ENVIRONMENT-AWARE INTERFERENCE MANAGEMENT IN FEMTOCELLS

Avishek PatraInstitute for Networked Systems, RWTH Aachen University

CONTENTS

1. MOTIVATION 2. INTERFERENCE PROBLEM IN FEMTOCELLS3. INTERFERENCE MANAGEMENT4. LOCALIZATION ALGORITHM

1. ENVIRONMENTAL MODELING & WINPROP2. PROPAGATION MODELING3. ALGORITHM DESCRIPTION & RESULTS

5. CHANNEL ALLOCATION SCHEMES1. ALGORITHM DESCRIPTION2. ALGORITHM RESULTS

6. CONCLUSION

MOTIVATION

● Shift from voice-only to voice- & data-based traffic

● Improved technologies – smart antennas, cell size reduction

● Deadzone Problem – Poor indoor coverage and inability to

match required capacity

● Solution – Femtocells – Small range, low power BSs with

better indoor coverage and higher capacity

● Outdoor Macro-Network + Indoor Femto-Network =

Heterogeneous Networks

INTERFERENCE PROBLEM IN FEMTOCELLS

● Co-channel Interference● Uncertainty of Placement due to User-Deployment● Degradation to and from other Femtocell and Macrocell

Basestations

INTERFERENCE SCENARIOS

1. Macrocell UE Femtocell BS2. Macrocell BS Femtocell UE3. Femtocell UE Macrocell BS4. Femtocell BS Macrocell UE5. Femtocell ‘A’ UE Femtocell ‘B’ BS6. Femtocell ‘A’ BS Femtocell ‘B’ UE

Cross-Tier

Co-Tier

INTERFERENCE PROBLEM IN FEMTOCELLS [CONTD.]

Fig. 1. Femtocell – MacrocellInterference Scenarios

INTERFERENCE MANAGEMENT

SOLUTIONS IN LITERATURE

1. Decentralized Spectrum Allocation [1]

2. Transmit Power Control [2]

3. Frequency Hopping [3]

4. Directional Antennas [4]

5. Hybrid Channel Allocation [5]

[1] V. Chandrasekhar and J.G. Andrews, "Spectrum Allocation in Two-Tier Networks", IEEE Asilomar, Oct. 2008.[2] H. Claussen, "Performance of Macro- and Co-Channel Femtocells in a Hierarchical Cell Structure,“ PIMRC 2007.

IEEE 18th International Symposium, Sep. 2007[3] V. Chandrasekhar, J. Andrews, and A. Gatherer, "Femtocell networks: A Survey," IEEE Commun. Mag., vol. 46,

no. 9, pp. 59-67, Sep. 2008.[4] T. H. Kim, T. Salonidis, and H. Lundgren, "MIMO wireless networks with directional antennas in indoor

environments," INFOCOM, 2012 Proceedings IEEE , vol., no., pp.2941,2945, 25-30 March 2012.[5] Yong Ding, and Li Xiao, “Channel Allocation In Multi-channel Wireless Mesh Networks”, Computer

Communications, Volume 34, Issue 7, 16 May 2011, Pages 803-815.

INTERFERENCE MANAGEMENT [CONTD.]

PROPOSED SOLUTION

Environment-aware Interference Management in Femtocells

SALIENT FEATURES

1. Localization :1. Indoor localization using environmental information2. Dependent on signal penetration loss through walls

2. Interference Management :1. Dynamic channel allocation2. Allocation using heuristic methods

1. LOCALIZATION ALGORITHM

PROPOSED METHOD

● Localize Femtocell within a Room in an Urban Environment through triangulation

● Based on RSSI (Received Signal Strength Indicator)

● Effect of different penetration losses through walls of different materials

● Fixed Macrocell Base Stations as Anchors Fig. 2. Femtocell Localization by

Triangulation

ENVIRONMENT MODELING AND WINPROP

● Received Signal degrades due to:○ Path Loss in Urban Environment○ Penetration Loss in Indoor Environment (Walls of

Building containing the Femtocell)● Environmental Modeling using WinProp Suite [6]

● Urban Model : 1. Height of Buildings2. Position of Buildings

● Indoor Model : 3. Individual Wall Losses4. Positions of Walls

[6] AWE Communication http://www.awe-communications.com

ENVIRONMENT MODELING AND WINPROP [CONTD.]

Fig. 3(a). Indoor Environment Model

ENVIRONMENT MODELING AND WINPROP [CONTD.]

Fig. 3(b). Signal propagation through Indoor

Environment Model

ENVIRONMENT MODELING AND WINPROP [CONTD.]

Fig. 3(c). Urban Environment Model

ENVIRONMENT MODELING AND WINPROP [CONTD.]

Fig. 3(d). Signal propagation through Urban Environment

Model

PROPAGATION MODELING

● Propagation Models to generate indoor Received Power

URBAN PROPAGATION MODEL

1. Parametric Model (COST 231 Walfisch Ikegami Model)2. Empirical Model (Empirical Data from WinProp Suite)

INDOOR PROPAGATION MODEL

● Based on material-dependent Wall Losses● Received Power, P_Rx at any point inside Building:

(in dB)

ALGORITHM DESCRIPTION

Flowchart: DatabaseGeneration

ALGORITHM DESCRIPTION [CONTD.]

ALGORITHM DESCRIPTION [CONTD.]

