with Backhaul Considerations Performance evaluation

Slides:



Advertisements
Similar presentations
February 20, Spatio-Temporal Bandwidth Reuse: A Centralized Scheduling Mechanism for Wireless Mesh Networks Mahbub Alam Prof. Choong Seon Hong.
Advertisements

VIKAS REDDY BEERAVALLY HETEROGENEOUS NETWORKS. Radio Network Evolution to heterogeneous Todays Networks 2015 Heterogeneous Networks Single Standard Radio.
Telecommunication Networks and integrated Services (TNS) Laboratory Department of Digital Systems University of Piraeus Research Center (UPRC) University.
1 Cross-Layer Design for Wireless Communication Networks Ness B. Shroff Center for Wireless Systems and Applications (CWSA) School of Electrical and Computer.
August 6, Mobile Computing COE 446 Network Planning Tarek Sheltami KFUPM CCSE COE Principles of.
1 A Distributed Algorithm for Joint Sensing and Routing in Wireless Networks with Non-Steerable Directional Antennas Chun Zhang *, Jim Kurose +, Yong Liu.
Supervisor: Prof. Jyri Hämäläinen Instructor: M.Sc Zhong Zheng A part of NETS2020 project Ying Yang
MAXIMIZING SPECTRUM UTILIZATION OF COGNITIVE RADIO NETWORKS USING CHANNEL ALLOCATION AND POWER CONTROL Anh Tuan Hoang and Ying-Chang Liang Vehicular Technology.
International Technology Alliance In Network & Information Sciences International Technology Alliance In Network & Information Sciences 1 Cooperative Wireless.
Constrained Green Base Station Deployment with Resource Allocation in Wireless Networks 1 Zhongming Zheng, 1 Shibo He, 2 Lin X. Cai, and 1 Xuemin (Sherman)
1 11 Subcarrier Allocation and Bit Loading Algorithms for OFDMA-Based Wireless Networks Gautam Kulkarni, Sachin Adlakha, Mani Srivastava UCLA IEEE Transactions.
SoftCOM 2005: 13 th International Conference on Software, Telecommunications and Computer Networks September 15-17, 2005, Marina Frapa - Split, Croatia.
College of Engineering WiFi and WCDMA Network Design Robert Akl, D.Sc. Department of Computer Science and Engineering Robert Akl, D.Sc. Department of Computer.
On Placement and Dynamic Power Control Of Femto Cells in LTE HetNets
Device-to-Device Communication in Cellular Networks Speaker: Tsung-Han Chiang Date: Feb. 24,
1 A Novel Capacity Analysis for Wireless Backhaul Mesh Networks Tein-Yaw David Chung, Kung-Chun Lee, and Hsiao-Chih George Lee Department of Computer Science.
Fairness-Aware Cooperative Resource Allocation for Self-Healing in SON-based Indoor System Kisong Lee, Student Member, IEEE, Howon Lee, Associate Member,
Advanced Spectrum Management in Multicell OFDMA Networks enabling Cognitive Radio Usage F. Bernardo, J. Pérez-Romero, O. Sallent, R. Agustí Radio Communications.
Downlink Scheduling With Economic Considerations to Future Wireless Networks Bader Al-Manthari, Nidal Nasser, and Hossam Hassanein IEEE Transactions on.
Capacity Enhancement with Relay Station Placement in Wireless Cooperative Networks Bin Lin1, Mehri Mehrjoo, Pin-Han Ho, Liang-Liang Xie and Xuemin (Sherman)
Yschen, CSIE, CCU1 Chapter 5: The Cellular Concept Associate Prof. Yuh-Shyan Chen Dept. of Computer Science and Information Engineering National Chung-Cheng.
Multiple Frequency Reuse Schemes in the Two-hop IEEE j Wireless Relay Networks with Asymmetrical Topology Weiwei Wang a, Zihua Guo b, Jun Cai c,
Multicast Recipient Maximization in IEEE j WiMAX Relay Networks Wen-Hsing Kuo † ( 郭文興 ) & Jeng-Farn Lee ‡ ( 李正帆 ) † Department of Electrical Engineering,
Joint Base Station and Relay Station Placement for IEEE j Networks Hsiao-Chen Lu and Wanjiun Liao Department of Electrical Engineering, National.
Doc.: IEEE / Submission March 2013 Juho Pirskanen, Renesas Mobile CorporationSlide 1 Discussion On Basic Technical Aspects for HEW Date:
Cooperative Resource Management in Cognitive WiMAX with Femto Cells Jin Jin, Baochun Li Department of Electrical and Computer Engineering University of.
Communication Protocol Engineering Lab. A Survey Of Converging Solutions For Heterogeneous Mobile IEEE Wireless Communication Magazine December 2014 Minho.
In the name of God.
By: Dr.Lway Faisal Abdulrazak
Impact of Interference on Multi-hop Wireless Network Performance
2010 IEEE Global Telecommunications Conference (GLOBECOM 2010)
Cost Effectively Deploying of Relay Stations (RS) in IEEE 802
Adv. Wireless Comm. Systems - Cellular Networks -
Wonkwang Shin, Byoung-Yoon Min and Dong Ku Kim
A glimpse into the future, looking beyond 2025
Ad-hoc Networks.
Ad hoc Data Dissemination in Vehicular Networks
An-Najah National University Mobile Wi-Max Network
Meisam Mirahsan, Carleton University, Ottawa, Canada
Backhaul-aware Robust 3D Drone Placement in 5G+ Wireless Networks
ECE 7930 Advanced Topics in Wireless Networks
Cellular Concepts المحاضرة السادسة 03/07/2015 Omar Abu-Ella.
Syed Hussain Ali, Member, IEEE Victor C. M. Leung, Fellow, IEEE
Month Year doc.: IEEE yy/xxxxr0 November 2017
Chapter 3: Wireless WANs and MANs
Evaluation Model for LTE-Advanced
Dynamic Load Balancing and Channel Allocation in Indoor WLAN
Howard Huang, Sivarama Venkatesan, and Harish Viswanathan
Autonomous & Connected Vehicles
5G Micro Cell Deployment in Coexistence with Fixed Service
Royal Institute of Technology Dept. of Signals, Sensors and Systems
Month Year November 2018 November 2018
QoS Aware Adaptive Subcarrier Allocation in OFDMA Systems
TUT experience and vision
An overview of the IEEE Standard
MITP 413: Wireless Technologies Week 2
Hemant Kr Rath1, Anirudha Sahoo2, Abhay Karandikar1
IEEE Journal Papers – Under Review
doc.: IEEE yy/xxxxr0 Date:
Discussion on IMT-2020 mMTC and URLLC
Current Status of submission about EUHT
doc.: IEEE yy/xxxxr0 Date:
Channel usage in NGV: follow-up
Cellular Telephone Networks
IEEE Magazine Papers – under review
doc.: IEEE yy/xxxxr0 Date: September, 2019
Chrysostomos Koutsimanis and G´abor Fodor
Cellular Systems.
Presentation transcript:

