Syed Hussain Ali, Member, IEEE Victor C. M. Leung, Fellow, IEEE

Slides:



Advertisements
Similar presentations
Mobility Increase the Capacity of Ad-hoc Wireless Network Matthias Gossglauser / David Tse Infocom 2001.
Advertisements

VSMC MIMO: A Spectral Efficient Scheme for Cooperative Relay in Cognitive Radio Networks 1.
May 4, Mobile Computing COE 446 Network Planning Tarek Sheltami KFUPM CCSE COE Principles of Wireless.
2005/12/06OPLAB, Dept. of IM, NTU1 Optimizing the ARQ Performance in Downlink Packet Data Systems With Scheduling Haitao Zheng, Member, IEEE Harish Viswanathan,
Kuang-Hao Liu et al Presented by Xin Che 11/18/09.
1 Cross-Layer Design for Wireless Communication Networks Ness B. Shroff Center for Wireless Systems and Applications (CWSA) School of Electrical and Computer.
Introduction to Cognitive radios Part two HY 539 Presented by: George Fortetsanakis.
EE360: Lecture 15 Outline Cellular System Capacity
Cellular System Capacity Maximum number of users a cellular system can support in any cell. Can be defined for any system. Typically assumes symmetric.
Opportunistic Transmission Scheduling With Resource-Sharing Constraints in Wireless Networks From IEEE JOURNAL ON SELECTED AREAS IN COMMUNCATIONS Presented.
COGNITIVE RADIO FOR NEXT-GENERATION WIRELESS NETWORKS: AN APPROACH TO OPPORTUNISTIC CHANNEL SELECTION IN IEEE BASED WIRELESS MESH Dusit Niyato,
College of Engineering Resource Management in Wireless Networks Anurag Arepally Major Adviser : Dr. Robert Akl Department of Computer Science and Engineering.
Seyed Mohamad Alavi, Chi Zhou, Yu Cheng Department of Electrical and Computer Engineering Illinois Institute of Technology, Chicago, IL, USA ICC 2009.
MAXIMIZING SPECTRUM UTILIZATION OF COGNITIVE RADIO NETWORKS USING CHANNEL ALLOCATION AND POWER CONTROL Anh Tuan Hoang and Ying-Chang Liang Vehicular Technology.
Network diversity in broadband wireless system ONR workshop 2003 Hui Liu Department of Electrical Engineering University of Washington.
POWER CONTROL IN COGNITIVE RADIO SYSTEMS BASED ON SPECTRUM SENSING SIDE INFORMATION Karama Hamdi, Wei Zhang, and Khaled Ben Letaief The Hong Kong University.
12. Feb.2010 | Christian Müller Distributed Resource Allocation in OFDMA-Based Relay Networks Christian Müller.
Orthogonal Frequency Division Multiple Access (OFDMA)
Suk-Bok Lee, Ioannis Pefkianakis, Adam Meyerson, Shugong Xu, Songwu Lu
1 11 Subcarrier Allocation and Bit Loading Algorithms for OFDMA-Based Wireless Networks Gautam Kulkarni, Sachin Adlakha, Mani Srivastava UCLA IEEE Transactions.
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.
報告人:陳柏偉 日期: 指導老師:林永松.  ABSTRACT  INTRODUCTION  MODEL FOR ELASTIC TRAFFIC  INTERFERENCE COORDINATION SCHEMES  SELF-ORGANIZING INTERFERENCE.
Philipp Hasselbach Capacity Optimization for Self- organizing Networks: Analysis and Algorithms Philipp Hasselbach.
Performance evaluation of adaptive sub-carrier allocation scheme for OFDMA Thesis presentation16th Jan 2007 Author:Li Xiao Supervisor: Professor Riku Jäntti.
Fen Hou and Pin-Han Ho Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, Ontario Wireless Communications and Mobile.
User Cooperation via Rateless Coding Mahyar Shirvanimoghaddam, Yonghui Li, and Branka Vucetic The University of Sydney, Australia IEEE GLOBECOM 2012 &
Wireless Mobile Communication and Transmission Lab. Chapter 8 Application of Error Control Coding.
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.
Multiuser OFDM with Adaptive Subcarrier, Bit and Power Allocation (IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 17, NO. 10, OCTOBER 1999)
Joint Scheduling and Power Control for Wireless Ad Hoc Networks Advisor: 王瑞騰 Student: 黃軍翰.
