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SON Functions for Multi-Layer LTE and Multi-RAT Networks INFSO-ICT-316384 SEMAFOUR D4.1 SON functions for multi-layer LTE and multi-RAT networks (first results) Contractual Date of Delivery to the EC: November 30th, 2013 Actual Date of Delivery to the EC: November 29th, 2013 Work Package WP4 Participants: NSN-D, EAB, iMinds, FT, TNO, TUBS, NSN-DK Authors Daniela Laselva, Zwi Altman, Irina Balan, Andreas Bergström, Relja Djapic, Hendrik Hoffmann, Ljupco Jorguseski, István Z. Kovács, Per Henrik Michaelsen, Dries Naudts, Pradeepa Ramachandra, Cinzia Sartori, Bart Sas, Kathleen Spaey, Kostas Trichias, Yu Wang Reviewers Thomas Kürner, Kristina Zetterberg Estimated Person Months: 53 Dissemination Level Public Nature Report Version 1.0 Total number of pages: 141 Abstract: Five promising SON functionalities for future multi-RAT and multi-layer networks have been identified within the SEMAFOUR project, namely, Dynamic Spectrum Allocation and Interference Management, multi-layer LTE / Wi-Fi Traffic Steering (TS), Idle Mode mobility Handling, tackling the problem of High Mobility users and Active/reconfigurable Antenna Systems. This document covers the detailed description of the SON features, the Controllability and Observability analysis as well as initial directions of the SON design for the above-mentioned five use cases. Furthermore, initial performance evaluation in the realistic “Hannover scenario” is provided for the proposed TS SON algorithms. Keywords: Self-management, Self-optimization, SON, Multi-layer, Multi-RAT, Spectrum Allocation, Traffic steering, High Mobility, Active Antenna, Controllability and Observability SEMAFOUR (316384) D4.1 SON functions (first results) Executive Summary Self-management and self-optimization will play critical roles in the future evolution of wireless networks. The complexity of future multi-layer / RAT technologies and the pressure to be competitive, e.g. by reducing costs (Operational Expenditure OPEX, Capital Expenditure CAPEX), will be key drivers. The EU FP7 funded project SEMAFOUR (SElf-MAnagement FOr Unified heterogeneous Radio access networks) aims at designing the next SON generation, i.e. a unified self-managed and optimized system for the efficient and holistic operations of a heterogeneous mobile network [1]. One of the key goals of the SEMAFOUR project is the development of multi-RAT / multi-layer SON functions that provide closed loop solutions for the configuration and optimisation of key configuration parameters related to mobility and network resources. In this light, a number of promising use cases for future networks have been identified during the initial phase of the project. The relevance of the selected features has been also verified based on the feedback of the project Advisory Board. The most suitable functions selected for investigation within SEMAFOUR are namely: Dynamic Spectrum Allocation and Interference Management (DSA/IM) Multi-layer LTE/Wi-Fi Traffic Steering (TS) Idle mode mobility handling (IMH) Tackling the problem of High Mobility users (HM) Active/reconfigurable Antenna Systems (AAS) This deliverable covers the definitions and the initial studies for the above-mentioned SON functions in the multi-layer LTE scenario (with the exception of the LTE / Wi-Fi TS case). Furthermore, this document includes the first results achieved for the selected SON functions while the final results and multi-RAT aspects will be captured in the subsequent SEMAFOUR deliverables, Deliverable 4.2 ‘SON functions for multi-layer LTE and multi-RAT networks (final results)’, Deliverable 4.3 ‘SON functions for integrated multi-layer and multi-RAT networks’, and public Deliverable 4.4 ‘SON for future networks’. In the following, specifics of the individual use case studies covered in this deliverable are highlighted. The DSA/IM use case studies optimization techniques for spectrum allocation adapted to the spatial and temporal load / bandwidth requirements. The first step was to perform a set of Observability and Controllability (C&O) investigations, with the main target of uncovering the potential of DSA like schemes in typical urban LTE network deployments including macro and micro cells and several frequency layers. The first and most important result from these C&O studies is that in order to properly analyse DSA-like schemes a suitable baseline is required in terms of LTE traffic steering and load balancing. A second finding is that a DSA scheme is likely to be beneficial only when the offered traffic load in the system is within certain lower and upper limits. Significant effort has been spent in analysing the required traffic steering and load balancing mechanisms, thus this deliverable presents a detailed set of results concerning the C&O study based on which a DSA SON algorithm is proposed. The evaluation of the intra-RAT LTE DSA algorithm studies will be continued and finalized in Deliverable 4.2. The current findings are relevant and will be used further in the inter-RAT DSA studies, i.e. when including the LTE, 3G and / or GSM network layers. The TS use case addresses