Energy efficient power allocation scheme in heterogeneous cellular networks

The deployment of small-cell access points(SCAs) is widely acknowledged as a promising network densification way to satisfy the future capacity needs of 5G wireless cellular network. In this paper, we study the power allocation problem in heterogeneous downlink network while satisfying QoS constraints and power constraints simultaneously. The scheme is formulated as maximizing the system energy efficiency and then transformed into a tractable convex optimization problem. Utilizing multiflow RZF beamforming to reduce complexity, an iterative algorithm is proposed with provable convergence. Numerical results compare the proposed algorithm in different simulation parameters and show that increasing the number of SCAs, the antennas per SCA and users could enhance the total system energy efficiency.

[1]  Yongming Huang,et al.  Coordinated Multicell Multiuser Precoding for Maximizing Weighted Sum Energy Efficiency , 2014, IEEE Transactions on Signal Processing.

[2]  Yongbin Wei,et al.  A survey on 3GPP heterogeneous networks , 2011, IEEE Wireless Communications.

[3]  M Kobayashi,et al.  Green Small-Cell Networks , 2011, IEEE Vehicular Technology Magazine.

[4]  Mérouane Debbah,et al.  Massive MIMO in the UL/DL of Cellular Networks: How Many Antennas Do We Need? , 2013, IEEE Journal on Selected Areas in Communications.

[5]  Derrick Wing Kwan Ng,et al.  Energy-Efficient Resource Allocation in OFDMA Systems with Hybrid Energy Harvesting Base Station , 2013, IEEE Transactions on Wireless Communications.

[6]  Yongming Huang,et al.  Energy-Efficient Optimization for Downlink Massive MIMO FDD Systems With Transmit-Side Channel Correlation , 2016, IEEE Transactions on Vehicular Technology.

[7]  Yongming Huang,et al.  Decentralized Energy-Efficient Coordinated Beamforming for Multicell Systems , 2014, IEEE Transactions on Vehicular Technology.

[8]  Mérouane Debbah,et al.  Massive MIMO and small cells: How to densify heterogeneous networks , 2013, 2013 IEEE International Conference on Communications (ICC).

[9]  Jeffrey G. Andrews,et al.  Modeling and Analysis of K-Tier Downlink Heterogeneous Cellular Networks , 2011, IEEE Journal on Selected Areas in Communications.

[10]  I. Stancu-Minasian.  Nonlinear Fractional Programming , 1997 .

[11]  Emil Björnson,et al.  Optimal Resource Allocation in Coordinated Multi-Cell Systems , 2013, Found. Trends Commun. Inf. Theory.

[12]  Xinping Yi,et al.  User Scheduling for Heterogeneous Multiuser MIMO Systems: A Subspace Viewpoint , 2011, IEEE Transactions on Vehicular Technology.

[13]  Yongming Huang,et al.  Game Theoretic Max-logit Learning Approaches for Joint Base Station Selection and Resource Allocation in Heterogeneous Networks , 2015, IEEE Journal on Selected Areas in Communications.

[14]  Yongming Huang,et al.  Leakage-Aware Energy-Efficient Beamforming for Heterogeneous Multicell Multiuser Systems , 2014, IEEE Journal on Selected Areas in Communications.

[15]  Derrick Wing Kwan Ng,et al.  Energy-Efficient Resource Allocation in OFDMA Systems with Large Numbers of Base Station Antennas , 2012, IEEE Transactions on Wireless Communications.

[16]  Zhi-Quan Luo,et al.  Joint Base Station Clustering and Beamformer Design for Partial Coordinated Transmission in Heterogeneous Networks , 2012, IEEE Journal on Selected Areas in Communications.

[17]  Emil Björnson,et al.  Energy-efficient future wireless networks: A marriage between massive MIMO and small cells , 2015, 2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[18]  Emil Björnson,et al.  Massive MIMO and small cells: Improving energy efficiency by optimal soft-cell coordination , 2013, ICT 2013.

[19]  Jeffrey G. Andrews,et al.  Heterogeneous cellular networks: From theory to practice , 2012, IEEE Communications Magazine.

[20]  Jamie S. Evans,et al.  SCALE: A Low-Complexity Distributed Protocol for Spectrum Balancing in Multiuser DSL Networks , 2009, IEEE Transactions on Information Theory.