Performance Analysis of OFDM Systems with Adaptive Sub Carrier Bandwidth Suvra S. Das, Student Member, IEEE, Elisabeth De Carvalho, Member, IEEE, and Ramjee.
OFDMA Based Two-hop Cooperative Relay Network Resources Allocation Mohamad Khattar Awad, Xuemin (Sherman) Shen Student Member, IEEE Senior Member, IEEE.
Downlink Scheduling With Economic Considerations to Future Wireless Networks Bader Al-Manthari, Nidal Nasser, and Hossam Hassanein IEEE Transactions on.
1 11 Channel Assignment for Maximum Throughput in Multi-Channel Access Point Networks Xiang Luo, Raj Iyengar and Koushik Kar Rensselaer Polytechnic Institute.
X. Li, W. LiuICC May 11, 2003A Joint Layer Design Smart Contention Resolution Random Access Wireless Networks With Unknown Multiple Users: A Joint.
Transmit Power Adaptation for Multiuser OFDM Systems Jiho Jang, Student Member, IEEE, and Kwang Bok Lee, Member, IEEE IEEE JOURNAL ON SELECTED AREAS IN.
Overload Prediction Based on Delay in Wireless OFDMA Systems E. O. Lucena, F. R. M. Lima, W. C. Freitas Jr and F. R. P. Cavalcanti Federal University of.
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,
5: Capacity of Wireless Channels Fundamentals of Wireless Communication, Tse&Viswanath 1 5. Capacity of Wireless Channels.
Content caching and scheduling in wireless networks with elastic and inelastic traffic Group-VI 09CS CS CS30020 Performance Modelling in Computer.
Hard Handoff Scheme Exploiting Uplink and Downlink Signals in IEEE e Systems Sunghyun Cho, Jonghyung Kwun, Chihyun Park, Jung-Hoon Cheon, Ok-Seon.
Reuse Partitioning in Fixed Two-hop Cellular Relaying Network Reporter: Yi-Harn Lin Date: 2006/05/10.
Resource Allocation in Hospital Networks Based on Green Cognitive Radios 王冉茵
On Exploiting Diversity and Spatial Reuse in Relay-enabled Wireless Networks Karthikeyan Sundaresan, and Sampath Rangarajan Broadband and Mobile Networking,
Chance Constrained Robust Energy Efficiency in Cognitive Radio Networks with Channel Uncertainty Yongjun Xu and Xiaohui Zhao College of Communication Engineering,
An Orthogonal Resource Allocation Algorithm to Improve the Performance of OFDMA-based Cellular Wireless Systems using Relays Woonsik Lee, Minh-Viet Nguyen,
Joint Routing and Scheduling Optimization in Wireless Mesh Networks with Directional Antennas A. Capone, I. Filippini, F. Martignon IEEE international.
Cost Effectively Deploying of Relay Stations (RS) in IEEE 802
Introduction to Cognitive radios Part two
Presented by Tae-Seok Kim
Space-Time and Space-Frequency Coded Orthogonal Frequency Division Multiplexing Transmitter Diversity Techniques King F. Lee.
6. Opportunistic Communication and Multiuser Diversity
Cellular Concepts المحاضرة السادسة 03/07/2015 Omar Abu-Ella.
Sanam Sadr, Alagan Anpalagan and Kaamran Raahemifar
Chapter 3: Wireless WANs and MANs
Scheduling in Wireless Communication Systems
Scheduling Algorithms in Broad-Band Wireless Networks
Ian C. Wong, Zukang Shen, Jeffrey G. Andrews, and Brian L. Evans
Royal Institute of Technology Dept. of Signals, Sensors and Systems
Royal Institute of Technology Dept. of Signals, Sensors and Systems
Weihuang Fu1, Zhifeng Tao2, Jinyun Zhang2, and Dharma P. Agrawal1
QoS Aware Adaptive Subcarrier Allocation in OFDMA Systems
Qingwen Liu, Student Member, IEEE Xin Wang, Member, IEEE,
Adaptive Resource Allocation in Multiuser OFDM Systems
Presented By Riaz (STD ID: )
Ian C. Wong and Brian L. Evans ICASSP 2007 Honolulu, Hawaii
Link Performance Models for System Level Simulations in LC
Chrysostomos Koutsimanis and G´abor Fodor
Presentation transcript:

Dynamic Frequency Allocation in Fractional Frequency Reused OFDMA Networks Syed Hussain Ali, Member, IEEE Victor C. M. Leung, Fellow, IEEE University of British Columbia, Vancouver, Canada TWC 2009 1 1