with Backhaul Considerations Performance evaluation IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 User Association and Bandwidth Allocation for Terrestrial and Aerial Base Stations with Backhaul Considerations Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion Elham Kalantari*, Irem Bor-Yaliniz**, Abbas Yongacoglu*, and Halim Yanikomeroglu** *School of Electrical Engineering and Computer Science, University of Ottawa, Canada **Department of Systems and Computer Engineering, Carleton University, Canada October 2017 E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Outline IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Introduction System model Proposed Algorithm Performance Evaluation Conclusion Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion E. Kalantari, M. Z. Shakir, H. Yanikomeroglu, and A. Yongacoglu E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Different Applications of Drones IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Military Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion Agriculture Aerial Photography Product Delivery Recreational Applications E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Why Drone Base Stations? IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Terrestrial base stations’ locations is determined based on the long term average traffic. However temporal and spatial variations in user densities and user application rates are expected to result in difficult-to-predict traffic patterns. supply and demand mismatch. To increase the agility and flexibility of the network, DRONES can be integrated into the wireless network as flying base stations.  Bring supply wherever and whenever the demand is. Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Various Use Cases for Integration of Drone-BSs in Cellular Networks IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion - Temporary congestion issue - Remote areas - During aftermath of a disaster E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation When Supply and Demand Do Not Match in Space and Time IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion Can we store (in time) and/or transfer (in space) the supply? If difficult, then more heterogeneous + more unpredictable  more problems E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