LOCALIZATION ALGORITHM

● RSSI Database Generation w.r.t. all anchor MBSs● Localization by referring to generated RSSI Databases● Location by Maximum Likelihood Estimation

Fig. 4. Maximum Likelihood Estimation – 3D Plot

ALGORITHM RESULT

LOCALIZATION RESULTS

● Pr(Room Correctness) = 0.88(95% Shadow CI)● Pr(Position Correctness) = 0.30(95% Shadow CI)● Average Distance Error = 1.36 m

OBSERVATIONS

● Variation due to different propagation model for generating RSSI Databases

● Variation in results due to different MBS Deployment Scenario

ALGORITHM RESULT [CONTD.]

Fig. 5(a). Box-Plots of Distance Errors for different Scenarios

6-MBS WI-based

Curve-Fitting

6-MBS COST 231 WI Model

8-MBS WI-based

Curve-Fitting

8-MBS COST 231 WI Model

ALGORITHM RESULT [CONTD.]

Fig. 5(b). Histogram of Distance Error for Scenario with 8-MBS at average distance of 400m

2. CHANNEL ALLOCATION SCHEMES

● Interference Management for OFDMA-based Femtocell downlink scenario

ASSUMPTIONS

● Location of Femtocells in Building known● Femtocells share fixed no. of OFDMA sub-channels● Femtocells have fixed transmit power● Users associate with Serving Femtocell Base Station● Co-channel Non-Serving Femtocell signals act as

interference

● Target: Maximise Average Downlink SINR of Users

ALGORITHM DESCRIPTION

1. GRAPH COLORING BASED METHOD (GCM)

● Based on DSATUR Algorithm [7]

● Interference Graph generation● Low available sub-channels to FBS served users ratio● Edge-Weight assignment: (Lower Weighing Edges dropped)

1. Range-based ∝ overlap (FBS i, FBS j)2. Distance based ∝ 1/dist (FBS i, FBS j)3. Walls &distance based ∝ 1/[dist (FBS i, FBS j) x

walls (FBS i, FBS j)][7] D. Brélaz, “New Methods to Color the Vertices of a Graph,” Comm. ACM 22, 251-256, 1979.

ALGORITHM DESCRIPTION [CONTD.]

2. SIMULATED ANNEALING METHOD (SAM)

● Analogous to metal annealing [8]

● Scenario Interference as Objective Function● Temperature decrease depends on Cooling Scheme● Linear Cooling Scheme

T – Temperature, N – Total Iterations

[8] S. Kirkpatrick, C. Gelatt, Jr., M. Vecchi, “Optimization by simulated annealing,” Science, Vol220, No 4598, pp. 671-680, May 1983.

Fig. 6. Cooling Schemes

ALGORITHM RESULTS

● Perfect Localization: (6 Scenarios)○ Average SINR = 30 - 52 dB○ 05%-ile SINR = 18 - 36 dB○ 95%-ile SINR = 42 - 85 dB (max. 112 dB)

● Imperfect Localization: (1 Scenario)○ Average SINR = 18 - 48 dB○ 05%-ile SINR = 02 - 32dB○ 95%-ile SINR = 38 - 110 dB

● Error in SINR = ~ 20 – 26 dB

ALGORITHM RESULTS [CONTD.]

Fig. 8(a). Box-Plots for Channel Allocation Scenario (12-FBS 4-Channels) in a single storiedmulti-room building using GCM and SAM

Range-basedGCM

70

60

50

40

30

20

10

SAM

Scen

ario

SIN

R [i

n dB

]

C B R C B R C B R R

Distance- and Walls Based GCM

Distance-basedGCM

C – Complete RangeB – Range points within BuildingR – Range points within Room

ALGORITHM RESULTS [CONTD.]

Fig. 8(b). Box-Plots for Channel Allocation Scenarios (30-FBS 6-Channels and 30-FBS 8-Channels) in a double storied multi-room building using SAM

30-FBS 6-ChannelsSAM

30-FBS 8-ChannelsSAM

R – Range points within Room

R R

ALGORITHM RESULTS [CONTD.]

OBSERVATIONS

● Scenario SINR α Number of available channels

● Scenario SINR α 1/Number of FBSs

● Scenario SINR varies with different FBS SINR measurement methods

● Difference in average scenario SINR results due to inaccurate localisation

Fig. 7. Allocated Channels for 12-FBS 3-Channel Scenario

● GCM v/s SAM – No clear winner in channel allocation. (GCM faster compared to SAM)

CONCLUSION

● Localization with awareness of surrounding environment

● Localization within room with accuracy up to 88% and minimum average distance error of 1.36m

● Interference management through location-based dynamic channel allocation

● Average SINR (downlink) in range of:○ Perfect Localization: 30 – 52 dB○ Imperfect Localization: 18 – 48 dB

● Easily extendable for co-tier uplink and cross-tier scenarios

● Study using IRT Propagation Model and complex multiple material building

READ THE PDF OF THE COMPLETE MASTER THESIS AT THE LINK BELOW:

COMPLETE MASTER THESIS TEXT

DO NOT COPY OR REPRODUCE IN ANY FORM WITHOUT ASSENT OF THE AUTHOR.

ALL RIGHTS RESERVED TO THE AUTHOR AND RELATED INSTITUTES.

THANK YOU

QUESTIONS?