Outline Introduction System Architecture and Model Problem Formulation Proposed Solution Numerical Results and Discussion Conclusion 2 2

Introduction OFDMA allows dynamic assignment of channels/subcarriers to different users at different time instances Dynamic subcarrier assignments (DSA) to multiple users improve the system data rate of an OFDMA system This improvement is due to the multiuser diversity gain as the channel characteristics for different users are independent of one another In systems where adaptive modulation and coding (AMC) techniques are employed, a better channel response results in a higher data rate

Equally Distribute Power In principle, allocating different power levels to individual subcarriers should improve performance Previous studies [6] and [7] have shown that the performance improvements are marginal [7]: Users with the best channel gain for each subcarrier are selected and then transmit power is equally distributed among the subcarriers A simpler solution involving DSA with equal power per subcarrier is preferred over more complex joint DSA and APA solution [6] G. Song and Y. G. Li, “Cross-layer optimization for OFDM wireless networks—part I: theoretical framework," IEEE Trans. Wireless Commun. 2005. [7] J. Jang and K. B. Lee, “Transmit power adaptation for multiuser OFDM systems," IEEE J. Select. Areas Commun. 2003

Frequency Reuse Factor of 1 is Better [13] reported large performance losses due to the frequency reuse schemes and suggested a frequency reuse factor of 1 [13]: A fractional loaded 1-reuse, with admission control or blocking, is a better alternative than a 3-reuse Our proposed scheme dynamically assigns carriers to different regions, allocates them to different users and maintains a frequency reuse factor of 1 Subcarriers are assigned to a user depends on the signal-to-interference-noise ratio (SINR) of the subcarrier and the fairness requirements of the users [13] “Downlink inter-cell interference co-ordination/avoidance evaluation of frequency reuse," 3GPP TSG-RAN WG1 Contribution, Tech. Rep. R1-061374, May 2006. [Online]. Available: http://www.3gpp.org/ftp/tsg_ran/WG1_RL1/TSGR1_45/Docs/R1-061374.zip

Static FFR Scheme (1) Fractional frequency reuse (FFR) scheme partitions the cell surface into two distinct geographical regions: Inner cell area users present in this cell area is called the super group Outer cell area near the cell edge users located in this cell area is called the regular group We identify the original FFR as the static FFR scheme

Static FFR Scheme (2) Shortcomings of static FFR scheme It divides users in two groups on the basis of static distance or SINR thresholds The trunking gain is reduced because only a fraction of the total cell population is part of a group It partitions the available subcarriers randomly into the groups The subcarrier partitioning does not consider their radio channel states We feel that FFR could benefit if only users in a cell are virtual members of both the groups This way the users will be able to get access to the subcarriers of both groups and result in increased trunking gain

Objective The objective of this research is to improve the long-term system data rate of a downlink OFDMA multicell network by intelligently distributing and allocating subcarriers first among geographical locations of cells and later, within a cell, among users We assume that the cell power is equally distributed among the subcarriers We propose a dynamic FFR cell architecture Subcarriers are dynamically partitioned among geographical locations by radio network controller (RNC) The BS schedules those subcarriers to the users opportunistically

Proposed Dynamic FFR Both user groups (super and regular) cover the whole cell surface. All users of a cell are virtual members of both groups The subcarriers assigned to the super and the sectors within the regular groups are orthogonal

System Model (1) We consider K-cell OFDMA cellular network and A central radio network controller (RNC) manages the K BSs Let Υk denote the set of users and be the number of users in a cell k is the total number of users is the set of all users in the network Assume that each cell is partitioned into L sectors where l identifies a particular sector denotes the set of users and is the number of users in a sector l of a cell k represents the total number of users in the lth sector of all cells

System Model (2) Let N be the number of subcarriers available Csup and Creg be the set of subcarriers assigned to the super and regular groups, respectively be the set of subcarriers allocated to a sector l be the set of interferers for a user in the super group and a sector l of the regular group, respectively For a 19-cell grid, there are 18 and 7 interferers experienced by the super and regular group users, respectively

Example The set of interferers for a user in sector A of cell 1 includes all the adjacent cells in the super group cells numbered {5, 6, 13, 14, 15, 16, 17} in the regular group setting

Channel and Data Rate Models (1) The channel gain for a user i on a subcarrier j from the serving BS k is given by where are path loss at distance r, shadowing and fading coefficient, respectively The corresponding SINR is given as where N0 is the noise power spectral density, △f is the subcarrier spacing, P is the power per subcarrier, Q is the set of interferers for the super group for the regular group sector l

