Coverage Optimization for Dense Deployment Small Cell Based on Ant Colony Algorithm

Dense deployment of small cell in heterogeneous networks (HetNet) is considered as a promising way to cope with the exponential growth in mobile traffic demand. In such scenario, coverage optimization is a challenge due to the unplanned deployment and plug-and-play feature of small cell. In this paper, the coverage performance of the network is analyzed under different deployment density of small cells. Then the coverage problem is modeled as a cost function which includes the inappropriate coverage ratio of the network. After that, the ant colony algorithm (ACA) is applied to find the optimal pilot Tx power of each small cell through the minimization of the cost function. Finally, compared to the fixed coverage scheme, the proposed algorithm can not only reduce the ratio of coverage hole but also the proportion of coverage overlap as well.

[1]  Manuel López-Ibáñez,et al.  Ant colony optimization , 2010, GECCO '10.

[2]  Geng Wu,et al.  Capacity and coverage enhancement in heterogeneous networks , 2011, IEEE Wireless Communications.

[3]  Gautam Garai,et al.  An efficient Ant Colony Optimization algorithm for function optimization , 2013, 2013 IEEE Congress on Evolutionary Computation.

[4]  Jeffrey G. Andrews,et al.  Heterogeneous cellular networks: From theory to practice , 2012, IEEE Communications Magazine.

[5]  Bongyong Song,et al.  A holistic view on hyper-dense heterogeneous and small cell networks , 2013, IEEE Communications Magazine.

[6]  Thomas Stützle,et al.  A short convergence proof for a class of ant colony optimization algorithms , 2002, IEEE Trans. Evol. Comput..

[7]  Holger Claussen,et al.  Distributed Radio Coverage Optimization in Enterprise Femtocell Networks , 2010, 2010 IEEE International Conference on Communications.

[8]  Hui Liu,et al.  Mobility Robustness Optimization in Femtocell Networks Based on Ant Colony Algorithm , 2012, IEICE Trans. Commun..

[9]  Holger Claussen,et al.  Evolving femtocell coverage optimization algorithms using genetic programming , 2009, 2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications.

[10]  Yiqing Zhou,et al.  Distributed coverage optimization for small cell clusters using game theory , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).

[11]  Yongbin Wei,et al.  A survey on 3GPP heterogeneous networks , 2011, IEEE Wireless Communications.

[12]  Yinlong Liu,et al.  Optimization of Coverage for OFDMA Femtocell Networks Based on MADM , 2012, 2012 8th International Conference on Wireless Communications, Networking and Mobile Computing.

[13]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

[14]  Hongcheng Zhuang,et al.  A hybrid framework for capacity and coverage optimization in self-organizing LTE networks , 2013, 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[15]  Imed Bouazizi,et al.  ARA-the ant-colony based routing algorithm for MANETs , 2002, Proceedings. International Conference on Parallel Processing Workshop.