self-organized spectrum chunk selection algorithm for local area deployment sanjay kumar 1 yuanye...
TRANSCRIPT
Self-organized Spectrum Chunk Selection Algorithm for Local Area
Deployment
Sanjay Kumar 1
Yuanye Wang 2, Nicola Marchetti 2
1Birla Institute of Technology, Ranchi, India
2Aalborg University, Denmarkywa @es.aau.dk, [email protected]
2
Introduction Motivation and Objectives Algorithm Scenaion Description Performance Metrics Evaluation Parameters Performance Results Conclusions
Contents
3
Introduction
The IMT-A : 4G systems with new capabilities To be operational around the year 2015 Provide access to wide range of telecommunication services Target peak data rates 1 Gbps in DL and 500 Mbps in UL Focus on Local Area (LA) deployment scenarios The Wide Area (WA) deployment uses fixed frequency reuse schemes It needs proper network planning, such as :
Frequency reuse plans
Base station location
Controlling transmit power levels etc. The LA of IMT-A : expected random and uncoordinated deployment Hence netwrok planning not feasible Also, possiblly Home Node Bs (HeNBs) share the available radio spectrum A mechanism is needed to assign spectrum in self organized manner and improve throughput
performance
4
Motivation and Objectives
Reuse 2 gives the highest throughput performance in LA deployment [11], but needs Network planning
A mechanism is needed to achieve nearly same performance in random deployment
Fig. 1. Possible chunk selection with reuse 2 in random deployment
Fig. 2. Allocation for reuse 2 with optimal network planning
To minimize the mutual inter-cell interference among HeNBs with random and uncoordinated deployment in order to improve throughput performance .
5
Algorithm
Figure 3: Flow chart of the Algorithm
Steps
1.Initialization2.Update chunk selection 3.Interference consideration 4.Chunk switch over
6
Random selection of a spectrum chunk Initialization with sequence number & switch-over number Sequence number : determines position in queue Switch-over number : helps to avoid dead lock situation It indicates the maximum # of times a chunk is retained
Algorithm Description
Spectral bandwidth is divided in two equal size spectrum chunks (for considering to compare with reuse 2) Algorithm could be used for any reuse schemes
Step 1: Initialization phase
7
Algorithm Description (1) Step 2: Condition to update the chunk selection
Step 3: Interference consideration for chunk selection
The sequence number is reduced by one in each update interval This indicates HeNB turn to update its chunk selection
Comparison of interference levels over the chunks The UL-RIP is used as interference measurement yard stick UL- RIP is defined as the total power received over the spectrum chunk The chunk selection is based on : Abs (RIP1 - RIP2 ) > P_Threshold This ensures a sufficient amount of interference difference before decision The threshold indicates a tradeoff between :
tolerable interference vs increased signaling requirement
8
Algorithm Description (2)
Step 4: Switching over to other Chunk
Main features of the Algorithm Uses UL- RIP (already standardized for LTE system) Works in a random and uncoordinated deployment Requires very little signaling exchangeChunks allocation in sequence (avoids complexity in interference assessment) If # of HeNBs is very high : a long convergence time may be requiredProvides a scalable solution. Performance is upper-bounded by reuses 2 schemeCould be used for both DL & UL
The chunk with minimum RIP is chosen
9
Scenario Description
HeNB Location : center of each cell (also examined with randomized) HeNB coverage area . 50 x 25 m (consisting of 10 rooms) Simulation method : snap-shot based Several thousands snap-shots are simulated Users : uniformly distributed locations Throughput :Mapping SINR [8]
100 m
50 m
Figure 4: LA office indoor with 4 HeNBs
10
Performance Metrics
Average Cell Throughput: Cell throughput averaged among all the simulated cellsCell Edge User Throughput: The 5% user outage throughput , CDF value Chunk Selection Interval: Time period for one chunk selection operation. It contains an integer number of transmission frames.
