mitting a signal J(t) with constant power J in the system shown in Figure 3.6. An ideal coherent BPSK demodulator is assumed to follow the received signal y(t) multiplied by the PN sequence Basic Concepts and System Models c(t). Here, the channel output is ¹ (3.28) which is multiplied by the PN sequence c(t) to obtian r(t) = =c(t)y(t) = c(t)x(t) + c(t)J(t) s (t ) + c(t)J(t). (3.29) This is the ordinary BPSK signal imbedded in some additive noise given by c(t)J(t). The BPSK detector output which is optimum for broadband inter- ference [8] is r==VVE,+, (3.30) where d is the data bit for this T second interval. Eb = ST is the bit energy, and n is the equivalent noise component given by (3.31) The typical BPSK decision rule is ifr>0 (3.32) if   . Hence, the bit error probability is = pr{n>VE}} (3.33) assuming, without loss of generality, that d = -1. The noise term depends upon many PN chips, viz., (3.34) Assuming the jammer transmits broadband Gaussian noise of one-sided power spectral density given by (3.8), the terms J(t)cos wot dt (3.35) are independent zero-mean Gaussian random variables with variance Nj/2. Thus, n defined by (3.34) and rewritten as (3.36) Receiver noise which is typically modeled as additive white Gaussian noise is ignored here since jammer interference is assumed to dominate. In Section 3.9 we discuss this assumption. coswo+ MODULATOR GENERATOR RECEIVER CHANNEL TRANSMITTER Figure Basic Concepts and System Models is a zero-mean Gaussian random variable with variance N /2. For a contin- uous broadband noise jammer of constant power J the uncoded bit error probability is (3.37) where (3.38) is the Gaussian probability integral [8] and from (3.3) and (3.20), (Wss/Rb) = (J/S) (3.39) For large N, the above bit error probability also applies to most constant power jammer waveforms. This is based both on the assumption that the PN sequence {ck} is approximated as an independent binary sequence and the application of the Central Limit Theorem [9]. The details of this assumption are discussed in Part 1,