Decentralized Probabilistic Frequency-Block Activation Control for Inter-Cell Interference Coordination and Traffic Load Balancing

We propose a decentralized probabilistic frequency-block activation control method for the cellular downlink. The aim of the proposed method is to increase the downlink system throughput within the system coverage by adaptively controlling the activation of each multiple frequency block at all base stations (BSs) to achieve inter-cell interference coordination (ICIC) and traffic load balancing effects. The proposed method does not rely on complicated inter-BS cooperation; it uses inter-BS cooperation only to share the temporal system throughput observed at the neighboring BSs. Based on the shared temporal system throughput information, each BS independently performs online activation control for the respective frequency blocks in a probabilistic manner, which autonomously achieves ICIC and load balancing effects among BSs. Computer simulation results, in which the mobility of the user terminals is taken into account, show the effectiveness of the proposed method.

[1]  Ashwin Sampath,et al.  Cell Association and Interference Coordination in Heterogeneous LTE-A Cellular Networks , 2010, IEEE Journal on Selected Areas in Communications.

[2]  Higuchi Kenichi,et al.  On the Range in Inter-Base Station Information Exchange in Online Probabilistic Activation Control of Base Stations Based on Observed System Throughput , 2016 .

[3]  Rui Chang,et al.  Interference coordination and cancellation for 4G networks , 2009, IEEE Communications Magazine.

[4]  Hiroyuki Seki,et al.  Selection of Component Carriers Using Centralized Baseband Pooling for LTE-Advanced Heterogeneous Networks , 2013, IEICE Trans. Commun..

[5]  Yoshihisa Kishiyama,et al.  Frequency Block-Dependent Online Probabilistic Activation Control of Base Stations in Heterogeneous Networks , 2018, 2018 21st International Symposium on Wireless Personal Multimedia Communications (WPMC).

[6]  Tracy Camp,et al.  A survey of mobility models for ad hoc network research , 2002, Wirel. Commun. Mob. Comput..

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

[8]  Yoshihisa Kishiyama,et al.  Adaptive Step Size Control for Update of Activation Probability in Online Probabilistic BS Activation Control Method , 2018, 2018 21st International Symposium on Wireless Personal Multimedia Communications (WPMC).

[9]  Zhisheng Niu,et al.  Energy-optimal probabilistic base station sleeping under a separation network architecture , 2014, 2014 IEEE Global Communications Conference.

[10]  Hyundong Shin,et al.  Energy Efficient Heterogeneous Cellular Networks , 2013, IEEE Journal on Selected Areas in Communications.

[11]  Higuchi Kenichi,et al.  Improved Algorithms for Online Probabilistic Activation Control of Base Stations Based on Observed System Throughput in Heterogeneous Networks , 2016 .

[12]  IMT Vision – Framework and overall objectives of the future development of IMT for 2020 and beyond M Series Mobile , radiodetermination , amateur and related satellite services , 2015 .

[13]  Higuchi Kenichi,et al.  Online probabilistic activation control of picocells for system throughput maximization in heterogeneous networks , 2015, International Symposium on Intelligent Signal Processing and Communication Systems.

[14]  Zhang Chao,et al.  Green Mobile Access Network with Dynamic Base Station Energy Saving , 2009 .

[15]  Frank Kelly,et al.  Charging and rate control for elastic traffic , 1997, Eur. Trans. Telecommun..

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