Fairness based resource allocation strategy towards heterogeneous QoS requirement
Jing Cao, Xigang Zhang · 2021 IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS) · 2021
Dynamic spectrum allocation is a promising solution to alleviate the severe spectrum scarcity recently, meanwhile the fairness of resource allocation between different SUs with heterogeneous Quality of Service (QoS) demands is an existed problem. In this paper, we propose a fairness based resource allocation strategy to guarantee the transmission of different SUs in cognitive radio networks (CRNs). First, we formulate the resource allocation problem as a constrained optimization problem with the objection of maximizing the sum capacity of all SUs. Second, we transform the optimization problem into two sub-problems, and find a suboptimal alternative to decrease the complexity. Third, we design a fairness index based strategy to transform the problem into equivalent optimization problems by adjusting the fairness degree through penalty functions. Simulations and analysis show that, the proposed strategy can guarantee the allocation rationality between different SUs at the premise of satisfying the required transmit rate of users.