Environment-aware localization of femtocells for interference management

Femtocells are a promising approach to provide high data rates through autonomous configuration in indoor environments. However, due to the random and uncontrolled deployment of femtocells within users premises, interference between femtocells themselves and with macrocell base stations is a major issue. In this work, we look into the interference management problem and work towards the development of an interference mitigation algorithm based on the localization of randomly positioned femtocells using radio environmental information. In particular, we show that based on building floorplans and basic information on the urban landscape, femtocells can accurately localize themselves using macrocellular base stations as anchor nodes. Based on the localized femtocell positions, various channel allocation schemes are employed to mitigate interference.

[1]  M. Salazar-Palma,et al.  A survey of various propagation models for mobile communication , 2003 .

[2]  Tokio Taga,et al.  Outdoor-to-indoor propagation modelling with the identification of path passing through wall openings , 2002, The 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications.

[3]  Masayuki Murata,et al.  Autonomous localization method in wireless sensor networks , 2005, Third IEEE International Conference on Pervasive Computing and Communications Workshops.

[4]  Lan truyền,et al.  Wireless Communications Principles and Practice , 2015 .

[5]  C. D. Gelatt,et al.  Optimization by Simulated Annealing , 1983, Science.

[6]  Berna Sayraç,et al.  Design of layered radio environment maps for RAN optimization in heterogeneous LTE systems , 2011, 2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications.

[7]  Laurent Toutain,et al.  Experiments on the RSSI as a Range Estimator for Indoor Localization , 2012, 2012 5th International Conference on New Technologies, Mobility and Security (NTMS).

[8]  Jeffrey G. Andrews,et al.  Spectrum allocation in tiered cellular networks , 2009, IEEE Transactions on Communications.

[9]  Zygmunt J. Haas,et al.  On optimal design of multitier wireless cellular systems , 1997 .

[10]  Holger Claussen,et al.  An overview of the femtocell concept , 2008, Bell Labs Technical Journal.

[11]  Theodore S. Rappaport,et al.  Wireless communications - principles and practice , 1996 .

[12]  Jeffrey G. Andrews,et al.  Power control in two-tier femtocell networks , 2008, IEEE Transactions on Wireless Communications.

[13]  T. Schwengler,et al.  Propagation models at 5.8 GHz-path loss and building penetration , 2000, RAWCON 2000. 2000 IEEE Radio and Wireless Conference (Cat. No.00EX404).

[14]  Dong In Kim,et al.  Interference management in OFDMA femtocell networks: issues and approaches , 2012, IEEE Wireless Communications.

[15]  Jad Nasreddine,et al.  On The Computation of the Maximum Capacity of TDMA-CDMA/TDD Systems , 2006, 2006 IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications.

[16]  J. Shapira Microcell engineering in CDMA cellular networks , 1994 .

[17]  Sverrir Olafsson,et al.  Observations on Using Simulated Annealing for Dynamic Channel Allocation in 802.11 WLANs , 2008, VTC Spring 2008 - IEEE Vehicular Technology Conference.

[18]  Daniel Brélaz,et al.  New methods to color the vertices of a graph , 1979, CACM.

[19]  Holger Claussen,et al.  Performance of Macro- and Co-Channel Femtocells in a Hierarchical Cell Structure , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[20]  V. Cerný Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm , 1985 .

[21]  Masayuki Murata,et al.  Indoor Localization System using RSSI Measurement of Wireless Sensor Network based on ZigBee Standard , 2006, Wireless and Optical Communications.