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Abstract
Deploying in-building distributed antenna systems (IB-DAS) is a crucial step towards providing ubiquitous wireless services. In this paper, we study the multiobjective network planning problem, aiming to minimize both construction costs and average power loss. The main challenge in solving this problem is efficiently representing the network structure. To address this, we encode the network structure as a spanning tree, with the root node connecting to the signal source, and leaf and non-leaf nodes representing all floors and power devices, respectively. Compared to existing encodings, this tree encoding offers several advantages, including improved locality and the ability to easily generate valid solutions. Additionally, we propose a tree-encoded evolutionary algorithm called TMOEA. Since the standard operators cannot be applied, we devise problem-specific crossover and mutation operators to produce tree-encoded solutions. Moreover, the Tchebycheff approach is employed to update solutions. Comprehensive experiments on 11 test instances with up to 30 floors demonstrate that the proposed algorithm outperforms four compared algorithms in terms of both the hypervolume indicator and the inverted generational distance indicator for each test instance. © 2013 IEEE.
Original language | English |
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Article number | 10413627 |
Pages (from-to) | 3002-3014 |
Journal | IEEE Transactions on Network Science and Engineering |
Volume | 11 |
Issue number | 3 |
Online published | 24 Jan 2024 |
DOIs | |
Publication status | Published - May 2024 |
Funding
This work was supported in part by the Innovation and Technology Fund of Hong Kong under Grant GHP/110/20GD, in part by the General Research Fund CityU under Grant 11215622 from the Research Grants Council of Hong Kong, and in part by the National Natural Science Foundation of China under Grant 62276223.
Research Keywords
- In-building distributed antenna system (IB-DAS)
- network planning
- multiobjective optimization
- evolutionary algorithm
- encoding
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GRF: Few for Many: A Non-Pareto Approach for Many Objective Optimization
ZHANG, Q. (Principal Investigator / Project Coordinator)
1/01/23 → …
Project: Research
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ITF: Investigation on Indoor Distributed System Planning Modeling and Fast Algorithm for 5G Mobile Communication Network
ZHANG, Q. (Principal Investigator / Project Coordinator) & SONG, L. (Co-Investigator)
1/09/22 → 28/02/25
Project: Research