difference between the two base station signals. The parameters Ck and Dj are taken to be fixed cross-correlation con- stants. The only random variables here are the binary data bits on these inter- fering spread-spectrum signals. They are given by the independent binary random variables ak and bj, which take on values of 1 with equal proba- bility. The expectation, E, is taken over only these binary random variables. For the moment, we shall retain as a constant. Since the binary random variables are independent, we have (3B.7) Appendix 3B. Error Bounds for Interference-Limited Channels (3B.8) Next we use the inequality cosh x (3B.9) to obtain the bond ()((i + (3B.10) At this point, we make one simplifying assumption about the base station signals. We assume that the interference terms of the interfering base sta- tion's in-phase and quadrature coordinates are identical and, consequently, that each base station will "balance" out the load into its in-phase and quad- rature transmissions. Thus, we assume that (3B.11) and define the term J as (3B.12) (3B.13) and the total bound becomes (3B.14) which is valid for any r > 0. The value of r that minimizes the bound is eas- ily found to be (3B.15) Commercial Applications which then gives the final form of the upper bound (3B.16) Note that since A2/2 = Eb, this Chernoff bound is exactly the same as the ideal differentially coherent demodulated DBPSK bit error rate against white Gaussian noise with noise spectral density of No = J0/2. Thus, we have the natural measure of Eb/No given by Eg/No =A2/Jo (3B.17) where J is the sum of the squares of all correlation values of interference at the output sample of the mobile unit's codeword-matched filter. The "balance" assumption that (3B.18) eliminated the phase term from the bound. Note that by following the above discussion, interference signals from sev- eral base stations would give basically the same result where J is the sum of the squares of the cross-correlation values of all interfering signals from all other base stat