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Multi-objective network planning optimization algorithm: human exposure, power consumption, cost, and capacity

Ning Liu (UGent) , David Plets (UGent) , Sotirios K. Goudos, Luc Martens (UGent) and Wout Joseph (UGent)
(2015) WIRELESS NETWORKS. 21(3). p.841-857
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Abstract
Due to the huge popularity of wireless networks, future designs will not only consider the provided capacity, but also the induced exposure, the corresponding power consumption, and the economic cost. As these requirements are contradictory, it is not straightforward to design optimal wireless networks. Those contradicting demands have to satisfy certain requirements in practice. In this paper, a combination of two algorithms, a genetic algorithm and a quasi-particle swarm optimization, is developed, yielding a novel hybrid algorithm that generates further optimizations of indoor wireless network planning solutions, which is named hybrid indoor genetic optimization algorithm. The algorithm is compared with a heuristic network planner and composite differential evolution algorithm for three scenarios and two different environments. Results show that our hybrid-algorithm is effective for optimization of wireless networks which satisfy four demands: maximum coverage for a user-defined capacity, minimum power consumption, minimal cost, and minimal human exposure.
Keywords
INDOOR WIRELESS NETWORKS, GENERAL PUBLIC EXPOSURE, DIFFERENTIAL EVOLUTION ALGORITHM, PATH-LOSS PREDICTION, ENVIRONMENTAL-IMPACT, STRATEGY ADAPTATION, BASE STATIONS, DESIGN, LTE, Indoor wireless network planning, Optimization algorithm, WiFi (IEEE 802.11n), Coverage, Power consumption, Exposure

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Chicago
Liu, Ning, David Plets, Sotirios K. Goudos, Luc Martens, and Wout Joseph. 2015. “Multi-objective Network Planning Optimization Algorithm: Human Exposure, Power Consumption, Cost, and Capacity.” Wireless Networks 21 (3): 841–857.
APA
Liu, N., Plets, D., Goudos, S. K., Martens, L., & Joseph, W. (2015). Multi-objective network planning optimization algorithm: human exposure, power consumption, cost, and capacity. WIRELESS NETWORKS, 21(3), 841–857.
Vancouver
1.
Liu N, Plets D, Goudos SK, Martens L, Joseph W. Multi-objective network planning optimization algorithm: human exposure, power consumption, cost, and capacity. WIRELESS NETWORKS. 2015;21(3):841–57.
MLA
Liu, Ning et al. “Multi-objective Network Planning Optimization Algorithm: Human Exposure, Power Consumption, Cost, and Capacity.” WIRELESS NETWORKS 21.3 (2015): 841–857. Print.
@article{6972197,
  abstract     = {Due to the huge popularity of wireless networks, future designs will not only consider the provided capacity, but also the induced exposure, the corresponding power consumption, and the economic cost. As these requirements are contradictory, it is not straightforward to design optimal wireless networks. Those contradicting demands have to satisfy certain requirements in practice. In this paper, a combination of two algorithms, a genetic algorithm and a quasi-particle swarm optimization, is developed, yielding a novel hybrid algorithm that generates further optimizations of indoor wireless network planning solutions, which is named hybrid indoor genetic optimization algorithm. The algorithm is compared with a heuristic network planner and composite differential evolution algorithm for three scenarios and two different environments. Results show that our hybrid-algorithm is effective for optimization of wireless networks which satisfy four demands: maximum coverage for a user-defined capacity, minimum power consumption, minimal cost, and minimal human exposure.},
  author       = {Liu, Ning and Plets, David and Goudos, Sotirios K. and Martens, Luc and Joseph, Wout},
  issn         = {1022-0038},
  journal      = {WIRELESS NETWORKS},
  keywords     = {INDOOR WIRELESS NETWORKS,GENERAL PUBLIC EXPOSURE,DIFFERENTIAL EVOLUTION ALGORITHM,PATH-LOSS PREDICTION,ENVIRONMENTAL-IMPACT,STRATEGY ADAPTATION,BASE STATIONS,DESIGN,LTE,Indoor wireless network planning,Optimization algorithm,WiFi (IEEE 802.11n),Coverage,Power consumption,Exposure},
  language     = {eng},
  number       = {3},
  pages        = {841--857},
  title        = {Multi-objective network planning optimization algorithm: human exposure, power consumption, cost, and capacity},
  url          = {http://dx.doi.org/10.1007/s11276-014-0822-y},
  volume       = {21},
  year         = {2015},
}

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