Radio Resource Allocation based on Power- Bandwidth Characteristics for Self-optimising Cellular Mobile Radio Networks

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1 Radio Resource Allocation based on Power- Bandwidth Characteristics for Self-optimising Cellular Mobile Radio Networks Philipp P. Hasselbach, Anja Klein Communications Engineering Lab Technische Universität Darmstadt, Germany Ingo Gaspard Deutsche Telekom Laboratories Darmstadt, Germany This work was partly funded by Deutsche Telekom AG and is part of the corporate project SORAN (self-optimizing radio access networks). ITG FG 5.2.4, 30. Treffen, 29. Juni 2009 Philipp P. Hasselbach, Technische Universität Darmstadt, Communications Engineering Lab

2 Motivation Fluctuating resource demand of the cells Rush hour traffic Change in user behaviour Change in environment Dynamic Resource Allocation t = t 1 Self-organizing networks (SONs) Fast, reliable, autonomous algorithms t = t 2 ITG FG 5.2.4, 30. Treffen, 29. Juni 2009 Philipp P. Hasselbach, Technische Universität Darmstadt, Communications Engineering Lab 2

3 Outline System Model Power-Bandwidth Characteristics Resource Allocation Cell Bandwidth Allocation Transmit Power Allocation Simulation Results Comparison ITG FG 5.2.4, 30. Treffen, 29. Juni 2009 Philipp P. Hasselbach, Technische Universität Darmstadt, Communications Engineering Lab 3

4 System Model Inter-cell interference Data signal P I R bit, i, k P tx,i γ i,k P N Reuse distance D Adaptive modulation is used QoS parameter: user bit rate NC cells P tx,i R bit, i, k P I P N γ i,k Transmit power of cell i Required bit rate of user k of cell i Inter-cell interference power Noise power SINR of user k of cell i ITG FG 5.2.4, 30. Treffen, 29. Juni 2009 Philipp P. Hasselbach, Technische Universität Darmstadt, Communications Engineering Lab 4

5 Power-Bandwidth Characteristics User distribution f r, ϕ ( r,ϕ) f r, ϕ ( r,ϕ) K independent users f γ ( γ ) f ( B, P P ) k tx, B k PDF of the bandwidth required by user k I B k = log R 2 bit, k ( 1+ γ ) k Bandwidth required by user k K = B Bandwidth required cell k k= 1 by the whole cell B ITG FG 5.2.4, 30. Treffen, 29. Juni 2009 Philipp P. Hasselbach, Technische Universität Darmstadt, Communications Engineering Lab 5

6 Power-Bandwidth Characteristics User distribution K independent users f r, ϕ ( r,ϕ) f r, ϕ ( r,ϕ) f γ ( γ ) f ( B, P P ) k tx, B k PDF of the bandwidth required by user k I B k = log R 2 bit, k ( 1+ γ ) k Bandwidth required by user k K = B Bandwidth required cell k k= 1 by the whole cell B Central Limit Theorem PDF of the bandwidth required by the cell, P ) Ν( µ 2, σ ITG FG 5.2.4, 30. Treffen, 29. Juni 2009 Philipp P. Hasselbach, Technische Universität Darmstadt, Communications Engineering Lab 6 f B cell ( B cell, P tx F( Bcell, Ptx, PI ) I cell cell )

7 Average Interference, Power Ratio Average interference Power ratio Γ i = P I, i P tx, i + P N P I, i P tx, j = fr, ϕ, a j i, j ( r, ϕ) attenuation user distribution P = G P I tx ( r ϕ) r dϕ dr Power-Bandwidth Characteristic Coupling matrix F( Bcell, Ptx, PI ) F( B cell, Γ) ITG FG 5.2.4, 30. Treffen, 29. Juni 2009 Philipp P. Hasselbach, Technische Universität Darmstadt, Communications Engineering Lab 7

8 Cell Outage Probability CDF of the resources required by the cell: probability that sufficient resources are allocated 1 p cell Prob ( Γ < Γ) = F( B, ) cell Γ 1 p cell Prob cell cell cell 0 ( B < B ) = F ( B, Γ ) Prob ( Γ < Γ ) = F ( B, ) cell,0 Γ B Bandwidth required by the cell cell B cell p cell = 1 F( Bcell, Γ) Power ratio Γ required by the cell Cell outage probability: probability that allocated resources are not sufficient ITG FG 5.2.4, 30. Treffen, 29. Juni 2009 Philipp P. Hasselbach, Technische Universität Darmstadt, Communications Engineering Lab 8 Γ

