Abstract-Performance of heterogeneous network is strongly limited by the interference due to multiple access points operating in the same geographical area, with overlapping service coverage. The common understanding is that interference, classically processed as additive noise, compromises the transmission and therefore must be ideally avoided or at least strongly limited. However, recent investigations in the domain of information theory and successive interference cancellation (SIC) techniques have proved that interference may not necessarily be treated as an opponent, but may become an ally. In this paper, we propose a novel interference aware resource management algorithm, where the system may only control its interference perception. In a system consisting of a couple of downlink users and access points with overlapping coverage, we aim to define the most spectralefficient way to process interference at each receiver. Based on a 3-regimes interference classifier, both users in the system may either treat interference as noise, orthogonalize transmissions so that interference may be avoided, or cancel interference out of the received signal via SIC-based techniques. Our study shows that, when aiming at maximizing total spectral efficiency, ignoring or avoiding interference is not always the best option. Based on our theoritical study, we propose an interference classification algorithm, with only 2 admissible regimes for each user. Finally, we assess its notable performance improvement by simulation results.
Abstract-In this paper, we consider the scenario of a cellular network where base stations aim to transmit several data packets to a set of users in the downlink, within a predefined time, at minimal energy cost. The base stations are non-cooperating and the instantaneous transmission rate depends on the instantaneous SINR at the receiver. The purpose of this article is to highlight a power-efficient transmit policy. By assuming a large number of homogeneous users, we model the problem as a mean field game, with tractable equations, that allow us to bypass the complexity of analyzing a Nash equilibrium in a L-body dynamic game. The framework we propose yields a consistent analysis of the optimal transmit power strategy, that allows every base station to, selfishly but rationally, satisfy its transmission, at a minimal energy cost.
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