Joint resource allocation and admission control in OFDMA-based multi-tier cellular networks

We present a joint resource allocation (RA) and admission control (AC) framework for an orthogonal frequency-division multiple access (OFDMA)-based cellular network composed of a macrocell overlaid by small cells. In this framework, the resource allocation problems for both the macrocell and small cells are formulated as optimization problems. The macrocell RA problem is aware of the existence of the small cell tier. On the other hand, the RA and AC problems for the small cells aim at maximizing the number of admitted users while simultaneously minimizing the consumed bandwidth. These optimization problems are shown to be mixed integer nonlinear problems (MINLPs). Techniques are proposed to obtain either the optimal solution or a bound on the optimal solution with reduced complexity through convex relaxation. Dual decomposition technique is also used to have a distributed solution for the small cell tier. Numerical results confirm that the convex relaxations follow a similar behavior to the MINLP formulations. Also, the distributed solution converges to the optimal solution obtained by solving the corresponding convex optimization problem in a centralized fashion.

[1]  Khaled Ben Letaief,et al.  Multiuser OFDM with adaptive subcarrier, bit, and power allocation , 1999, IEEE J. Sel. Areas Commun..

[2]  3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Evolved Universal Terrestrial Radio Access (e-utra); Further Advancements for E-utra Physical Layer Aspects (release 9) , 2022 .

[3]  Ekram Hossain,et al.  Evolution toward 5G multi-tier cellular wireless networks: An interference management perspective , 2014, IEEE Wireless Communications.

[4]  Ravikumar Balakrishnan,et al.  Traffic-Aware QoS Provisioning and Admission Control in OFDMA Hybrid Small Cells , 2014, IEEE Transactions on Vehicular Technology.

[5]  Matti Latva-aho,et al.  Joint admission control & interference avoidance in self-organized femtocells , 2010, 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers.

[6]  Dong In Kim,et al.  Clustering and Resource Allocation for Dense Femtocells in a Two-Tier Cellular OFDMA Network , 2014, IEEE Transactions on Wireless Communications.

[7]  Wayne L. Winston.  Operations research: applications and algorithms / Wayne L. Winston , 2004 .

[8]  Chintha Tellambura,et al.  Joint Bandwidth and Power Allocation With Admission Control in Wireless Multi-User Networks With and Without Relaying , 2010, IEEE Transactions on Signal Processing.

[9]  Yung Yi,et al.  REFIM: A Practical Interference Management in Heterogeneous Wireless Access Networks , 2011, IEEE Journal on Selected Areas in Communications.

[10]  Ekram Hossain,et al.  Resource allocation for spectrum underlay in cognitive radio networks , 2008, IEEE Transactions on Wireless Communications.

[11]  Junyi Li,et al.  Network densification: the dominant theme for wireless evolution into 5G , 2014, IEEE Communications Magazine.

[12]  Steffen Rebennack,et al.  Ellipsoid Method , 2009, Encyclopedia of Optimization.

[13]  Mohammed Nafie,et al.  Admission and Power Control for Spectrum Sharing Cognitive Radio Networks , 2011, IEEE Transactions on Wireless Communications.

[14]  Tho Le-Ngoc,et al.  Power allocation in wireless multi-user relay networks , 2009, IEEE Transactions on Wireless Communications.

[15]  Mérouane Debbah,et al.  Slow admission and power control for small cell networks via distributed optimization , 2013, 2013 IEEE Wireless Communications and Networking Conference (WCNC).

[16]  Stephen P. Boyd,et al.  Convex Optimization , 2004, Algorithms and Theory of Computation Handbook.

[17]  Jens Zander,et al.  Gradual removals in cellular PCS with constrained power control and noise , 1995, Proceedings of 6th International Symposium on Personal, Indoor and Mobile Radio Communications.

[18]  Long Bao Le,et al.  Fair Resource Allocation for OFDMA Femtocell Networks With Macrocell Protection , 2014, IEEE Transactions on Vehicular Technology.

[19]  Jonathan Currie,et al.  Opti: Lowering the Barrier Between Open Source Optimizers and the Industrial MATLAB User , 2012 .

[20]  Stephen P. Boyd,et al.  Notes on Decomposition Methods , 2008 .

[21]  Ioannis Mitliagkas,et al.  Joint Power and Admission Control for Ad-Hoc and Cognitive Underlay Networks: Convex Approximation and Distributed Implementation , 2011, IEEE Transactions on Wireless Communications.