 are the dual-K convolutional codes, which can be fairly effective against worst case jamming, with improved performance for lower codes rates 1/v. For a given class of codes, there are observations to be made with regard to the impact of the channel dimensionality K and the type of jamming on system performance. The variation in performance with K is illustrated in Figures 2.76-2.81. Recall that for uncoded FH/MFSK signalling with opti- mum diversity, the performance in worst case partial-band noise improved monotonically with K for moderate and lower Pb's (Figure 2.31); this behav- ior is adhered to by the orthogonal and dual-K convolutional codes. On the other hand, for worst case n = 1 band multitone jamming, Figure 2.51 showed that the best performance for uncoded signalling with optimum diversity is achieved for K = 2, with increasingly degraded performance for larger values of K. (This should be qualified by the reminder that the K = 1 performance could be made arbitrarily good for large enough amounts of diversity.) The dual-K performance in worst case multitone jamming con- forms to this behavior (without the K = 1 qualifier above), while the ortho- gonal convolutional codes in Figure 2.77 do not. Focussing on the dual-K convolutional code behavior, since performance improves with K for worst case partial-band noise, and degrades with K > 2 for worst case n = 1 band multitone jamming, the impact of the type of jam- ming becomes more significant for larger values of K. This effect is illustrated in Figure 2.82 for the rate 1/3 codes. In particular, at Pb = 10-5, noise jam- ming is about 1 dB more effective than multitone jamming for K = 1; the jam- ming effectiveness is reversed for K 2, with multitone jamming exhibiting a 3 dB advantage at K = 3, and a 7 dB advantage at K = 5 for this . The relative performance of all these codes in noise and multitone jam- ming is summarized in Table 2.12 at the benchmark Pb = 10-5. From a min/max perspective, if we wanted to choose the coded system that required the sm