Interference management for energy saving in Heterogeneous Networks

In this paper, we study how to save energy in Heterogeneous Networks (HetNets), which is introduced to the next generation cellular systems. A HetNet based cellular system consists of a mix of macrocells and low power nodes, such as picocells, femtocells and relays, making the systematic power controlling more complex than the conventional ones. The major difficulty for power control in HetNets is the mutual interference among cells with different transmission power. So interference management is very important for the next generation cellular networks. We try to minimize the total power consumption while guaranteeing users' rate requirements, to save energy and keep the user's QoS from degenerating. Our general problem formulation leads to a nonconvex optimization problem which is generally hard to solve. We derive the lower bound of user's achievable rates with given power consumption and develop an efficient iterative algorithm to deal with the intractable optimization task. Numerical results show that our proposed algorithm performs well for practical wireless scenarios.

[1]  Zhouyue Pi,et al.  An introduction to millimeter-wave mobile broadband systems , 2011, IEEE Communications Magazine.

[2]  Rui Chang,et al.  Interference coordination and cancellation for 4G networks , 2009, IEEE Communications Magazine.

[3]  Romeo Giuliano,et al.  WiMAX fractional frequency reuse for rural environments , 2008, IEEE Wireless Communications.

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

[5]  Ismail Güvenç,et al.  Capacity and Fairness Analysis of Heterogeneous Networks with Range Expansion and Interference Coordination , 2011, IEEE Communications Letters.

[6]  Robert W. Heath,et al.  Is the PHY layer dead? , 2011, IEEE Communications Magazine.

[7]  Luc Vandendorpe,et al.  Iterative Resource Allocation for Maximizing Weighted Sum Min-Rate in Downlink Cellular OFDMA Systems , 2011, IEEE Transactions on Signal Processing.

[8]  Jamie S. Evans,et al.  Low-Complexity Distributed Algorithms for Spectrum Balancing in Multi-User DSL Networks , 2006, 2006 IEEE International Conference on Communications.

[9]  Gpp 3G Home NodeB Study Item Technical Report , 2008 .

[10]  Andrea J. Goldsmith,et al.  Variable-rate variable-power MQAM for fading channels , 1997, IEEE Trans. Commun..

[11]  Wei Yu,et al.  Dual methods for nonconvex spectrum optimization of multicarrier systems , 2006, IEEE Transactions on Communications.