Decoupled uplink-downlink user association in full-duplex small cell networks
In multi-tier cellular networks, user performance is largely a ected by the varying transmit powers, distances, and non-uniform tra c loads of di erent base stations (BSs) in both the downlink (DL) and uplink (UL) directions of transmission. In presence of such heterogeneity, decoupled UL-DL user association (DUDe), which allows users to associate with di erent BSs for UL and DL transmissions, can be used to optimize network performance. Again, in-band full-duplex (FD) communi- cation is considered as a promising technique to improve the spectral e ciency of future multi-tier fth generation (5G) cellular networks. Nonetheless, due to severe UL-to-DL and DL-to-UL interference issues arising due to FD communications, the performance gains of DUDe in FD multi-tier networks are inconspicuous. To this end, this thesis develops a comprehensive framework to analyze the usefulness of DUDe in a full-duplex multi-tier cellular network. We rst formulate a joint UL and DL user association problem (with the provision of decoupled association) that maximizes the sum-rate for UL and DL transmission of all users. Since the formulated problem is a mixed-integer non-linear programming (MINLP) problem, we invoke approxi- mations and binary constraint relaxations to convert the problem into a Geometric Programming (GP) problem that is solved using Karush-Kuhn-Tucker (KKT) opti- mality conditions. Given the centralized nature and complexity of the GP problem, the solution of which serves as the upper bound for any sub-optimal solution, we formulate a distributed two-sided iterative matching game and develop a solution to obtain the solution of the game. In this game, the users and BSs rank one another using preference metrics that are subject to the externalities (i.e., dynamic interfer- ence conditions). The solution of the game is guaranteed to converge and provides Pareto-e cient stable associations. Finally, we derive e cient light-weight versions of the iterative matching solution, i.e., non-iterative matching and sequential UL-DL matching algorithms. The performances of all the solutions are critically evaluated in terms of aggregate UL and DL rates of all users, the number of unassociated users, and the number of coupled/decoupled associations. Simulation results demonstrate the e cacy of the proposed algorithms over the centralized GP solution as well as traditional coupled and decoupled user association schemes.