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1 NETS2020 Project Task #2.3: Self-organization in Dynamic Networks Olav Tirkkonen, Jyri Hämäläinen 1

2 Content Subtask #2.3.1: Convergence of Distributed Network Algorithms: The project outcome Subtask #2.3.2: 2: Heterogeneous Networks: The project outcome 2

3 Distributed Resource and Power Allocation Studies 1. Fractional power control on per-cell basis presented in afternoon 2. Dynamic joint optimization of scheduling and power allocation to instantaneous user population in small cell network Distributed utility maximization, finding solution of KKT equations Below 3

4 UE-BS pricing link BS-BS pricing link System model Distributed downlink resource allocation algorithm: (1) BSs exchange interference prices on each channel (2) BSs update power and scheduling weights (per carrier), based on reported interference prices and known channel gains 4

5 Simulation results: Small Cell Layout Path loss model: WINNER A1 (2,6 GHz) Location of BSs 4 base stations (Max Power: 20 dbm) 5 component carriers (1,25 MHz each) 2 mobile users per base station 4 closed subscriber groups CSG1 CSG2 CSG3 CSG4 A: Adaptive F: Fixed PA: Power Allocation SCH: Scheduling A: Adaptive F: Fixed PA: Power Allocation SCH: Scheduling Max-Rate Utility Proportional Fair Utility 5

6 Mobile Relaying Self-organized cooperation between User Equipments (UEs) UEs act as mobile relays, helping cell-edge UEs Each active UE may select multiple idle UEs Each idle UE helps at most one active UE Resolve conflicts when multiple sources request for same relay in distributed manner 6

7 System Model First hop broadcast channel Quality restricted by worst relay channel Second hop Multinode transmission Quality characterized by total received power Relay set clustering With multiple sources dynamically select best clustering of relay nodes Conflict resolution needed Sets of desired relays for source nodes Conflicts 7

8 Simulation Results Circular cell, distance-dependent path loss Four sources, 7 relays, Each source may select up to 3 relays Self-organized conflict resolution gives near-optimal performance 8

9 Subtask #2.3.1: Publications C.-H. Yu and O. Tirkkonen, Opportunistic Multiple Relay Selection with Diverse Mean Channel Gains, IEEE T. Wireless Commun, vol. 11, no. 3, p , March C.-H. Yu and O. Tirkkonen, ``Device-to-Device i D i Underlay Cellular l Network Based on Rate Splitting,'' IEEE WCNC, p C.H. Yu, B. Mumey and O. Tirkkonen, "Distributed Multiple Relay Selection by an Auction Mechanism,'' IEEE GLOBECOM, 6 pp., Dec F. Ahmed, A. Dowhuszko, and O. Tirkkonen, ``Distributed Algorithm for Downlink Resource Allocation in Multicarrier Small Cell Networks,'' IEEE ICC, 7 pp., June 2012.

10 U. Oruthota, O. Tirkkonen and P. Dharmawansa, ``Analysis of Uplink Power Control in Cellular Mobile Systems,'' IEEE VTC-- Spring, 5 pp., June J. Yu, O. Tirkkonen and D. Liu, "Distributed t ib t d Greedy Synchronization with Memory in Self-Organized Wireless Network", Journal of Next Generation Information Technology, vol. 2, no. 3, p , Aug O. Tirkkonen, E. Lähetkangas, K. Pajukoski, E. Tiirola, I. Harjula, ``Multihop Relaying for Local Area Access, '' IEEE VTC--Spring Workshops, 5 pp., June S. Hailu, Coordinated Multi-Cell Cooperation for Spectrum Sharing in Co-located Radio Access Networks, M. Sc. Thesis,, C.-H. Yu, Radio Resource Management for Cellular Networks Enhanced by Inter-User Communication, Ph. D. thesis, Aalto University,

11 Subtask #2.3.2: Heterogeneous Networks: The project outcome While starting, a LTE compliant system simulator was build Path loss models, scenarios and radio parameters were adopted from 3GPP recommendations as such. First study: uplink power control parameter optimization in two-tier tier HetNet It was found that power control parameter selections are impacted due to newly added femtocells. Also, the performance of UL scheduling was impacted by the power control parameters. It can be stated that power control parameters will always represent a trade-off that depends on prioritization (between macrocell performance and femtocell performance). 11