QoS based traffic steering techniques between multi-layer LTE and Wi-Fi networks. Wi-Fi is being used by operators as a complementary technology to offload cellular traffic, and the current trend is to enable Wi-Fi as an integrated piece of operators’ networks. Therefore, intelligent TS between the two access networks is a key technology component. Without traffic steering in place, the Wi-Fi network can easily become congested, thus degrading the user experience and operator service quality. Moreover, both user experience and system efficiency depend on the traffic steering between the two networks. In this deliverable, two closed-loop SON algorithms, Wi-Fi RSS-based and LTE RSRP-based, are proposed and built upon the outcomes of the C&O analysis of the corresponding control parameters, which proved to be effective for network access selection Version 1.0 Page 2 of 141 SEMAFOUR (316384) D4.1 SON functions (first results) control. The SON algorithms were evaluated by system level simulations in the “Hannover scenario,” an outdoor hot zone scenario with three network layers, i.e. LTE macro as well as densely deployed collocated LTE micros and Wi-Fi APs. Simulation results showed that both SON algorithms can balance the load between the two access networks. For the RSS-based algorithm the throughput analysis is presented, which shows significantly improved user throughput comparing to reference cases of “Wi-Fi if coverage” and TS with fixed RSS thresholds. The IMH use case focuses on the optimization of the cell reselection procedure so that the UE always camps on the most appropriate cell. By being camped on a suitable cell, connection times are reduced and subsequent unnecessary handovers once the user becomes active are avoided leading to signalling, packet loss and delay reduction, which may directly affect the QoS for the user and diminish the strain on the network. An intelligent IMH would work as a pro-active load balancing mechanism, similar to Mobility Load Balancing (MLB) or traffic steering. The optimization of the cell reselection procedure could be done either by dynamically adjusting the cell reselection control parameters or by adding extra control parameters and extra complexity in the user equipment. Typically, the MLB and TS schemes focus on the connected mode, where the user is active and radio link failures and call drops may occur. For best results, the traffic steering strategies in both idle and connected mode should be aligned in order to prevent conflicts and maximize gain. However, based on the state-of-the-art and technical review, the predicted magnitude of the IMH gains are marginal. It was therefore decided not to continue to the simulation phase with this use case. The HM use case focuses on cases when users tend to make frequent handovers, for example, when there is a dense deployment of small cells or when user velocities are high. This use case focuses on mitigating these frequent handovers and the negative impact that is caused by them both on the user and core network performance. In order to do so the SON function developed in this use case will try to predict the future mobility behaviour of users based on the trajectory that they follow through a cell. By assuming that users that follow similar trajectories through a cell will behave the same in the future a user can be steered more appropriately, resulting in fewer handovers. In this document, a modified version of the Dynamic Time Warping (DTW) algorithm is developed which identifies users that follow similar trajectories through a cell. This algorithm searches for similarities between recent measurements made by active users and measurements that are made by users that were active in the past. Results show that the modified DTW algorithm is able to effectively identify users that follow similar trajectories within certain bounds. As reducing the effects of frequent handovers on the core network is an important part of this use case, a second part of this use case focuses on quantifying these effects. For this, a theoretical model is constructed, which is then used to estimate the overhead and delays that are caused by handovers in the core network. In the AAS use case the capabilities of modern active antenna systems are under examination, and more specifically, the effectiveness of Vertical Sectorization (VS) as a densification approach, is evaluated through simulations. The network performance is measured under various conditions in the Controllability & Observability study, revealing the necessity for a SON function to control the VS, in order to obtain densification gains. Two main control parameters were defined for the VS, namely the down-tilt per vertical sector and the transmission power per vertical sector. Moreover, crucial KPIs such as aggregated average, 5th and 10th percentile user throughput, system resource utilization and coverage percentage, were identified, in order to evaluate the performance of the network, and they were monitored on a per network, per cell and per pixel (geographical area of 10 x 10 meters) basis.
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