1 / 23

Performance Analysis of LTE-Advanced Relay Node in Public Safety Communication

Performance Analysis of LTE-Advanced Relay Node in Public Safety Communication. M.Sc. Inam Ullah Supervisor: Prof. Jyri Hämäläinen Aalto University School of Electrical Engineering. Outline. Introduction Goal Relaying Basics Simulator Development Simulation Results Future Tasks

johnna
Download Presentation

Performance Analysis of LTE-Advanced Relay Node in Public Safety Communication

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Performance Analysis of LTE-Advanced Relay Node in Public Safety Communication M.Sc. Inam Ullah Supervisor: Prof. Jyri Hämäläinen Aalto University School of Electrical Engineering

  2. Outline • Introduction • Goal • Relaying Basics • Simulator Development • Simulation Results • Future Tasks • Questions & Suggestions

  3. Introduction 3GPP LTE-Advanced Requirements: • Data rates of 1Gbps in DL & 500 Mbps in UL. • High spectral efficiency both in DL (30 bps/Hz) and UL (15 bps/Hz). • Improve cell edge capacity • Reduce the user and control plane latencies. Proposed Technologies: • Carrier aggregation • Extended MIMO • Relay node deployment • Femto cell deployment • Pico base station deployment

  4. Goal • Deployment of relay nodes into existing overlaid macro base station in system level simulator and analyze the impact of relay deployments on network performance. • Relaying usage in public safety communication (Emergency Telemedicine)

  5. Relaying Basics (1/5) I. Relaying: • Two-hop technique reducing the UE-Infrastructure distance • Increases high data rates possibility • Overcome the low SINR problem especially at the cell edge • Overcome the shadowing creats coverage holes

  6. Relaying Basics(2/5) II. Relay Node (RN): • Small wireless base station connected via donor cell to core network • Low transmission power (30dBm). • Eliminate high cost site selection,planning,acquisation and installation. • Admit the wireless Relay link, eliminate the high cost of fixed link. III. Relay link & Access link: • Relay link refers to base station-relay connection. • Access link refers to relay-terminal connection. • Relay node connect to donor cell via relay link. • Both links are time-divisioned multiplexed.

  7. Relaying Basics (3/5) V. RN are further classified according to their resource utilization strategy on the relay and access links: • Inband RN • Relay & access link shares the same frequency spectrum. • Relay link also shares the same frequency spectrum with direct link. • Type 1 RN • Control cells of its own with Physical cell ID as normal eNB. • Transmit its own synchronization channels, reference symbols. • Non-transparent to UE . • Type 2 RN • Doesn’t have its own Physical cell ID. • Transparent to UE. • Outband RN • Relay link operates in separate frequency spectrum with access link. • Shares the same frequency spectrum with direct link.

  8. Relaying Basics (4/5) VI. RN are further classified from deployment perspective

  9. Relaying Basics (5/5) VII. Relaying Usage

  10. Simulator Development (1/5) I. Network Layout • 7 tri-sectored hexagonal cells • Inband Type 1 nomadic relay node (Ambulance repeater) • 5*5 building (25 flats) • 8 Indoor emergency UEs • 10 Outdoor non-emergency UEs / sector II. Simulation Scenarios • 3GPP Urban scenario case 1 • Inter-site distance (ISD) = 500 m

  11. Simulator Development (2/5) III. UE SINR & Throughput computation: Note: The number ’0’ represents the serving eNB or RN. Fast fading is not considered in the simulations. Numerator gives the received signal power from serving base station while denominator gives the co-channel interference and noise power from the interferes.

  12. Simulator Development (3/5) IV. Resource Scheduling Method: • A Max-Min Fairness (MMF) scheduling technique is used to distribute the network resources at eNB on direct link as well as at RN on Access link with relay link constraint. • From cellular system perspective, this algorithm aims to maximize the minimum user throughput by allocating more network resources to UEs with low Signal-to-Interference-and-Noise-Ratio (SINR), with a condition that all UEs obtain same throughput level. V. Channel Models: • A modified version of COST-231 is proposed namely COST231-Walfisch-Ikegami (WI) Model.

