Power control and resource allocation for capacity improvement in picocell downlinks

In this paper we study the power control of multiuser orthogonal frequency division multiplexing (OFDM) transmissions in a heterogeneous network which features macro user equipments (MUEs) and pico user equipments (PUEs) sharing the same resource blocks (RBs) during downlink. We aim to maximize the sum capacity of PUEs while meeting the performance constraints of MUEs. Because of mutual interference caused by RB reuse, the transmission power of every RB is to be individually controlled, leading to a more complex problem of resource allocation and power control optimization. Our proposed approach is to first reformulate the original mixed integer programming problem into a convex power control problem by dropping the allocation variables. Secondly, we propose a fast and effective power control algorithm to solve the convex problem by exploiting the Karush-Kuhn-Tucker conditions of power control. Finally, we propose a suboptimal resource allocation scheme and present numerical results for performance evaluation.

[1]  Adrish Banerjee,et al.  Power and subcarrier allocation for OFDMA femto-cell based underlay cognitive radio in a two-tier network , 2011, 2011 IEEE 5th International Conference on Internet Multimedia Systems Architecture and Application.

[2]  Fan Zhang,et al.  Resource Allocation for Delay Differentiated Traffic in Multiuser OFDM Systems , 2006, IEEE Transactions on Wireless Communications.

[3]  Timothy A. Thomas,et al.  LTE-advanced: next-generation wireless broadband technology [Invited Paper] , 2010, IEEE Wireless Communications.

[4]  Jeffrey G. Andrews,et al.  Femtocell networks: a survey , 2008, IEEE Communications Magazine.

[5]  T. Aaron Gulliver,et al.  Graph coloring based spectrum allocation for femtocell downlink interference mitigation , 2011, 2011 IEEE Wireless Communications and Networking Conference.

[6]  F. Richard Yu,et al.  Dynamic Resource Allocation for Heterogeneous Services in Cognitive Radio Networks With Imperfect Channel Sensing , 2012, IEEE Trans. Veh. Technol..

[7]  Yuan Wu,et al.  Distributed Power Allocation Algorithm for Spectrum Sharing Cognitive Radio Networks with QoS Guarantee , 2009, IEEE INFOCOM 2009.

[8]  Peng Gong,et al.  Radio Resource Management with Proportional Rate Constraint in the Heterogeneous Networks , 2012, IEEE Transactions on Wireless Communications.

[9]  Dong-Ho Cho,et al.  A joint power and subchannel allocation scheme maximizing system capacity in dense femtocell downlink systems , 2009, 2009 IEEE 20th International Symposium on Personal, Indoor and Mobile Radio Communications.

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

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

[12]  Neal Patwari,et al.  Channel Sounding for the Masses: Low Complexity GNU 802.11b Channel Impulse Response Estimation , 2010, IEEE Transactions on Wireless Communications.

[13]  NITIN MANGALVEDHE,et al.  LTE-ADVANCED : NEXT-GENERATION WIRELESS BROADBAND , 2010 .

[14]  Mengyao Ge,et al.  Fast Optimal Resource Allocation is Possible for Multiuser OFDM-Based Cognitive Radio Networks with Heterogeneous Services , 2012, IEEE Transactions on Wireless Communications.