報告人：陳柏偉 日期： 指導老師：林永松

 INTRODUCTION  SYSTEM MODEL AND SELF-CONFIGURATION  SELF-OPTIMIZATION MECHANISM  SIMULATION RESULTS  CONCLUSION 2

 INTRODUCTION  SYSTEM MODEL AND SELF-CONFIGURATION  SELF-OPTIMIZATION MECHANISM  SIMULATION RESULTS  CONCLUSION 3

 The ITU organization con fi rms that by the end of 2011 the number of mobile services subscribers reached 6 billion around the world, with a penetration factor of 86% [1] and recent surveys show that in the near future in-building generated phone calls and data traf fi c are expected to account for 50 and 70 of total volume, respectively [2].  Users are requiring an ever-higher data rates and a better coverage, especially in low coverage areas, such as macrocell edges and indoor environment. 4

 To cope with these challenges, femtocells were integrated with existing macrocells to increase their capacity, to maintain their coverage and to meet the requirement of quality of service (QoS) [3].  As femtocells are user-deployed, their proper operation relies on their self-con fi guration and self-optimization capabilities. 5

 In view of this, SONs constitute a novel approach that empowers operators to reduce the amount of manual intervention involved in network planning by relying on self-analysis, self-con fi guration and self-healing [5].  Using SON-enabling mechanisms, small cells can sense, learn from their environment and autonomously adjust their transmission strategies towards an optimal performance [8]. 6

 Nowadays, an extensive deployment of femtocells has been implemented, resulting in two main concerns.  One is the inevitable co-channel interference between macrocell and femtocells, which is one of the main factor limiting achievable spectral ef fi ciency and system coverage.  The other one is the resultant substantial energy consumption of femtocells. 7

 In this paper, self-con fi guration of transmit power for femtocells is adopted to guarantee the power leaked out of the home under a low level.  After self-con fi guration, we fi nd that there exists a femtocell-centered region in the room.  When UE is outside the region, macrocell will provide a higher SINR for UE than the femtocell on condition that femtocell turns off radio transmission and UE swithes to macrocell. 8

 The proposed self-optimization method calculates the virtual cell size and allows the femtocell to turn on radio transmission when distance between UE and femtocell doesn’t exceed virtual cell size, and turn off on the contrary.  This mechanism has the advantages that it can improve indoor SINR and reduce the energy consumption of femtocell’s transmission power. 9

 INTRODUCTION  SYSTEM MODEL AND SELF-CONFIGURATION  SELF-OPTIMIZATION MECHANISM  SIMULATION RESULTS  CONCLUSION 10

 the downlink SINR of femtocell UE i in femtocell j can be represented as  The obtainable throughput for UE in each location of femtocell is calculated as 11

 In self-con fi guration, the transmit power for each femtocell is set to a value that is on average equal to the strongest power received from macrocell at the target cell radius of r=10m.  Then the femtocell transmit power can be calculated (in dB) as 12

 INTRODUCTION  SYSTEM MODEL AND SELF-CONFIGURATION  SELF-OPTIMIZATION MECHANISM  SIMULATION RESULTS  CONCLUSION 13

 Assume that femtocell j is located in macrocell M, and UE i is in the edge of femtocell j.  If UE i is attached to femtocell j, the received SINR of UE is calculated as 14

 If UE i is attached to macrocell M, the received SINR of UE is calculated as  Based on the self-con fi guration scheme in Section II, p Mi is the roughly the same as p ji because UE i is located in the edge of the femtocell. 15

 Now if femtocell j switches off its radio transmission, the received SINR of UE i in the same condition is calculated as 16

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 So we de fi ne virtual cell size as a distance to femtocell, where SINR of UE attached to macrocell with femtocell turning off is equal to that attached to femtocell in the direction of connection between macrocell and femtocell.  From the de fi nition of virtual cell size, we can deduce that: 18

 Then virtual cell size can be written as 19

 The way to calculate virtual cell size in (8) needs to know received power from macrocells and femtocells in advance, which is hard to realize.  Initially, the femtocell turns off radio transmission and value of virtual cell size is set to 5 meters (half of cell radius). The  UE located in femtocell is connected to macrocell and sends its SINR to femtocell as SINR threshold.  The UE located in femtocell is connected to macrocell and sends its SINR to femtocell as SINR threshold. 20

 Then, femtocell starts self-con fi guration and UE switches to femtocell as signal from femtocell is stronger.  Every 500ms, femtocell detects its distance from UE and compares it with value of virtual cell size.  In the case that distance exceeds virtual cell size, if SINR of UE attached to femtocell is larger than threshold, the value of virtual cell size will be updated to the distance.  With time going on and UE moving, virtual cell size will get closer to the actual value. 21

 Based on the virtual cell size obtained above, the power control method allows a femtocell to turn on or turn off its radio transmissions through comparing the distance detected between UE and itself with virtual cell size every 500 ms.  If distance exceeds virtual cell size, femtocell will switch off radio transmission during next detection cycle and UE will switch to macrocell to obtain a higher SINR. 22

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 INTRODUCTION  SYSTEM MODEL AND SELF-CONFIGURATION  SELF-OPTIMIZATION MECHANISM  SIMULATION RESULTS  CONCLUSION 24

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 Scheme 1: Femtocell turns off radio transmission and UEs in femtocell coverage connect to macrocell all the time.  Scheme 2: Femtocell turns on radio transmission and UEs in femtocell coverage connect to femtocell all the time.  Scheme 3: self-optimization mechanism described in Section III. 26

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 Here the performance about energy ef fi ciency of scheme 3 is evaluated by examining the resultant reduction in femtocell’s transmit power consumption.  The average reduction in femtocell’s transmit power consumption can be characterized as a percentage of the total energy: 33

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 INTRODUCTION  SYSTEM MODEL AND SELF-CONFIGURATION  SELF-OPTIMIZATION MECHANISM  SIMULATION RESULTS  CONCLUSION 35

CONCLUSION  A method to calculate virtual cell size for each femtocell and a novel power-control scheme were proposed based on femtocell’s self-optimization capability.  It can make full use of femtocells and reduce the transmit power consumption of femtocells.  The evaluation results have proved that the self- optimization mechanism improves the SINR obtained indoor without increasing transmit power of femtocell and introduces an average reduction of approximately 58.5% in femtocell’s transmit power consumption. 36