itted by the k-th transmitter is of the form (1.2) where Nk{j:(k-1)D<jskD} (1.3) and {a}} is a data-dependent set of coefficients. We will refer to the above as an orthogonal communication system complex of multiplicity K. Of course, real systems generally radiate real signals. The reader may wish to view mk(t) as the modulation on the radiated signal Re{mk(t) exp (jwct + 0)}. Without loss of generality, we can dispense with the shift to RF during this initial discussion. In a simplified jamming situation, the signal Zi(t) observed at the i-th receiver in the receiving complex might be (1.4) where ni(t) represents internally generated noise in the i-th receiver, J(t) is an externally generated jamming signal, and the K-term sum represents the total output signal of the transmitter complex. One signal processing A Basis for a Jamming Game strategy for the i-th receiver is to project the received signal onto the set of basis functions for the i-th transmitter's signal space, thereby calculating = dt for all Ni. (1.5) In the absence of jamming and receiver noise, the properties of the ortho- normal basis insure that Zj = aj, and thus, the i-th receiver correctly discov- ers the data dependent set of coefficients {aj}, j E Ni, used by the i-th transmitter. Both the jamming and receiver noise signals can be expanded in terms of the orthonormal basis as (1.6) (1.7) where Jo(t) represents that portion of the jamming signal orthogonal to all of the 2TWSs basis functions used in producing the composite signal. The receiver noise component noi(t) likewise is orthogonal to all possible trans- mitted signals. These representations indicate that, in general, the projection (1.5) of Zi(t) onto 4;(t) in the i-th receiver produces for all j E N;. (1.8) The everpresent thermal noise random variable Nij, assumed complex Gaussian, independent, and identically distributed for different values of i and/or j, represents the relatively benign receiver perturbations in the absence of jamming. The jamming signal coefficients Jj are less 