ctly a function of the symbol error probability of the inner code denoted Ps. That is, Pb=F(Ps). (4.130) In Appendix 4C, a table showing this relationship for various RS codes is presented. 4.11 SUMMARY OF BIT ERROR BOUNDS We conclude this chapter with tables of some basic expressions for bit error bounds of direct sequence spread coherent BPSK systems with pulse jam- ming and frequency-hopped spread non-coherent MFSK systems with par- tial-band noise jamming. These expressions are based on the discussion in this chapter. There are many other detector types such as detectors with var- ious quantizations, clipping, and rank order lists which have not been included here. The basic analysis approach presented in this chapter, how- ever, can be applied to derive easy to evaluate bit error bounds for these more complex detectors. Some of these will be discussed in Part 2, Chapters 1 and 2. Recall that regardless of the use of coding the energy per bit-to-jammer noise ratio, EIN is defined by (4.3). With time-continuous jamming of DS/BPSK systems, the bit error bound has the same form as for the addi- tive white Gaussian noise channel. Similarly, with broadband noise jamming of FH/MFSK the bit error bound has the same form as for the additive white Gaussian noise channel. 4.11.1 DS/BPSK with Pulse Jamming Table 4.1 presents the various expressions for the channel parameter D for DS/BPSK systems with pulse jamming. Here p is the fraction of time the sys- tem is being jammed where continuous jamming is the special case of p = 1. Summary of Bit Error Bounds Table 4.1. DS/BPSK with pulse jamming Jammer State Metric Information Pb < G(D); E = REb R = 1 - log(1 + D) bits/symbol D = exp(-EJN) Continuous Jamming D = pexp(-pE/N) Pulse Jamming D = - D = V4e(1 -e);e=pQ(V2pE/Nj For soft decision detectors the metric has the form m(y,x; z) = ((c(z)y: (4.131) while hard decision detectors have the metric y=x X. (4.132) When there is jamming state information c(0) >> c(1). (4.133) That is, the unjammed metric values are given much mo