Abstract/Description
In this paper we determine the optimal fractional frequency reuse (FFR) and resource allocation in OFDMA system. Since the users at the cell edge are more exposed to inter-cell interference therefore each cell is partitioned into two regions; inner region and outer region. We determine the optimal FFR factor for the outer region, bandwidth assigned to each region and subcarrier and power allocation to all the users in the cell. The problem is formulated as sum-power minimization problem subject to minimum rate constraints in both the regions. This is a mixed linear integer programming problem which is relaxed into a convex optimization problem. We develop an efficient algorithm by using Lagrange dual decomposition theory at reasonable computational cost.
Keywords
Radio spectrum management, Resource management, Bandwidth, Computational efficiency, Frequency conversion, Downlink, Bit rate, Interference cancellation, Computational complexity, Interference constraints
Location
Eiffel 3
Session Theme
Networks - II
Session Type
Other
Session Chair
Dr. Sayeed Ghani
Start Date
16-9-2009 1:20 PM
End Date
16-8-2009 1:40 PM
Recommended Citation
Hassan, N. u., & Assaad, M. (2009). Networks - II: Optimal Fractional Frequency Reuse (FFR) and resource allocation in multiuser OFDMA system. International Conference on Information and Communication Technologies. Retrieved from https://ir.iba.edu.pk/icict/2009/2009/13
Networks - II: Optimal Fractional Frequency Reuse (FFR) and resource allocation in multiuser OFDMA system
Eiffel 3
In this paper we determine the optimal fractional frequency reuse (FFR) and resource allocation in OFDMA system. Since the users at the cell edge are more exposed to inter-cell interference therefore each cell is partitioned into two regions; inner region and outer region. We determine the optimal FFR factor for the outer region, bandwidth assigned to each region and subcarrier and power allocation to all the users in the cell. The problem is formulated as sum-power minimization problem subject to minimum rate constraints in both the regions. This is a mixed linear integer programming problem which is relaxed into a convex optimization problem. We develop an efficient algorithm by using Lagrange dual decomposition theory at reasonable computational cost.
