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In the next few years, small cells (SCs) are about to be densely deployed to achieve sustainable capacity enhancement. Due to the expected high SC density, some SCs will not have a direct connection to the core network, and thus will forward their traffic to the neighboring SCs through a multi-hop backhaul (BH). In such multi-hop architectures, the user association problem becomes challenging with BH energy consumption playing a key role. On the other hand, the ever-increasing need to minimize the user equipment (UE) transmission power along with the uplink (UL) and downlink (DL) traffic asymmetry, predicate the joint study of UL and DL. Thus, in this paper, we study the joint UL and DL cell selection problem aiming at maximizing the total network energy efficiency, without compromising the UE quality of service. The problem is formulated as an optimization problem, which is NP-hard. Therefore, we propose a heuristic algorithm that exploits context-aware information to associate the UEs in an energy-efficient way, while considering both access and BH energy consumption in UL and DL. We evaluate the performance of the proposed algorithm and we show that it can achieve significantly higher energy efficiency than the reference algorithms, while maintaining high spectral efficiency and low UE power consumption.
CitationMesodiakaki, A. [et al.]. Joint uplink and downlink cell selection in cognitive small cell heterogeneous networks. A: IEEE Global Communications Conference. "Proceedings GLOBECOM 2014". Austin, TX: 2014, p. 2643-2648.
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