 2.12 Required EIN, in dB to achieve Pb = 10