When Supply and Demand Do Not Match in Space and Time IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion Can we store (in time) and/or transfer (in space) the supply? If difficult, then more heterogeneous + more unpredictable  more problems Ultra-Agile Infrastructure for Wireless Super-Connectivity E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Previous work in VTC 2016 IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Find the minimum number of drone-BSs and their 3D placement so that users with high data rates are served. * Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion Subject to: Drone-BSs can change their altitudes in order to tackle coverage and capacity issues. A drone-BS decreases its altitude in a dense area to reduce interference to the users that are not served by it and increases its altitude to cover a large area in a low density region. * Elham Kalantari, Halim Yanikomeroglu, and Abbas Yongacoglu, “On the number and 3D placement of drone base stations in wireless cellular networks”, IEEE Vehicular Technology Conference (VTC2016-Fall), 18–21 September 2016, Montreal, QC, Canada. E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Previous work in ICC 2017 IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Backhaul constraint is an important limitation in drone-BSs deployment. A drone-BS should have a wireless backhaul; therefore, the peak data rate a drone-BS can support is limited and it may dramatically decrease due to inclement weather conditions especially if the link is based on the FSO or mmWave technology. Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion Find the maximum number of weighted users so that the bandwidth, backhaul, and coverage constraints are satisfied for different rate requirements in a clustered user distribution.* * Elham Kalantari, Muhammad Zeeshan Shakir, Halim Yanikomeroglu, and Abbas Yongacoglu, “Backhaul-aware robust 3D drone placement in 5G+ wireless networks”, IEEE International Conference on Communications (ICC) 2017 – Workshop on Flexible Networks (FlexNets), 21 May 2017, Paris, France. E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Previous work in ICC 2017 IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Subject to: Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion network-centric user-centric E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Air-to-Ground Channel Model IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Excessive pathloss due to LoS or NLoS channel between TX and RX Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion Probability of LoS: P(LoS) increases as the elevation angle is increased. - A. Al-Hourani, S. Kandeepan, and A. Jamalipour, “Modeling air-to-ground path loss for low altitude platforms in urban environments,” in IEEE Global Communications Conference (GLOBECOM), Dec 2014, pp. 2898–2904. - A. Al-Hourani, S. Kandeepan, and S. Lardner, “Optimal LAP altitude for maximum coverage,” IEEE Wireless Communications Letters, vol. 3,no. 6, pp. 569–572, Dec 2014. E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Air-to-Ground Channel Model IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Problem Definition IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 We assume downlink wireless HetNet including two tiers of BSs, an MBS and a number of DBSs. Wireless Backhaul is not fixed unlike the previous work. In-band wireless backhaul is employed for DBSs and the MBS is utilized as a hub to connect DBSs to the network. Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion ITU classifications of 5G services: Enhanced mobile broadband (eMBB), Massive machine-type communications (mMTC), Ultra reliable and low latency communications (uRLLC). URLLC users with delay-sensitive applications co-exist with regular eMBB users. The mobility of the DBSs and different types of users require that the following key issues are considered to provide wireless services efficiently: Finding the locations of DBSs, Determining the user-BS associations with consideration to user type, Bandwidth allocation for access and backhaul links. E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Shared backhaul with access side of drone-BS Bandwidth allocation Backhaul spectrum Dedicated backhaul Shared backhaul with access side of drone-BS Self-Interference IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 The whole available bandwidth Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion α 1-α Backhaul side of DBSs Access side of DBSs and the MBS To avoid self-interference, orthogonal frequency channels in the backhaul and access side of the DBSs is employed. Bandwidth is shared between the access side of the MBS and DBSs. E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Problem Constraints PIMRC 2017 Association with only one BS IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Association with only one BS Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion Total available bandwidth Backhaul constraint for DBSs Delay-sensitive and delay-tolerant users The DBS user should be in coverage footprint of the DBS Minimum distance to avoid interference E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Problem Formulation IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Logarithmic utility function is assumed to consider fairness; therefore, Subject to: Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion Equal resource allocation is the optimal allocation for the logarithmic utility; therefore, E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Proposed algorithm IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 The procedure includes three main processes: 1- The user-BS association problem can be written as a convex sub problem for a fixed and locations of DBSs. Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion (a) 2- For fixed s (after rounding them), the convex master problem that finds can be solved. (b) 3- Locations of DBSs are updated using PSO algorithm. (c) E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Flowchart for the proposed algorithm IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Start Find initial placements for DBSs Assume an initial value for Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion P.15 (c) P.15 (a) Find 3D locations of DBSs by PSO algorithm Find the association indicators, round them, find the utility function P.15 (b) Update , update the utility function Is convergence achieved? No No Yes Is convergence achieved? Yes End E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Simulation Assumptions IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion Antenna gain for drone-BSs: E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Simulation Results IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion The heterogeneity of the users distribution is measured by the coefficient of variation (CoV) of the Voronoi area of the users. In a more clustered distribution, the probability that each user receives a higher rate increases. This confirms that the proposed algorithm can increase the performance of the cellular network in terms of users’ satisfactions in more clustered distributions. E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Simulation Results IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 By increasing the CoV, more users could be associated with the DBSs which results in better load balancing in the system. Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion Increasing θB, increases the maximum possible coverage area. However, it also increases D, which means that to prevent overlapping, DBSs have to keep a larger distance between each other. Hence, the total capacity of users decreases, although the coverage radius increases with increasing θB. The effect of θB becomes more severe as the number of utilized DBSs increases. Therefore, it is necessary to develop efficient interference cancellation methods for dense deployments of DBSs, since preventing overlaps between DBSs causes significant performance loss. E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Conclusion IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Delay-sensitive users are associated with the MBS, while delay-tolerant users can be associated with either one of the BSs. As all the DBSs share the same bandwidth, using directional antennas is proposed to relieve the effect of the interference. User-BS association and wireless backhaul bandwidth allocation are found through a decomposition method and the locations of DBSs are updated using a PSO algorithm. Further insights is obtained on the effects of CoV and halfpower beamwidth by simulations. The results show that utilizing DBSs in cases where the users are clustered can increase total rate of the users associated with DBSs, despite depleting the resources. In order to prevent interference, overlaps of coverage areas of different DBSs are not allowed. However, the half-power beamwidth should be chosen carefully for these scenarios, as the results show that increasing the beamwidth can decrease total rate by preventing DBSs to be deployed in beneficial locations. Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

