he list metric for larger alpha- bet size M = 32. We compare the full list (L* = M = 32) metric with the energy metric (EM), which is near optimum for the additive white Gaussian noise channel, and the hard decision metric (HDM). The probability qe that the transmitted signal is l-th on the list is plotted in Figure 2.23 for the worst case partial-band noise jammer when M = 8. Note that ql for l = 2, 3, 8 are not too far apart. This result is contrasted with the worse case tone jam- mer results shown in Figure 2.24, which show a much wider divergence in the values of qe for l = 2, 3, 8. Against tone jamming there is more infor- mation in the list detector outputs. WITH JSI WITHOUT JSI L* = 32 32 EM (w/o JSI) EcIN, (dB) Figure 2.22. R0 versus EI against worst case tone jamming (M = 32). Multiple Access Rather than assume the worst case multitone jammer, Creighton [116] studied the list detector with maximum-likelihood metrics when there are L simultaneously transmitting radios with FH/MFSK signals of equal power at the receiver. He assumed the following: 1. All FH/MFSK signals have the same power level at the receiver. 2. Over a chip time interval, the average power of the sum of tones at a given frequency equals the sum of their average powers. 3. All radios are time synchronized and have signals hopping at the same time. 4. All hopping patterns are independent of each other and consist of inde- pendent uniformly distributed hop frequencies. 5. The performance is limited by mutual interference and receiver noise can be ignored. With these assumptions the following parameters were selected: = diversity or number of MFSK chips for each M-ary symbol = list size number of simultaneously transmitting radios Two types of maximum-likelihood metrics were selected. The first metric assumes only knowledge of the probabilities {qk} and uses the metric defined by (2.29). The second metric assumes that additional side infor- mation is available in the form of knowing the number of M chip energy detector outputs that consist o