Iterative Randomized RA algorithm Sample Clauses

Iterative Randomized RA algorithm. (i-RRA) Here, a low-complexity, iterative randomized algorithm is proposed which runs in a semi-centralized manner as follows: first, the cellular users of each cell are initially assigned with orthogonal RBs, depending on the area they are located in (inner or outer). Secondly, assuming that N RBs are available in an either an inner or an outer area, each BS will randomly allocate one RB per associated D2D pair according to the aforementioned FFR allocation logic and the area that the pair is located in. This RB will be then subtracted from the corresponding to each cell available RB pool. In case that all RBs are occupied (highly dense D2D scenarios), a cellular resource can be reused by more than one D2D link. This implementation will run for up to a designated number of iterations M . Then, the BSs cooperatively opt the best allocation pattern among all. The criterion for finally choosing the best resource allocation pattern to be applied is the total network throughput, estimated as the cumulative cellular and D2D transmissions’ rates for all cells. The algorithmic steps are given in Algorithm 1. The proposed algorithm’s nature falls within the category of “embarrassing” parallel problems because iterations of the algorithm to explore the search space can be executed without requiring any communication between them [68]. Its computational complexity is O(M ), which means that it only increases linearly Algorithm 1: i-RRA algorithm Data: CUEs and DUEs’ location coordinates, Cb: set of CUEs in cell b, Lb: set of D2D links associated with cell b (input from MOCA framework), {N Inner {Nb }: inner-region available RBs in each cell b, }: outer-region available RBs in each cell b, Outer
Sample 1
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