Performance evaluation Under Review in WCNC 2018 IEEE International Symposium on Personal, Indoor and Mobile Radio Communications PIMRC 2017 Find 3D location of a drone-BS while the users move base on Reinforcement learning method. This method can bring much higher QoS to the network considering users’ movements. After giving the agent sufficient time to learn the environment, the processing time to find the optimum position of the drone-BS becomes really low; therefore, it is a promising approach that can keep the agility and flexibility of the future wireless networks. Outline Introduction System model Proposed Algorithm Performance evaluation Conclusion E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, and H. Yanikomeroglu PIMRC 2017

I. Bor-Yaliniz, HA. El-Keyi, Yanikomeroglu, “Spatial configuration of agile wireless networks with drone-BSs and user-iin-the-loop”, under review in IEEE Transactions on Wireless Communications, 2017. I. Bor-Yaliniz, H. Yanikomeroglu, “The new frontier in RAN heterogeneity: Multi-tier drone-cells”, IEEE Communications Magazine, November 2016. F. Lagum, I. Bor-Yaliniz, H. Yanikomeroglu, “Strategic densificationn with UAV-BSs for cellular networks”, under review in IEEE Wireless Communications Letters, 2017. R. Ghanavi, E. Kalantari, M. Sabbaghian, H. Yanikomeroglu, A. Yongacoglu, “Efficient 3D aerial base station considering users mobility by reinforcement learning ”, u/r in IEEE WCNC 2018. S. Andreev, V. Petrov, M. Dohler, H. Yanikomeroglu, “Future of ultra-dense networks beyond 5G: Harnessing heterogeneous moving cells”, under review in IEEE Communications Magazine, 2017. M. Gapeyenko, I. Bor-Yaliniz, S. Andreev, H. Yanikomeroglu, Y. Koucheryavy, “Effect of blockage in deploying mmWave drone base stations for beyond-5G networks”, u/r in IEEE WCNC 2018. I. Bor-Yaliniz, S.S. Szyszkowicz, H. Yanikomeroglu, "Environment aware drone-base-station placements in modern metropolitans”, under review in IEEE Wireless Communications Letters, 2017. E. Kalantari, I. Bor-Yaliniz, A. Yongacoglu, H. Yanikomeroglu, “User association and bandwidth allocation for terrestrial and aerial base stations with backhaul considerations”, IEEE PIMRC 2017.  M. Alzenad, M.Z. Shakir, H. Yanikomeroglu, M.-S. Alouini, “FSO-based vertical backhaul/fronthaul framework for 5G+ wireless networks”, under review in IEEE Communications Magazine, 2017. E. Kalantari, M.Z. Shakir, H. Yanikomeroglu, A. Yongacoglu, “Backhaul-aware robust 3D drone placement in 5G+ wireless networks”, IEEE ICC Workshops 2017. Routing, subchannel scheduling, and power allocation are generally treated as separate problems. They are mostly modeled using NLP to maximize either sum rate or minimum rate. Although separation of problems simplifies modeling, it degrades network efficiency, Low sum rate Low minimum rate. M. Alzenad, A. El-Keyi, H. Yanikomeroglu, “3D placement of an unmanned aerial vehicle BS for maximum coverage of users with different QoS requirements”, IEEE Wireless Commun Letters, 2017. E. Kalantari, H. Yanikomeroglu, A. Yongacoglu, “On the number and 3D placement of drone base stations in wireless cellular networks”, IEEE Vehicular Technology Conference (VTC2016-Fall). M. Alzenad, A. El-Keyi, F. Lagum, H. Yanikomeroglu, “3D placement of unmanned aerial vehicle base station (UAV-BS) for energy-efficient maximal coverage”, IEEE Wireless Communications Letters, Aug 2017. I. Bor Yaliniz, A. El-Keyi, H. Yanikomeroglu, “Efficient 3-D placement of an aerial base station in next generation cellular networks”, IEEE ICC 2016.