  13. Simulator Development (4/5) VI. Simulation Parameters:

  14. Simulator Development (5/5) I. Benchmarking the simulator results with a reference [1]: • For Scenario (3GPP Case 1 Urban, 4 RN per sector, Downlink) [1]. A. Bou Saleh, Ö. Bulakci, S. Redana, J. Hämäläinen, B. Raaf: "Enhancing LTE-Advanced Relay Deployments via Biasing in Cell Selection and Handover Decision", IEEE Personal, Indoor and Mobile Radio Communications Symposium (PIMRC), Istanbul, Turkey, 2010.

  15. Emergency Telemedicine results (1/6) I. What is Emergency Telemedicine? • Emergency telemedicine is the usage of telecommunication technologies by Emergency Medical Services providers (hospitals, paramedics, etc) so as to ensure a rapid and coordinated medical care to patients at emergency sites. • This typically enables emergency use cases, such as, setting up a communications link to provide field paramedics with expert opinion from physicians at a hospital or trauma center, thus enabling better-informed diagnosis or medical interventions by the EMS responder. • A high-speed link may enable for sharing of large amounts of patient measurements or images prior to transfer to relevant trauma center.

  16. Emergency Telemedicine results (2/6) • Eight Indoor Emergency User Equipments • Via comprehensive system level simulations, a comparative study of eNB only and REC networks performance is carried out, in terms of cumulative distribution function (CDF) of indoor EUE data rates. • Moreover, we also examine the impact of RN transmission on the performance of non-emergency UEs of only those eNBs, which are serving the indoor EUE. • Below figures indicates simulations are carried out for cell center and cell edge with UE performance constraint of 2 Mbps.

  17. Emergency Telemedicine results (3/6) • The REC network outperforms the eNB only deployment, with almost 70% indoor EUEs in cell center case and 77% indoor EUEs in cell edge case, achieve a data rate of higher then 6 Mbps (i.e. from mid to high data rate levels) .This gain is due to the fact that indoor EUE receive good enhanced signal quality from RN as well as experience less competition for radio resources. • However, in addition to performance constraint of 2 Mbps, the high power eNB creates interference towards the indoor EUE, resulting an outage (2%) in case of cell center scenario, which is negligible for the cell edge scenario where the eNB interference decays over the long distance.

  18. Emergency Telemedicine results (4/6) • Similarly, below figures show the CDF plots for outdoor non-emergency UE data rates. The results demonstrate the deterioration impact of RN deployment on the performance of outdoor non-emergency UEs, due to the RN interference power. However, this degradation is insignificant as compared to the indoor coverage provided in emergency events.

  19. Emergency Telemedicine results (5/6) Four Indoor Emergency User Equipments • Below figures show the results for the case of four indoor EUEs, where the data rates are comparatively improved inside the building as almost 75% indoor EUEs in cell center case and 85% indoor EUEs in cell edge case, achieve a data rate of higher then 6 Mbps. • This improvement is due to the fact that, reducing the number of indoor EUEs ease the competition to allocate more network resources to serving indoor EUEs. • Besides the data rate improvements, the outage probability has been comparatively increased. It is due to the reason that, indoor EUEs are randomly distributed inside the building while few of them might experience low RSRP (Reference signal received power) towards RN and/or eNB and need more network resources, which eventually being dropped.

  20. Emergency Telemedicine results (6/6) Two Indoor Emergency User Equipments • Below figures show the results for the case of 2 indoor EUEs, where the data rates are comparatively improved inside the building as almost 75% indoor EUEs in cell center case and 88% indoor EUEs in cell edge case, achieve a data rate of higher then 6 Mbps. • This improvement is due to the fact that, less number of indoor EUEs connected will get more network resources as compared to above cases.

  21. Future Work • The future work incorporating multiple tasks to be investigated as follow; • Currently, the building considered in 5*5 residential apartments with a single floor. Hence, for follow-up simulations, we will consider the scenario whereby the building is a multi-storey. • To observe the impact on indoor non-emergency UE. • The performance of multiple un-coordinated REC used by various PMR organizations. These RNs coexist and operate in the same frequency band, compete for the available radio resources at eNB. Hence, a scheduling mechanism with pre-defined requirement will be needed for optimal RN operations.

  22. Conference Paper • A conference paper has been submitted to Mobihealth conference with title as follows; • I. Ullah, Z. Zheng, E. Mutafungwa, and J. Hämäläinen : On the use of Nomadic Relaying for Emergency Telemedicine Service in Indoor Environment. • http://mobihealth.name/show/home

  23. For Questions & Suggestions inam.ullah@aalto.fi

More Related