Affiliations: [a] Department of ECE, Hindustan Institute of Technology and Science, Chennai, Tamilnadu, India
| [b] School of Computing, University of Eastern Finland, Kuopio, Finland
Correspondence:
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Corresponding author. K. Sakthidasan @ Sankaran, Department of ECE, Hindustan Institute of Technology and Science, Chennai, Tamilnadu, India. Tel.: +91 8056490436; E-mail: sakthidasan.sankaran@gmail.com.
Abstract: Nowadays, numerous algorithms on power allocation have been proposed for maximizing the EE (Energy efficiency) and SE (Spectral efficiency) in the Distributed Antenna System (DAS). Moreover, the conservative techniques employed for power allocation seem to be problematic, due to their high computational complexity. The main objective of this paper focuses on optimizing the power allocation in order to enhance the EE and SE along with the improved antenna capacity using an effective optimization approach with the clustering model. To obtain the optimized power allocation and antenna capacity, Multi-scale resource Grasshopper Optimization Algorithm (Multi-scale resource GOA) scheme is proposed and employed. Furthermore, clustering is developed based on the Discriminative cluster-based Expectation maximization (DC-EM) clustering algorithms, which also helps to reduce the interference rate and computational complexity. The performance analysis is made under various scenarios and circumstances. The proposed system (DAS with GOA-EM) is assessed and compared with the existing approaches in terms of both the EE and SE, which demonstrates that its superiority.
Keywords: Distributed Antenna system, power allocation, energy efficiency, spectral efficiency, optimization algorithms
