eases with K. At Pb's of 10-5 and lower, this gap exceeds 30 dB for any K, illustrating the effectiveness of worst-case partial-band noise jamming against uncoded FH/MFSK signals at typical operating points. (2.25) indicates that Pwc becomes very small for large Eb/N3's; that is, a worst case noise jammer concentrates its power in a small portion of Wss at low Pb's. The signals do not get jammed most of the time, but those that do are likely to result in errors. This is an indication that some form of coding redundancy that causes data decisions to depend on multiple symbol trans- missions can reduce the effectiveness of partial-band jamming; the degree to which this statement is true will become evident in Section 1.3. Table 2.1 Parameters associated with performance of uncoded FH/MFSK signals in worst case partial-band noise, as defined in (2.25). y, dB e-1=.3679 .2329 .1954 .1812 .1759 -1.41 Non-Coherent Frequency-Hopped Systems p=p WC Eb/N, dB Figure 2.9. Degradation in FH/MFSK (M = 2x) performance due to worst case (p = Pwc <1) partial-band noise relative to broadband (p = 1) noise jamming. 2.2.2 Multitone Jamming A second, sometimes more effective, class of intelligent FH jamming than partial-band noise is multitone or multiple CW tone interference. In this cat- egory, the jammer divides its total received power J into Q distinct, equal power, random phase CW tones. These are distributed over the spread-spec- trum bandwidth Wss according to one of several strategies illustrated in Figure 2.10 and discussed in detail below. One of the reasons that multitone jamming can be more effective against FH/MFSK signals than partial-band noise is that CW tones are the most efficient way for a jammer to inject energy into the non-coherent detectors. The analysis below involves several simplifying assumptions to allow us to focus on the issues of interest. We continue to neglect receiver thermal noise under the assumption that it is dominated by the jamming interference. As shown in Figure 2.10, we assume that each jamm