leaver techniques, coded symbols are written into a RAM and read out pseudorandomly. There may be several possible read out patterns, each stored in a read only memory (ROM). For each interleaved output block, a PN sequence can be used to select one of the read out pat- terns. (See Clark and Cain [5] and Richer [12].) The main point of this discussion is that channels with memory can be con- verted into essentially memoryless channels at a cost of buffer storage and transmission delay. This cost can become prohibitive if the channel memory is very long compared to the transmission time per coded symbol. Chapter Chapter 4 GENERAL ANALYSIS OF ANTI-JAM COMMUNICATION SYSTEMS The evaluation of bit error probabilities for anti-jam communication systems is generally more difficult than for conventional communication systems. This partly because of the fact that intentional jamming signals can be more varied than the additive Gaussian noise model which is typically assumed in conventional communication systems. In addition, most anti-jam com- munication systems use coding techniques where coding gains at 10-5 bit error rates are typically 30 dB to 60 dB compared to 4 dB to 5 dB with the additive Gaussian noise channel. (This will be shown in greater detail in Part 2, Chapters 1 and 2.) Even with conventional communication systems, the evaluation of exact coded bit error probabilities is usually difficult to do and, thus, easy-to-evaluate upper bounds are used [1], [2], [3]. The purpose of this chapter is to present a general expression for upper bounds on coded bit error probabilities which apply to all coded communi- cation systems that use enough interleaving and deinterleaving SO that the channel can be modeled as memoryless. We shall show that these error bounds are tight over ranges of interest by comparing them with exact bit error probabilities when they can be found. They are also applicable to arbitrary decoding decision metrics and a wide class of detectors. This generalization is necessary for anti-jam communi