In order to simulate the UE mobility,when simulation starts, the simulator gen- erates identifier for each UE and each cell, meanwhile it initiate its position and distribute each UE to every cell acceding the configuration, Then it traces each UE
4.3 Simulation result analysis 37
Figure 4.5: Handover management in simulator
movement every 1ms(Fig4.4), and records UE position, UE ID, the serving cell ID. When handover occurred, simulator records the handover information such as old eNB ID and target eNB ID, once handover completed, it release resource for old eNB, andnew eNB allocates the resource for UE 4.5 .
According the parameters as configured in Table 4.1, the simulation result is shown in the Fig 4.6,Fig 4.7, Fig 4.8 and Fig 4.9, respectively simulated the UE speed as 3Km/h,30Km/h and 120Km/h, and the UE number is based on 1,3,5,10. Through these three figures, it is obviously found that the HO number is greatly increased when the UE speed is higher, regardless of both HO algorithms. The growth of HO number lasted by increasing of UE number. We found that HO number in scenario of 30Km/h and 120Km/h is similar, the handover quality can not guarantee when the speed is higher than 30Km/h.
For Power-based HO algorithm, when UE speed performed 30Km/h and120Km/h, it produced huge number of HO, due to the speed is too high. In this huge of number, the majority number of HO is unnecessary, because of the high speed leads to very frequent Handover. According the UE movement trace record of simulation, the UE moves cross many HeNBs coverage and finally handover to the eNB(macrocell bases station), when it accessed each eNB coverage, the handover was triggered immediately, so these handovers are unnecessary.
For the proposed algorithm, in the scenario the number of HO is dramatically dropped comparing the Power-Based algorithm. It is efficiently avoided the unneces- sary HO occurred. According the UE movement record of simulation, we found UE in the femtocell directly handover to macrocell, it avoids the unnecessary HO triggered between HeNBs.
38
Simulation for new proposed handover decision algorithm and simulation result analysis 1 3 5 10 0 200 400 600 800 1000 N b . of U E i n e ac h Fe m t oc e l l Nb . o f HO
Proposed Algorithm with Speed 3Km/h
Proposed Algorhm Power−based HO Algorthm
Figure 4.6: Proposed Algorithm with speed 3Km/h
In the scenario of 3Km/h and15Km/h, we found the reason of handover reduction cause the the non-CSG UE is we restrict the access condition. These two velocities are normal in real life, the handover performance is also enhanced.
4.3 Simulation result analysis 39 1 2 3 4 0 200 400 600 800 1000 1200 1400 N b . of U E i n e ac h Fe m t oc e l l Nb . o f Nb HO
Proposed Algorithm with Speed 15Km/h Proposed Algorithm
Power−Based HO Algorithm
Figure 4.7: Proposed Algorithm with speed 15Km/h
1 3 5 10 0 500 1000 1500 2000 2500 3000 N b . of U E i n e c ah f e mt o c e l l Nb . o f H O
Proposed Algorithm with speed 30Km/h Proposed algoritm
Power−based HO algorithm
40
Simulation for new proposed handover decision algorithm and simulation result analysis 1 3 5 10 0 500 1000 1500 2000 2500 3000 N b . of U E i n e ac h Fe m t oc e l l Nb . o f HO
Proposed Algorithm with Speed 120Km/h
Proposed Algorthm Power−based HO Algorthm
Chapter 5
Conclusion and further work
5.1
Conclussion
In this thesis report, it is introduced LTE network and the statement of femtocell network, meanwhile we researched why do we need the femtocell and to researching for mobility management, the main reason of that is huge number of mobile device is in- creased rapidly recently, the network is more and more congested, as well as lower the network system performance. LTE network system proposed the femtocell to offload the macrocell traffic, solve network edge cover problem. With femtocell proposing, it brings mobility management issue caused by the huge number of mobile devices mov- ing. The handover is the most important part in the mobility management, because the handover is frequently occurred when UE is moving, hence the handover number directly affects the system performance, and network QoS. Then we found that the a sophisticated handover decision algorithm can improve the mobility management. In order to well kwon the principle of hangover, we studied the integrated LTE network architecture and each functions of its elements. The signalling of handover transmis- sion is based on both X2 and S1 network interface. The contribution of this thesis report is to design a new efficient handover decision algorithm. Hence we surveyed this handover technology in current literature, and we studied the existed handover decision algorithm. Through the survey, we found two issues needed to improve, the first is the majority of current handover algorithms is lack to consider the co-layer han-
42 Conclusion and further work
dover in femtocell, and the second issue is in case of UE fast enter fast leave problem. In order to solve that, we proposed a new handover decision algorithm depending on these algorithms, it is based on the UE velocity. In this algorithm, we limited access according the UE velocity for first issue, moreover we proposed a time to trigger the handover. Through the simulation for proposed algorithm, we obtained the desirable outcome, the handover is dramatically reduced comparing the conventional algorithm.