Dynamic Frequency Allocation in Fractional Frequency Reused OFDMA Networks

1. 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

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

3. 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

4. Equally Distribute Power • In principle, allocating different power levels to individual subcarriersshould improve performance • Previous studies [6] and [7] haveshown 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

5. 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

6. 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

7. 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

8. 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

9. 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

10. System Model (1) • We consider K-cell OFDMA cellular network and A central radio network controller (RNC) manages the K BSs • Let Υkdenote 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

11. System Model (2) • Let Nbe the number of subcarriers available • Csupand Cregbe 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

12. 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

13. 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

14. 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

15. 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 supergroup of subcarriers • When its complement , it signals that the subcarrier j is assigned to the user i and it falls in the regulargroup of subcarriers • The super and regular group subcarriers are orthogonal • i.e.,

16. Problem Formulation (2) • The joint DSA solves the following binary integer program for every scheduling time slot t • where Cibe 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

17. 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

18. RNC DSA Algorithm

19. 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

20. 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)) ≥ Cifor all i, and if E (Ri(x)) > Cithen • Employing stochastic approximation techniques , the true values of βi can be estimated in real time as follows • where is a small positive real number

21. 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

22. 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

23. Comparison of Proposed DSA as a Function of Cell Radius

24. CDF of Achieved Data Rates and Lower Bounds

25. Cell Edge Throughput (1)

26. Cell Edge Throughput (2)

27. 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