References
- F. Mhiri, K. Sethom, and R. Bouallegue, A survey on interference management techniques in femtocell self-organizing networks, J. Netw. Comput. Applicat. 36 (2013), no. 1, 58-65. https://doi.org/10.1016/j.jnca.2012.04.021
- H. Marshoud et al., Genetic algorithm based resource allocation and interference mitigation for OFDMA macrocell-femtocells networks, Wireless Mobile Netw. Conf. (WMNC), Dubai, United Arab Emirates, Apr. 23-25, 2013, pp. 1-7.
- V. Chandrasekhar and J. G. Andrews, Femtocell networks: A survey, IEEE Commun. Mag. 46 (2008), no. 9, 59-67. https://doi.org/10.1109/MCOM.2008.4623708
- D. Y. Yuan et al., Stackelberg game for backhaul resource allocation in the two-tier LTE femtocell networks, J. China Univ. Posts Telecommun. 21 (2014), no. 2, 32-39.
- M. Feng, S. Mao, and T. Jiang, Joint duplex mode selection, channel allocation, and power control for full-duplex cognitive femtocell networks, Digit. Commun. Netw. 1 (2015), no. 1, 30-44. https://doi.org/10.1016/j.dcan.2015.01.002
- I. W. Mustika et al., Potential game approach for self-organization scheme in open access heterogeneous networks, Int. ICST Conf. Cogn. Radio Oriented Wireless Netw. Commun. (CROWNCOM), Osaka, Japan, June 1-3, 2011, pp. 216-220.
- O. Mehanna, Sharing vs. splitting spectrum in OFDMA femtocell networks, IEEE Int. Conf. Acoustics, Speech Signal Proc., Vancouver, Canada, May 26-31, 2013, pp. 4824-4828.
- X. Kang, Y. C. Liang, and H. K. Garg, Distributed power control for spectrum-sharing femtocell networks using Stackelberg game, IEEE Int. Conf. Commun., Kyoto, Japan, June 5-9, 2011, pp. 1-5.
- H. Marshoud et al., Realistic framework for resource allocation in macro-femtocell networks based on genetic algorithm, Telecommun. Syst. 63 (2016), no. 1, pp. 99-110. https://doi.org/10.1007/s11235-015-9976-x
- S. Padmapriya and M. Tamilarasi, A case study on femtocell access modes, Eng. Sci. Technol. Int. J. 19 (2016), no. 3, 1534-1542. https://doi.org/10.1016/j.jestch.2016.05.007
- B. G. Choi et al., A femtocell power control scheme to mitigate interference using listening TDD frame, Int. Conf. Inform. Netw., Barcelona, Spain, Jan. 26-28, 2011, pp. 241-244.
- H.-S. Jo et al., Interference mitigation using uplink power control for two-tier femtocell networks, IEEE Trans. Wireless Commun. 8 (2009), no. 10, 4906-4910. https://doi.org/10.1109/TWC.2009.080457
- T. Zahir et al., A downlink power control scheme for interference avoidance in femtocells, Int. Wireless Commun. Mob. Comput. Conf., Istanbul, Turkey, July 4-8, 2011, pp. 1222-1226.
- W. Yalong et al., Resource allocation scheme based on game theory in heterogeneous networks, J. China Univ. Posts Telecommun. 23 (2016), no. 3, 57-88. https://doi.org/10.1016/S1005-8885(16)60033-X
- N. Fath et al., Optimal resource allocation scheme in femtocell networks based on Bat algorithm, Asia-Pacific Conf. Commun., Yogyakarta, Indonesia, Aug. 25-27, 2016, pp. 281-285.
- D. Liu et al., The sub-channel allocation algorithm in femtocell networks based on ant colony optimization, Militay Commun. Conf., Orlando, FL, USA, Oct. 29-Nov. 1, 2012, pp. 1-6.
- H. Marshoud et al., Resource allocation in macrocell-femtocell network using genetic algorithm, IEEE Int. Conf. Wireless Mobile Comput., Netw. Commun. (WiMob), Barcelona, Spain, Oct. 8-10, 2012, pp. 474-479.
- R. Estrada, H. Otrok, and Z. Dziong, Resource allocation model based on particle swarm optimization for OFDMA macro-femtocell networks, IEEE Int. Conf. Adv. Netw. Telecommun. Syst., Kattankulathur, India, Dec. 15-18, 2013, pp. 1-6.
- X. Chen, L. Li, and X. Xiang, Ant colony learning method for joint MCS and resource block allocation in LTE femtocell downlink for multimedia applications with QoS guarantees, Multimed. Tools Applicat. 76 (2017), no. 3, 4035-4054. https://doi.org/10.1007/s11042-015-2991-9
- V. Sharma, A review of bacterial foraging optimization and its applications, National Conf. Futur. Asp. Artif. Intell. Ind. Autom. 1 (2012), 9-12.
- H. E. A. Ibrahim, F. N. Hassan, and A. O. Shomer, Optimal PID control of a brushless DC motor using PSO and BF techniques, Ain Shams Eng. J. 5 (2014), no. 2, 391-398.
- A. Rajni and I. Chana, Bacterial foraging based hyper-heuristic for resource scheduling in grid computing, Futur. Gener. Comput. Syst. 29 (2013), no. 3, 751-762. https://doi.org/10.1016/j.future.2012.09.005
- B. Bhushan and M. Singh, Adaptive control of DC motor using bacterial foraging algorithm, Applicat. Soft Comput. J. 11 (2011), no. 8, 4913-4920. https://doi.org/10.1016/j.asoc.2011.06.008
- O. P. Verma et al., A novel bacterial foraging technique for edge detection, Pattern Recogn. Lett. 32 (2011), no. 8, 1187-1196. https://doi.org/10.1016/j.patrec.2011.03.008
- B. Hernandez-Ocana, E. Mezura-Montes, and P. Pozos-Parra, A review of the bacterial foraging algorithm in constrained numerical optimization, IEEE Congress Evolutionary Comput., Cancun, Mexico, June 20-23, 2013, pp. 2695-2702.
- 3GPP TS 36.211, Physical channels and modulation, Technical Specification, 2014, pp. 1-121.
- S. S. Patnaik and A. K. Panda, Optimizing current harmonics compensation in three-phase power systems with an enhanced bacterial foraging approach, Int. J. Electr. Power Energy Syst. 61 (2014), 386-398. https://doi.org/10.1016/j.ijepes.2014.03.051
- Y.-W. Chen, C.-L. Lin, and A. Mimori, Multimodal medical image registration using particle swarm optimization, Int. Conf. Intell. Syst. Des. Applicat., Kaohsiung, Taiwan, Nov. 26-28, 2008, pp. 127-131.
- S. Sharma and H. M. Pandey, Genetic algorithm, particle swarm optimization and harmony search: A quick comparison, Int. Conf. - Cloud Syst. Big Data Eng. (Confluence), Noida, India, Jan. 14-15, 2016, pp. 40-44.