Abstract
Small cells (SCs) have proven their marvelous capability, especially dealing with high density of user equipment (UE) in the configuration of Internet of Things (IoT). It is widely accepted that the SCs concept is one of the prospective solutions for 5G networks, specifically targeting IoT, to attain the high demand in the future smart city. SC deployment has attracted the attention of multiple research efforts, due to its importance and potential towards enhancing future networking for IoT. However, there is still a lack of works providing SC allocation with comprehensive optimization modeling, which provides essential infrastructural platform to SC functionalities and services (e.g. offloading). The analysis of the number and positions of SCs, towards the simultaneous optimization of both energy efficiency and data rates, is a highly required research direction. SC allocation facilitates the sustainability and reliability, to support exponentially increasing number of users, as well as yielding feasibility of achieving high traffic demand and low latency performance, in addition to longer sustainability based on enhanced energy efficiency. In this paper, a smart small cell allocation scheme is proposed for IoT in smart city. Integer programming multi-objective optimization problem is formulated, and a new algorithm, based on the fusion of Branch-and-Bound (BnB) and Non-Dominated Sorting Genetic Algorithm II (NSGA-II), is developed. Energy efficiency optimization and data rate maximization are formulated, as mutual objectives to fulfill the key demands of IoT in smart city, based on the estimation of users' behaviors. Simulations are conducted, whose results show that the proposed Smart-SC allocation outperforms the different considered benchmarks, resulting in higher offered data rates, while achieving better energy efficiency.
Highlights
Density of user equipment (UE) in modern cities has been dramatically proliferating, owing to the vast adoption of the concept of Internet-of-Things (IoT) [1]
SIMULATION RESULTS AND ANALYSIS To evaluate the proposed scheme, an IoT-network based indoor-outdoor seamless localization for the airport is developed, to track the location of trolleys, which is highly demanded by the global airport to improve the usage efficiency of the trolleys with human power saving
Densification is at the heart of 5th generation communication (5G) paradigm, enabling the provision of services to the foreseen huge number of UEs in the future IoT era
Summary
Density of user equipment (UE) in modern cities has been dramatically proliferating, owing to the vast adoption of the concept of Internet-of-Things (IoT) [1]. The SC allocation is formulated into integer programming with the consideration of optimizing the number and locations of SCs. The UE behavior and SBSs operation estimations are modeled with the jointly optimization objectives, energy efficiency and data rate maximization, to tackle the high-density and low-cost IoT networking development. Derived a network modeling for SC allocation as an integer-programming, non-linear multi-objective optimization problem (IPNLMOO) targeting energy efficiency and data rate maximization, with comprehensive QoS constraints. In this paper, a new SC allocation modelling, with the simultaneous optimization of energy efficiency management and data rate maximization, is proposed. We verify our proposed algorithm through simulations, whose results show that the proposed SC allocation can achieve optimal energy efficiency, with satisfactory data rate to support IoT applications in smart city. UEs can be connected to either SBSs or MBSs, depending on their request and link quality
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