Radio Resource Management with Proportional Rate Constraint in the Heterogeneous Networks

An Improved User Association Algorithm for MAP–FAPs Heterogeneous Networks

“…Different from [13], this paper restricts the number of maximum service users for each FAP. Note that the maximum service user number is small compared to the total user number, so to reduce the computational complexity, we only select the last K F i = min(λ max , K F i ) users as our final choice.…”

“…Unfortunately, the optimization problem involving AP selection is difficult to solve [13]. To make the problem tractable, restriction is relaxed.…”

“…Besides, players (users or APs) in HetNets may not be rational all the time, because multi-parameter optimization is considered in HetNets, and the one maximizing its sum-throughput may be perceived as non-rational by the other ensuring fairness, and vice versa [1]. References [13][14][15][16][17][18] solve the RRM problem using convex optimization. By formulating a system model and simplifying some conditions, the optimal problem will transfer into a convex optimization problem.…”

“…Reference [13] focuses on RRM under proportional user rate constraints in LTE-WLAN HetNets, and Karush-Kuhn-Tucker (KKT) conditions are used to obtain the optimal solution. However, the assumptions of multi-homing and resource element sharing are unreasonable; what is more, the average rate ratio-based user association algorithm in [13] uses an exhaustive search to obtain the optimal solution, which is too complicated to implement. References [19,20] use pricing-based user association for the HetNets.…”

“…So, it is necessary to consider this constraint when associating users with FAP. According to the lack of RRM in HetNets, this paper proposes a new user association algorithm in HetNets to maximize system sum-throughput under the constraints of user rate proportion and maximum service user number; meanwhile, the proposed algorithm has a lower complexity than [13].…”