9 Resource Allocation Power-Bandwidth Characteristics Model a cell w.r.t. to usage of transmit power and cell bandwidth Contain information on user distribution, environment, interference Provide quality indicator for resource assignment by means of cell outage probability Application in resource allocation ITG FG 5.2.4, 30. Treffen, 29. Juni 2009 Philipp P. Hasselbach, Technische Universität Darmstadt, Communications Engineering Lab 9

10 Resource Allocation Power-Bandwidth Characteristics Model a cell w.r.t. to usage of transmit power and cell bandwidth Contain information on user distribution, environment, interference Provide quality indicator for resource assignment by means of cell outage probability Bandwidth allocation min B cell, i s. t. max i 0 B n { i1, K, ir } { i, K, i } 1 { p } cell, i cell, i r B cell, n G B sys B sys B sys : total system bandwidth i = 1KN C cell, i = 1 F( Bcell,, Γ ) ITG FG 5.2.4, 30. Treffen, 29. Juni 2009 Philipp P. Hasselbach, Technische Universität Darmstadt, Communications Engineering Lab 10 p ρ ( X) Power allocation s. t. { p } min max cell, Γ i ρ i ( diag( Γ) G) < 1 : spectral radius of matrix X i i i

11 Simulation Scenarios Three hotspot scenarios Number of users in hotspot cell Number of users in normal cell Wrap around technique No boundary effects N N hs 0 Performance comparison of bandwidth allocation and power allocation Bandwidth allocation: no frequency reuse within frequency reuse distance, fixed transmit power Power allocation: fixed frequency planning, homogeneous bandwidth allocation Single hotspot Multi hotspot Cluster hotspot ITG FG 5.2.4, 30. Treffen, 29. Juni 2009 Philipp P. Hasselbach, Technische Universität Darmstadt, Communications Engineering Lab 11

12 Simulation Parameters Cell radius R User distribution Propagation model Shadow fading variance No frequency reuse within Hotspot reuse factor Total system bandwidth Scheduling Data rate per user 250 m uniform 3GPP SCM Urban Macro 8 db 3 times the cell radius R MHz Fair throughput 100 kbit/s ITG FG 5.2.4, 30. Treffen, 29. Juni 2009 Philipp P. Hasselbach, Technische Universität Darmstadt, Communications Engineering Lab 12

13 Simulation Results Single hotspot Adaptation to resource demand Capacity increases linear with bandwidth nonlinear (log2) with power ITG FG 5.2.4, 30. Treffen, 29. Juni 2009 Philipp P. Hasselbach, Technische Universität Darmstadt, Communications Engineering Lab 13

14 Simulation Results Single hotspot Multi hotspot Adaptation to resource demand Capacity increases linear with bandwidth nonlinear (log2) with power Independent hotspots for bandwidth allocation Dependent hotspots for power allocation ITG FG 5.2.4, 30. Treffen, 29. Juni 2009 Philipp P. Hasselbach, Technische Universität Darmstadt, Communications Engineering Lab 14

15 Simulation Results Single hotspot Multi hotspot Cluster hotspot Adaptation to resource demand Capacity increases linear with bandwidth nonlinear (log2) with power Independent hotspots for bandwidth allocation Dependent hotspots for power allocation Dependent hotspots for bandwidth allocation Independent hotspots for power allocation ITG FG 5.2.4, 30. Treffen, 29. Juni 2009 Philipp P. Hasselbach, Technische Universität Darmstadt, Communications Engineering Lab 15

16 Conclusion Power-Bandwidth Characteristics Assessment of the resource requirements of the cells Quality measure for resource allocation Two resource allocation algorithms Bandwidth allocation Transmit power allocation Dynamic resource allocation Adaptation to varying resource demands Performance gains bandwidth allocation for distributed hotspots scenarios transmit power allocation in concentrated hotspots scenarios Application in self-organising optimisation ITG FG 5.2.4, 30. Treffen, 29. Juni 2009 Philipp P. Hasselbach, Technische Universität Darmstadt, Communications Engineering Lab 16

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