1 Study of Self-Optimization of Neighbor Cell Listing for eNodeB in Long Term Evolution (LTE) Hanan Naeem Thesis Worker Ericsson Finland

2 Study of Self-Optimization of Neighbor Cell Listing for eNodeB in Long Term Evolution (LTE) Author:Hanan M. Naeem Supervisor:Prof. Riku Jäntti Instructor:M.Sc. (Tech) Mira Heiskari

3 What is LTE/SAE ? Next generation mobile communications technology standard LTE - Long Term Evolution –Study and work done by 3GPP to specify the long term evolution of the 3G radio part referred as E-UTRAN (Evolved-UMTS Terrestrial Radio Access Network) SAE - System Architecture Evolution –Study and work by 3GPP specifying the long term evolution of the 3G architecture, EPC (Evolved Packet Core)

4 LTE Design Targets High data rates –DL target: 100 MbpsUL target: 50 Mbps –Cell-edge data rates 2-3 times that of Rel-6 HSPA Low delay/latency –User plane RTT: Less than 10 ms –Channel set-up: Less than 100 ms High spectral efficiency –Targeting 3 times Rel-6 HSPA High performance for broadcast services Spectrum flexibility –Operation in a wide-range of spectrum allocations –Support for FDD, Half-duplex FDD and TDD Modes Cost-effective migration from current/future 3G systems

5 LTE - Radio Access Network Decentralized structure Single eNodeB encompassing all major functionalities DL preferred technique is OFDM, due to its flexible features like robustness, flexible bandwidth allocation and broadcast/multicast transmissions SC-FDMA used for UL due to its good PAPR (Peak-to-Average Power Ratio) performance

6 SAE Core Network IP based Core network EPC to be based on a single-node concept (GW) with all necessary functions encompassed in one node except the HSS (Home Subscriber Server) MME (Mobility Management Entity) responsible for authentication of the user by interacting with HSS, bearer activation and deactivation and GW assignment during handovers Anchors all 3GPP and non-3GPP technologies like GSM,HSPA, WiMax

7 LTE Services Rich voice Paid information Data messaging Fast browsing Personalization TV/ video on demand High quality music streaming Mobile commerce Mobile data networking Gaming

8 Objectives of this Thesis Study of telecom operators’ requirements for future Thorough study of the concept of self-configuration & self-optimization. Neighbor Cell List (NCL) self-optimization in cellular networks Suggesting a possible NCL self-optimization algorithm

9 Contemporary Operators’ Requirements Mobile Broadband Access Seamless access and mobility Support of Broadcast and Multicast Personalization IP Traffic Billing Network Automation –Self-planning –Self-configuration –Self-optimization –Self-testing –Self-healing –Self-protecting

10 Autonomic Computing Autonomic computing is often referred to as self-CHOP (Self-Configuration, - Healing, - Optimization, and -Protection) Automatic: Autonomic system must be able to self control and automatically configure or reconfigure Adaptive: An autonomic system must be sensitive and be able to alter its course of action based on the situations confronted based on defined policies Aware: An autonomic system must know itself and be able to monitor its operational context

11 Self-Configuration Configuration of a new node or a radio base station deployed or installed in an already working cellular network Node undergoes self-automated management tasks to adjust to the actual confronted environment Automated management tasks take place in pre-operational state of the node before entering the operational state Referred to ´plug and play´ behavior of the network nodes which simplifies the installation processes

12 Self-Configuration Features Decentralization: Nodes or entities interact and communicate with each other in a localized manner Adaptability: Ability to adapt in parallel with user density and traffic patterns Survivability: Capability of a system to fulfill its mission, in a timely manner, in the presence of attacks, failures, or accidents Scalability: The network still works with acceptable service quality and functionalities when the number of nodes grow very large

13 Self-Optimization Continuation of self-configuration Comes into action after self-configuration has been completed and the network enters an operational state Purpose is to maintain and improve the efficiency, service quality and performance of the network Change suggestions are based on performance indicators and matrices from the network itself sent by the mobile terminals

14 Major Self-Optimization Tasks Cell Identity Management: –Due to the availability of limited number of 504 physical-layer cell identities, Cell Identity Management is critical to avoid conflicts Neighbor Cell Management: –Self-optimization enables each eNodeB manages a list of immediate neighboring eNodeBs in the network Power Tuning: –Self-optimized power tuning controls coverage of the nodes, interference levels maintenance, pilot signaling strength in handover (HO) regions, automated antenna tilting, overshooting cell issues and overall network throughput

15 NCL Self-Optimization Approaches Layer based approach –Policy based three layered architecture –Graph associated to each layer functionality Range based approach –Neighbor cells detected within a certain range of the candidate cell are regarded as potential neighbors –Overlapping identification finalizes the neighbor cell

16 NCL Self-Optimization Approaches (Cont.) Antenna radiation based approach –Same as range based technique –Neighbors are added in the NCL based on the overlapping of antenna radiation patterns

17 Suggested Algorithm for NCL Self-Optimization

18 Assumptions All LTE mobile terminals are GPS equipped. Self-configuration phase has been completed successfully. Sectorization is observed throughout E-UTRAN There are no coverage gaps after self-configuration Self-configuration phase has allocated each eNodeB cell with a calculated value of r All cell IDs, corresponding IPs and assigned parameter ‘r’ to each cell are stored in a central database. UE triggers measurement reports once a new potential neighbor comes across. This information is sent to the eNodeB for NCL calculations. Adjacent two cells (sectors) of a cell site are always added in the NCL

19 Overlapping Judgment and Cell Addition to NCL Geographical coordinates used for angular calculations Measurements done with respect to antenna main lobe direction Overlapping detected based on different UEs in the field and measurement reports sent If the distance ‘d’ between UE and the detected cell is less than r, then its added as a neighbor in the NCL

20 Cell Deletion From NCL Unwanted and obsolete neighbors are to be deleted to keep the NCL updated Conditions for deletion: –Σ i [Φ i ] = ά, i=1,2, … N –Identify which cells are not been assigned any angle during the iteration process –Analyze those cells in the NCL which are tagged with smaller Φ than the newer detected cell.

21 Conclusions LTE is expected to meet most of the current market requirements Self-managing processes would make this communications technology more robust, scalable and adaptable With self-optimization of NCL would result in better system performance and throughputs Self-managing services would also decrease OPEX for the operators and manual intervention related issues would be avoided Geographical coordinates based NCL updating mechanism are simple and easy to implement with more accurate results

22 THANK YOU !!