An　adaptive　threshold-based　Call　Admission　Control　(CAC)　scheme　used　in　wireless/mobile　network　for　multi-class　services　is　proposed.　In　the　scheme,　each　class＇s　CAC　thresholds　are　solved　through　establishing　a　reward-penalty　model　which　tries　to　maximize　network＇s　revenue　in　terms　of　each　class＇s　average　new　call　arrival　rate　and　average　handoff　call　arrival　rate,　the　reward　or　penalty　when　network　accepts　or　rejects　one　class＇s　call　etc.　To　guarantee　the　real　time　running　of　CAC　algorithm,　an　enhanced　Genetic　Algorithm　is　designed.　Analyses　show　that　the　CAC　thresholds　indeed　change　adaptively　with　the　average　call　arrival　rate.　The　performance　comparison　between　the　proposed　scheme　and　Mobile　IP　Reservation(MIR)　scheme　shows　that　with　the　increase　of　average　call　arrival　rate,　the　average　new　Call　Blocking　Probability(CBP)　and　the　average　Handoff　Dropping　Probability　(HDP)　within　2000　simulation　intervals　of　the　proposed　scheme　are　confined　to　lower　levels,　and　they　show　approximatively　periodical　trends　of　first　rise　and　then　decline.　While　these　two　performance　metrics　of　MIR　always　increase.　At　last,　the　analysis　shows　the　proposed　scheme　outperforms　MIR　in　terms　of　network＇s　revenue.