Decoupled Uplink-Downlink Association in Full-Duplex Cellular Networks: A Contract-Theory Approach


The relationship between users is an essential component that has a significant impact on the efficiency of wireless networks. In this study, we investigate the user association problem in full-duplex cellular networks, which are characterized by densely distributed base stations (BSs) that have highly variable transmit powers and topologies. Specifically, we focus on how this issue affects networks that operate in full-duplex mode (e.g., heterogeneous networks). Decoupled uplink-downlink association (DUDe) is being considered as a means of improving system performance. This association makes it possible for user equipment (UE) to associate with different base stations (BSs) in the uplink (UL) and downlink (DL), respectively. We propose a contract-theory based distributed user association approach in light of the challenges posed by asymmetric information (such as channel gains and intercell interferences) between UEs and BSs. These challenges have been brought about by the presence of certain types of information. To be more specific, the association process is modeled after a labor market. In this scenario, the BSs take on the role of employers and present employees (also known as UEs) with two-dimensional contracts in an effort to maximize the utility of the BS. The provision of sufficient and necessary conditions constitutes the presentation of theoretical proof that the contract is feasible. In order to achieve optimality, a contract-theoretic decoupled user association algorithm has been developed. In this algorithm, a base station (BS) broadcasts the drafted contracts, and each user equipment (UE) chooses for itself the contract that best meets its needs by taking into account its own requirements. The performance of the proposed method in terms of node utilities and social surplus is demonstrated through the presentation of numerical results. We are also looking into the effects that the system settings have on the performance of the network.

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