Some simplifications are also assumed:
No power controlRound Robin for frequency domain schedulingFast fading not considered
11
Simulation Parameters
PARAMETERS SETTINGS
Spectrum allocation 100 MHz at 3.5 GHzAccess schemes DL: OFDMA, UL: SCFDMADuplexing Schemes TDD# UE’s per Cell 5~10 Total Transmit Power 24dBmReceiver Noise Figure 7-9 dB Room Size 10x10 mCorridoor width 5 m Internal walls light attenuation (5dB) Shadow fading LOS: 3dB, NLOS: 6dB (SD)Path Loss models
LOS 18.7 log10 (d) + 46.8 + 20log10 (f /5.0)NLOS 20 log10 (d) + 46.4 + nw · Lw + 20log10
(f /5.0)where,
d = direct-line distance (m)f = carrier frequency (GHz)nw = # of walls between Tx & Rx Lw = wall attenuation (dB)
12
Performance Results (1)
Figure 5 : Comparison of DL Average Cell Throughput
DL Average Cell Throughput
Improved compared to reuse 1 and 4 schemesSlightly lower compared to reuse 2 scheme Reuse 2 needs planning for optimal performance. Proposed algorithm performs in self- organized manner with
random and un-coordinated deployment
13
Figure 6: Comparison of DL Cell Edge User Throughput
Performance Results Performance Results (2)
DL Cell Edge User Throughput
significantly higher compared to reuse 1 scheme (200 ~ 300 %)
Nearly same as
reuse 4 schemeHowever lower than reuse 2 scheme
14
Performance Results Performance Results (3)
Figure 7 : Convergence Time of the Algorithm
Convergence Time
The performance is stabilized after 10 selection intervals, with Significant Improvement
15
Figure 8: DL Average Cell Throughput with Randomized HeNB Locations
Performance Results Performance Results (4)
Randomized HeNB Locations
It may be difficult to control HeNB locations
Especially in home scenarios
Nearly the similar performance is realized
With the same chunk allocation as DL, The similar performance has been realized in UL also
16
Conclusions
An Algorithm for self organized spectrum chunk selection has been proposed It minimizes mutual inter-cell interference and improves the system throughput performance Performance approaches fixed frequency reuse 2 scheme Gives much better performance than fixed frequency 1 and 4 schemes Suitable for LA with large scale random and uncoordinated deployment Works with very limited signaling exchange Needs no additional measurements than what is already established for the LTE The main features of the algorithm are scalability and operation simplicity
17
References
[1] H. Murai, M. Edvardsson and E. Dahlman, “LTE-Advanced – The Solution for IMT-Advanced”, ERICSSON, 2008.
[2] IEEE 802.11 B. P. Crow, I. Widjaja, J.G. Kim, P. T. Sakai, “Wireless Local Area Networks”, IEEE Communications Magazine, September 1997, pp. 116-126.
[3] ETSI MCC, “Report of 3GPP TSG RAN IMT-Advanced Workshop”, April 7-8, 2008.
[4] Arne Simonsson, “Frequency Reuse and Intercell Interference Co-ordination in E-UTRA”, IEEE VTC2007-Spring, pp. 3091-3095
[5] R. Giuliano, C. Monti and P. Loreti, “Wireless Technologies Advances for Emergency and Rural Communications - WiMAX Fractional Frequency Reuse for Rural Environments”, IEEE Wireless Communications, June 2008, pp. 60-65
[6] T. S. Rappaport and R. A. Brickhouse, “A Simulation Study of Urban In-building Cellular Frequency Reuse”, IEEE Personal Communications, February 1997, pp. 19-23
[7] IST-4-027756 WINNER II, D1.1.2 “WINNER II Channel Models part I- Channel Models”, Sept 2007.
[8] P. Mogensen, W. Na, I. Kovács, F. Frederiksen, A. Pokhariyal, K. Pedersen, T. Kolding, K. Hugl and M. Kuusela, “LTE Capacity compared to the Shannon Bound”, IEEE VTC2007-Spring, pp. 1234-1238.
[9] TR 101 112 V3.2.0 (1998-04), Technical Report, Universal Mobile Telecommunications System (UMTS); Selection Procedures for the Choice of Radio Transmission Technologies of the UMTS (UMTS 30.03 version 3.2.0)
[10] 3GPP TR 25.814 Technical Specification Group Radio Access Network; Physical Layer Aspects for Evolved UTRA, V7.0.0 (2006-6).
[11] Sanjay Kumar, “Techniques for Efficient Spectrum Usage for Next Generation Mobile Communication Networks: An LTE and LTE-A case Study” a PhD thesis at Aalborg University, Denmark, June, 2009 (ISBN 978-87-92328-29-8).
18
Thank You