Channel and Data Rate Models (2) Employing continuous rate adaptation, the SINR is mapped to data rate as follows: λ is a constant related to the target bit error rate (BER) as △f is the subcarrier spacing Ri,j is the achievable data rate by the ith user and jth subcarrier pair RNC algorithm employs average whereas the BS uses instantaneous values of these achievable rates A subcarrier j which falls within the regular group will have achievable data rate for user i identifies the achievable data rate of subcarrier j in the super group

Problem Formulation (1) The DSA objective is to maximize the system data rate while satisfying individual users lower data rate requirements Let be the binary decision variable, that is, When this variable is 1, it signals that the subcarrier j is assigned to the user i and belongs to the super group of subcarriers When its complement , it signals that the subcarrier j is assigned to the user i and it falls in the regular group of subcarriers The super and regular group subcarriers are orthogonal i.e.,

Problem Formulation (2) The joint DSA solves the following binary integer program for every scheduling time slot t where Ci be the lower bounds on data rates for user i A subcarrier can be assigned to only one user in a cell If a subcarrier j is assigned to the super group in one cell then this subcarrier should be reused in all the cells Similar reuse constraints for the regular group subcarriers

Proposed Solution We decompose the joint problem into two parts The first part is solved by a central location, like RNC which computes the membership of subcarriers in the super group or a sector within the regular group RNC DSA requires average achievable rates information for all user subcarrier pairs in the super and regular group settings The second part operates at the BS level and allocates subcarriers to the users BS DSA requires instantaneous data rate information for all user subcarrier pairs

RNC DSA Algorithm

BS DSA Algorithm (1) The RNC algorithm forwards the subcarrier assignments to every BS The BS DSA employs the minimum performance guarantee (MPG) opportunistic scheduling rule of [18] We define as the average data rate of user i up to time T where x represents the decisions made by the BS scheduler where are binary integer variables which signal the corresponding allocation decisions of the scheduler at a time slot t [18] X. Liu, E. K. P. Chong, and N. B. Shroff, “A framework for opportunistic scheduling in wireless networks," Computer Networks, vol. 41, no. 4, pp. 451-474, Mar. 2003

BS DSA Algorithm (2) is the average cell data rate where The MPG problem can be written as For the assignment of the super group subcarriers, j ∈ Csup, the algorithm finds the user i∗ that satisfies the following expression at every scheduling slot t The true controlling parameters in the above solutions are chosen such that for all i, E (Ri(x)) ≥ Ci for all i, and if E (Ri(x)) > Ci then Employing stochastic approximation techniques , the true values of βi can be estimated in real time as follows where is a small positive real number

Simulation Parameters We compare the proposed DSA algorithm with Full frequency reuse with full interference (FFFI) Conventional sectored Static FFR allocations All the four schemes considered have a frequency reuse factor of 1 The number of users, the cell dimensions, and the BS locations remain the same for the 100 super-frames User locations vary according to the random walk mobility model

Difference among Algorithms The algorithms differ in terms of the RNC DSA For FFFI, all the subcarriers are available for allocation to all the BSs in the grid with full inter-cell interference without any sectoring For the conventional sector allocation, RNC randomly selects a subset of the subcarriers for a sector. This subset is repeated in the same sector of all the cells The static FFR scheme divides users according to a distance threshold from the serving BS The users within 70 percent of the cell radius are considered members of the super group The remaining users are members of the regular group which is divided in 3 sectors The BS part of all the four allocation schemes is based on the MPG opportunistic scheduling

Comparison of Proposed DSA as a Function of Cell Radius

CDF of Achieved Data Rates and Lower Bounds

Cell Edge Throughput (1)

Cell Edge Throughput (2)

Conclusion We propose a new dynamic fractional frequency reused system architecture where a cell surface is virtually partitioned into two regions The first region is called super group, and the user-subcarrier pairs in this group experience interference from all the neighboring cells The second region is called the regular group which is physically partitioned into sectors and experiences reduced interference Both groups include all the cell users which results in increased trunking gain The proposed DSA scheme consists of two algorithms The first algorithm runs at the RNC and allocates subcarriers to the groups The second algorithm runs at every BS where opportunistic scheduling decisions are made and subcarriers are assigned to the users For small to medium cell, the proposed scheme outperforms the traditional schemes