Centralized Power Allocation for Interference Limited Networks

The goal of our work is to limit in-band inter-cell interference in wireless communication cellular systems. Based on interference classification techniques, we propose a novel centralized inter-cell power allocation algorithm which computes the minimum power budget required in each cell to meet its local quality of service (QoS) constraints. Both analytical and numerical results applied to cellular networks show how our algorithm permits to notably reduce both power budget and harmful effects of in-band inter-cell interference, while meeting QoS constraints of users in each cell.

[1]  A. Gjendemsjo,et al.  Optimal Power Allocation and Scheduling for Two-Cell Capacity Maximization , 2006, 2006 4th International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks.

[2]  Andrea J. Goldsmith,et al.  Adaptive coded modulation for fading channels , 1998, IEEE Trans. Commun..

[3]  Mérouane Debbah,et al.  Opportunistic interference alignment in MIMO interference channels , 2008, 2008 IEEE 19th International Symposium on Personal, Indoor and Mobile Radio Communications.

[4]  David Tse,et al.  Fundamentals of Wireless Communication , 2005 .

[5]  Masoud Salehi,et al.  Multiple access channels with arbitrarily correlated sources , 1980, IEEE Trans. Inf. Theory.

[6]  Sriram Vishwanath,et al.  Generalized Degrees of Freedom of the Symmetric Gaussian $K$ User Interference Channel , 2010, IEEE Transactions on Information Theory.

[7]  Amir K. Khandani,et al.  Capacity bounds for the Gaussian Interference Channel , 2008, 2008 IEEE International Symposium on Information Theory.

[8]  Chi-Hsiao Yih,et al.  Centralized power allocation algorithms for OFDM cellular networks , 2003, IEEE Military Communications Conference, 2003. MILCOM 2003..

[9]  Hua Wang,et al.  Gaussian Interference Channel Capacity to Within One Bit , 2007, IEEE Transactions on Information Theory.

[10]  Syed Ali Jafar,et al.  Exploiting Channel Correlations - Simple Interference Alignment Schemes with No CSIT , 2009, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[11]  Loïc Brunel,et al.  Soft-input soft-output lattice sphere decoder for linear channels , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

[12]  Yikang Xiang,et al.  Inter-cell Interference Mitigation through Flexible Resource Reuse in OFDMA based Communication Networks , 2007 .

[13]  Syed Ali Jafar,et al.  Approaching the Capacity of Wireless Networks through Distributed Interference Alignment , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

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

[15]  Te Sun Han,et al.  A new achievable rate region for the interference channel , 1981, IEEE Trans. Inf. Theory.

[16]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[17]  Daniel Pérez Palomar,et al.  Power Control By Geometric Programming , 2007, IEEE Transactions on Wireless Communications.

[18]  Aydano B. Carleial,et al.  A case where interference does not reduce capacity (Corresp.) , 1975, IEEE Trans. Inf. Theory.

[19]  Stephen P. Boyd,et al.  Optimal power control in interference-limited fading wireless channels with outage-probability specifications , 2002, IEEE Trans. Wirel. Commun..