Energy aware network planning for wireless cellular system with renewable energy

Powering wireless cellular system by green renewable energy cuts greenhouse gas emissions and electricity bill. However, green energy sources have the limitation of unsustainable availability and capacity. Therefore, the criteria of optimizing network planning for such system should involve both static and dynamic aspects. In this paper, the network planning scheme aims to jointly maximize cell coverage and energy sustainability, which indicate static and dynamic system performance respectively. Firstly, the energy buffer describing green energy evolution is modeled as a G/G/1 queue to investigate energy sustainability. Based on this model, the closed-form expression of service outage probability, which characterizes energy sustainability, is given. Secondly, effective coverage is introduced as a comprehensive parameter which balances cell coverage and energy sustainability. The network planning problem turns to be an effective coverage maximizing problem and solved by automatic cell management. Finally, simulation results are illustrated to validate the proposed automatic cell management.

[1]  Qing Wu,et al.  Harvesting-Aware Power Management for Real-Time Systems With Renewable Energy , 2012, IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

[2]  C. Singh,et al.  Multicriteria Design of Hybrid Power Generation Systems Based on a Modified Particle Swarm Optimization Algorithm , 2009, IEEE Transactions on Energy Conversion.

[3]  Andrzej Duda Transient diffusion approximation for some queuening systems. , 1983, SIGMETRICS '83.

[4]  Hisashi Kobayashi Application of the diffusion approximation to queuing networks: Part I Equilibrium queue distributions , 1973, SIGME '73.

[5]  Andrea J. Goldsmith,et al.  Degrees of freedom in adaptive modulation: a unified view , 2001, IEEE Trans. Commun..

[6]  M. Muselli,et al.  Stochastic study of hourly total solar radiation in Corsica using a Markov model , 2000 .

[7]  Pravin Varaiya,et al.  Capacity of fading channels with channel side information , 1997, IEEE Trans. Inf. Theory.

[8]  Hisashi Kobayashi,et al.  Application of the Diffusion Approximation to Queueing Networks II: Nonequilibrium Distributions and Applications to Computer Modeling , 1974, JACM.

[9]  G. Fettweis,et al.  ICT ENERGY CONSUMPTION – TRENDS AND CHALLENGES , 2008 .

[10]  Nirwan Ansari,et al.  ICE: Intelligent Cell BrEathing to Optimize the Utilization of Green Energy , 2012, IEEE Communications Letters.

[11]  Xin-She Yang,et al.  Introduction to Algorithms , 2021, Nature-Inspired Optimization Algorithms.

[12]  Biljana Badic,et al.  Energy Efficient Radio Access Architectures for Green Radio: Large versus Small Cell Size Deployment , 2009, 2009 IEEE 70th Vehicular Technology Conference Fall.

[13]  Hisashi Kobayashi,et al.  Application of the Diffusion Approximation to Queueing Networks I: Equilibrium Queue Distributions , 1974, JACM.

[14]  Erol Gelenbe,et al.  On Approximate Computer System Models , 1975, JACM.

[15]  Zhisheng Niu,et al.  Cell zooming for cost-efficient green cellular networks , 2010, IEEE Communications Magazine.