ng a suburban channel model, but the one type of service included had a target bitrate of 500 kbit/s. Different approaches to CAC were implemented for further discussion and comparison. 8.5.1.1 Type A: Baseline - CAC Without Network Isolation and Without Protection for Existing Users This model is used to show the number of users that would be qualified if there were no CAC constraints on existing users. This means that, overall, those users with the best chan- nel conditions were allocated resources, irrespective of whether they were existing or new users. It would be expected that this approach would lead to the highest number of qualified users but there would be no enforced isolation. To implement the model, the steps used are shown below; changes to the basic steps are shown in bold. Whenever a new user comes, 1. store the current RB allocation and interference map; 2. omitted (Marking all existing QUs as PrUs); 3. use the game-theoretic approach to allocate resources to all users; 4. omitted (PrU compensation); 5. if one or more users are still unqualified, loop back to step 3 until the result converges or the maximum number of iterations is reached, or all the users become qualified; 6. reject any unqualified user, including unqualified PrUs. 8.5.1.2 Type B: Optimum Types - B1 and B2 This approach includes compensation for the PrUs (after the extra interference from the new user has occurred) by allocating extra RBs to any unqualified PrU. Here, two versions are shown (B1 and B2). B1 also includes a roll back to the previous state if 100% protection is not there for the PrUs, but this is omitted in B2 to show the penalty (in terms of number of qualified users). The steps are as follows: 1. Store the current RB allocation and interference map. 2. Mark all existing QUs as PrUs. 3. Use the game-theoretic approach to allocate resources to all the unqualified users (RB reallocation). 4. If the existing (protected) users have become unqualified, provide extra resource to those users (PrU compensation). 5. If one