Tier-Aware Resource Allocation in OFDMA Macrocell-Small Cell Networks
- 2 February 2015
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Communications
- Vol. 63 (3), 695-710
- https://doi.org/10.1109/tcomm.2015.2397888
Abstract
We present a joint sub-channel and power allocation framework for downlink transmission in an orthogonal frequency-division multiple access (OFDMA)-based cellular network composed of a macrocell overlaid by small cells. In this framework, the resource allocation (RA) problems for both the macrocell and small cells are formulated as optimization problems. For the macrocell, we formulate an RA problem that is aware of the existence of the small cell tier. In this problem, the macrocell performs RA to satisfy the data rate requirements of macro user equipments (MUEs) while maximizing the tolerable interference from the small cell tier on its allocated sub-channels. Although the RA problem for the macrocell is shown to be a mixed integer nonlinear problem (MINLP), we prove that the macrocell can solve another alternate optimization problem that will yield the optimal solution with reduced complexity. For the small cells, following the same idea of tier-awareness, we formulate an optimization problem that accounts for both RA and admission control (AC) and aims at maximizing the number of admitted users while simultaneously minimizing the consumed bandwidth. Similar to the macrocell optimization problem, the small cell problem is shown to be an MINLP. We obtain a sub-optimal solution to the MINLP problem relying on convex relaxation. In addition, we employ the dual decomposition technique to have a distributed solution for the small cell tier. Numerical results confirm the performance gains of our proposed RA formulation for the macrocell over the traditional resource allocation based on minimizing the transmission power. Besides, it is shown that the formulation based on convex relaxation yields a similar behavior to the MINLP formulation. Also, the distributed solution converges to the same solution obtained by solving the corresponding convex optimization problem in a centralized fashion.Keywords
Funding Information
- NSERC Strategic Grant (STPGP 430285-12)
- National Research Foundation of Korea (NRF)
- Korean Government (MSIP) (2014R1A5A1011478, 2013R1A2A2A01067195)
This publication has 41 references indexed in Scilit:
- On the Complexity of Joint Subcarrier and Power Allocation for Multi-User OFDMA SystemsIEEE Transactions on Signal Processing, 2013
- LTE release 12 and beyond [Accepted From Open Call]IEEE Communications Magazine, 2013
- Dynamic Power Allocation for Downlink Interference Management in a Two-Tier OFDMA NetworkIEEE Transactions on Vehicular Technology, 2013
- Multiuser Resource Allocation Optimization Using Bandwidth-Power Product in Cognitive Radio NetworksIEEE Journal on Selected Areas in Communications, 2013
- Distributed SC-FDMA Resource Allocation Algorithm Based on the Hungarian MethodPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2009
- Dual methods for nonconvex spectrum optimization of multicarrier systemsIEEE Transactions on Communications, 2006
- Optimal Resource Allocation for OFDMA Downlink SystemsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2006
- Fundamentals of Wireless CommunicationPublished by Cambridge University Press (CUP) ,2005
- Cochannel Interference Mitigation and Cooperative Processing in Downlink Multicell Multiuser MIMO NetworksEURASIP Journal on Wireless Communications and Networking, 2004
- An efficient multiuser loading algorithm for OFDM-based broadband wireless systemsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002