noise with bit energy-to-noise ratio given by (2.2). If g is the bit energy-to-noise ratio that achieves a desired bit error probability, then the total interference in the channel must be bounded by J Eri=(M)s. S. (2.8) Figure 2.9 illustrates the special case where e = S;l = 1,2, = ..., L (2.9) plotting the maximum number of equal power interference signals at the receiver that can be tolerated as a function of the number of pseudoran- dom sequence chips N per information bit, called the processing gain (PG). This is parameterized by the required bit energy-to-noise ratio Y, which varies with the bit error probability requirement, the choice of coding tech- nique, and the decoding metric. Since we assume maximum power for the total interference in giving Y, we can use standard error probability curves for the additive white Gaussian noise channel to determine the required 10,000 1,000 20.00 1,000 10,000 100,000 PG, PROCESSING GAIN Figure 2.9. Simultaneous transmissions versus process gain. Spread-Spectrum Multiple Access with DS/BPSK Waveforms value of y to achieve a desired coded or uncoded bit error probability. Keep in mind that these results assume no background or receiver noise. This must ultimately be considered for some cases, as described in Chapter 3 of Part 1. Background noise can be added directly to the equivalent inter- ference. The point-to-point SSMA analysis for DS/BPSK waveforms is the same as that of the continuous jammer case covered in Chapter 1 of Part 2. For CDMA where pseudorandom sequences are designed to have low cross- correlation the multiple access performance will improve somewhat [63]-[76]. For the CDMA case the SSMA results here can be viewed as a bound on performance. Generally, when the number of CDMA signals is large the SSMA results presented here are close [65]. The results here generalize directly to fading channels. With Rayleigh fad- ing the bit energy-to-noise ratio becomes (2.10) where J is the average interference power and S is the average signal power. The curves used