12 Subtask #2.3.2: Heterogeneous Networks: The project outcome Second study: Distributed radio resource management in two-tier HetNet The goal was to find scheduling methods that avoid crucial interference especially between macrocell and femtocell layers A new stochastic scheduling method was introduced that can be applied based on rough predefined spectrum allocation rules between femtocells and macrocells. Analytical framework was later build based on analytical approximation of throughput distributions. In addition, HetNet CoMP work was started. The impact of delays on some simple cooperative multipoint transmission were analyzed and simulated. 12

13 Interference Management in LTE-A Het-Nets: Frequency-Domain Stochastic Scheduling Stochastic frequency-domain scheduling algorithm to manage co- channel interference in LTE-Advanced Het-Nets Objective: Allocate spectrum resources dynamically to obtain better performance results in both, femto- and macro-layers, when compared to traditional spectrum allocation approaches (i.e., fullrange and orthogonal alloc.) Approach: Stochastic scheme that relies on low-rate signaling exchange to allocate spectral resources at the FBSs in a distributed way (no central processing required) The stochastic scheduling scheme can be configured (by means of a parameter ω ) to balance smoothly the intra- and co-layer interference in the Het-Net 13

14 System model: Two-Layer System Probability of resource selection X (j) in and X (j) out denote the number of unused resources previous execution of step j Stochastic Spectrum Allocation Low-rate feedback information Indoor MUEs Outdoor MUEs 14

15 Simulation results: Macro- and Femto-Layout Path loss model: link dependent (outdoor/indoor) (macro/femto) Dual-Stripe Building 1 MBS (46 dbm) and 10 MUEs 30 FBS (10 dbm) and 30 FUEs 3 floors Fixed demand of PRBs per user 2 x 5 appart. Orthogonal Allocation Orthogonal Allocation Stochastic Allocation Stochastic Allocation Full-Range Allocation Full-Range Allocation Macro-Layer Femto-Layer 15

16 Subtask #2.3.2: 2: Publications Pradeep Mallya: Effect of Feedback Delay in Cooperative Multipoint i t Communications, MSc Thesis,, Z. Zheng, L. Wei, J. Hämäläinen, O. Tirkkonen: A Blind Time-Reversal Detector in the Presence of Channel Correlation, conditionally accepted to IEEE Signal Processing Letters, Z. Zheng, L. Wei, J. Hämäläinen, O. Tirkkonen: Approximation to Distribution of Product of Random Variables Using Orthogonal Polynomials for Lognormal Density", IEEE Communications Letters, Vol.16, No 12, pp Z. Zheng, L. Wei, J. Hämäläinen: "Novel Approximations to the Statistics of General Cascaded Nakagami-m Channels and Their Applications in Performance Analysis", accepted to IEEE International Conference on Communications - Wireless Communications Symposium ('ICC'13 WCS'),

17 Z. Zheng, A. Dowhuszko, J. Hämäläinen: "Interference management for LTE-Advanced Het-Nets: Stochastic scheduling approach in frequency domain", European Transactions on Telecommunications (ETT), Special Issue on Multi-Carrier Transmission & Applications, LTE & LTE-Advanced, in press (published online 12 September 2012). E. Lähetkangas, K. Pajukoski, E. Tiirola, Z. Zheng, J. Hämäläinen: On the Performance of LTE-Advanced MIMO: How to Set and Reach Beyond 4G Targets, European Wireless conference, January Note: results were created by NSN team, Aalto authors supported the writing. Z. Zheng, J. Hämäläinen, Y. Ying: "On Uplink Power Control Optimization and Distributed Resource Allocation in Femtocell Networks", IEEE Vehicular Technology Conference, Workshop BeFemto, Budabest, Hungary, May Z. Zheng, J. Hämäläinen, Y. Ying: Practical Resource Scheduling and Power Control Optimization for LTE Femtocell Networks, The 8th International Workshop on Multi-Carrier Systems & Solutions (MCSS), Herrsching, Germany, May

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