Matching-Based Cell Selection for Proportional Fair Throughput Boosting via Dual-Connectivity

In an increasingly dense and heterogeneous wireless network with various access points, the users are likely to lie in the overlapping coverage areas of multiple radio access technologies, which motivates the boost of user throughput and quality of service via small cell dual-connectivity. In this paper, with the objective of improving network throughput and considering fairness among users, we formulate a small cell selection problem to maximize the network utility reflecting proportional fairness, which is actually the sum of the logarithm of long-term rate of users. However, the formulated problem turns out to be non-convex and combinatorial, and is difficult to be transformed into a convex problem and traditional game-theoretic methods cannot be used. In this context, we introduce a many-to-one matching game with externalities, and develop a distributed algorithm that converges to a stable matching. To further enhance network throughput by mitigating co- channel interference among cellular small cells, a joint cell selection and power control algorithm is developed by adopting an iterative approach to determine them separately and sequentially. Lastly, compared with the nearest distance-based cell selection scheme and the cell selection scheme maximizing the total long-term rate of users, numerical results show the convergence of the matching-based cell selection algorithm and the joint cell selection and power control algorithm, as well as their significant improvement on both total long-term rate of users and user fairness.