Asymptotic RZF cooperative beamforming algorithm based on energy efficiency

Yinghui ZHANG; Biao ZHANG; Xiaoting LU; Yang LIU

doi:10.11959/j.issn.1000-436x.2019174

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Asymptotic RZF cooperative beamforming algorithm based on energy efficiency

Correspondences | 更新时间：2024-06-05

- Asymptotic RZF cooperative beamforming algorithm based on energy efficiency
- Journal on Communications Vol. 40, Issue 10, Pages: 169-179(2019)
- 作者机构：
  
  内蒙古大学电子信息工程学院，内蒙古呼和浩特 010021
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(61761033);The Natural Science Foundation of Inner Mongolia Autonomous Region of China(2016MS0604)
- DOI：10.11959/j.issn.1000-436x.2019174
  CLC： TN929.5
- Online First：2019-10，
  
  Published：25 October 2019
- 稿件说明：
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Yinghui ZHANG, Biao ZHANG, Xiaoting LU, et al. Asymptotic RZF cooperative beamforming algorithm based on energy efficiency[J]. Journal on Communications, 2019, 40(10): 169-179.
DOI：

Yinghui ZHANG, Biao ZHANG, Xiaoting LU, et al. Asymptotic RZF cooperative beamforming algorithm based on energy efficiency[J]. Journal on Communications, 2019, 40(10): 169-179. DOI： 10.11959/j.issn.1000-436x.2019174.

摘要

在下行异构大规模MIMO系统中，针对目前多流正则化迫零波束成形算法将正则化项中的每根天线功率约束值均设为固定的上限，且忽略在实际部署环境中天线数量、用户数以及QoS等因素影响，设计的Multiflow-RZF波束成形并不能获得最佳能效的问题，提出一种低复杂度的渐进式RZF协作波束成形算法。该算法在每次迭代中，对天线功率约束集合进行最优选择，渐近地获得最优波束成形设计以平衡用户间的干扰，在满足QoS约束和天线功率约束下，考虑天线数量、用户数等因素的影响，实现异构大规模MIMO系统能效最优。鉴于回程功耗在大规模MIMO系统中的重要性，进一步考虑更符合实际应用的回程功耗系统模型，分析了回程功耗对系统性能的影响。分析和仿真结果表明，提出的新算法具有较强的实用性和较大的性能提升，特别是当天线数较大时，算法性能接近最优，特别适合于下一代通信的大规模 MIMO系统。

Abstract

A low complexity asymptotic regularized zero forcing cooperative beamforming algorithm based on energy efficiency in heterogeneous massive MIMO system was proposed

aiming at the problem that the current multi-flow regularization zero forcing beamforming algorithm sets the power constraint of each antenna in the regularization term as a fixed value and ignores the influences of factors such as the number of antennas

the number of users and QoS.The algorithm selects the optimal antenna power constraint set through the optimization method

and the optimal beamforming was asymptotically ob-tained to balance the interference among users to achieve the optimal energy efficiency

considering the impact of the number of antennas and users with the constraints of the antenna power and QoS.In view of the importance of backhaul in massive MIMO system

a backhaul power consumption model and the impact of backhaul power consumption on system performance was analyzed.Analysis and simulation results show that the proposed algorithm has great improvement of the performance

especially when the number of antennas is large.The algorithm is close to optimal performance

especially suitable for massive MIMO system of next generation communication.

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references

PAULRAJ A , GORE D , NABAR R , et al . An overview of MIMO communications—a key to gigabit wireless [J ] . Proceedings of the IEEE , 2004 , 92 ( 2 ): 198 - 218 .

XING C W , MA S D , ZHOU Y Q . Matrix-monotonic optimization for MIMO systems [J ] . IEEE Transactions on Signal Processing , 2015 , 63 ( 2 ): 334 - 348 .

LARSSON E , EDFORS O , TUFVESSON F , et al . Massive MIMO for next generation wireless systems [J ] . IEEE Communications Magazine , 2014 , 52 ( 2 ): 186 - 195 .

WU S , KUANG L L , NI Z Y , et al . Low-complexity iterative detection for large-scale multiuser MIMO-OFDM systems using approximate message passing [J ] . IEEE Journal of Selected Topics in Signal Processing , 2014 , 8 ( 5 ): 902 - 915 .

SHARIATI N , BJÖRNSON N , BENGTSSON M , et al . Low-complexity polynomial channel estimation in large-scale MIMO with arbitrary statistics [J ] . IEEE Journal of Selected Topics in Signal Processing , 2014 , 8 ( 5 ): 815 - 830 .

LI Q , LI K , KAH C . Achieving optimal diversity-multiplexing tradeoff for full-duplex MIMO multihop relay networks [J ] . IEEE Transactions on Information Theory , 2010 , 57 ( 1 ): 303 - 316 .

HOYDIS J , BRINK S , DEBBAH M . Massive MIMO in the UL/DL of cellular networks:how many antennas do we need? [J ] . IEEE Journal on Selected Areas in Communications , 2013 , 31 ( 2 ): 160 - 171 .

HOYDIS J , BRINK S , DEBBAH M . Comparison of linear precoding schemes for downlink Massive MIMO [C ] // International Conference on Communications . IEEE , 2012 : 2135 - 2139 .

TIMOTHEOU S , KRIKIDIS I , ZHENG G , et al . Beamforming for MISO interference channels with QoS and RF energy transfer [J ] . IEEE Transactions on Wireless Communications , 2014 , 13 ( 5 ): 2646 - 2658 .

XU H B , LIU J , ZHOU A Z . Distributed energy efficiency beamforming design in multiple-input-single-output interference channels [J ] . IET Communications , 2016 , 10 ( 15 ): 1964 - 1970 .

DAI B B , YU W . Energy efficiency of downlink transmission strategies for cloud radio access networks [J ] . IEEE Journal on Selected Areas in Communications , 2016 , 34 ( 4 ): 1037 - 1050 .

BJÖRNSON E , KOUNTOURIS M , DEBBAH M . Massive mimo and small cells impriving energy efficiency by optimal soft-cell coordination [C ] // International Conference on Telecommunications . 2013 : 369 - 374 .

LIU Y N , DUAN X Y , BDOUDREAU G , et al . Adaptive beamforming based inband fronthaul for cost-effective virtual small cell in 5G networks [C ] // Global Communications Conference . IEEE , 2017 : 1 - 6 .

LIN Y , LI S D , WANG Y , et al . Energy efficient power allocation scheme in heterogeneous cellular networks [C ] // International Conference on Wireless Communications ＆ Signal Processing . 2015 : 1 - 5 .

GUPTA , JHA A , KUMAR R . Power optimization with low complexity using scaled beamforming approach for a massive MIMO and small cell scenario [J ] . Wireless Networks , 2018 : 1 - 12 .

CHOI J . On downlink beamforming with small cells in wireless heterogeneous systems [J ] . IEEE Wireless Communications Letters , 2015 , 4 ( 4 ): 425 - 428 .

RAMAMOORTHI Y , KUMAR A . Resource allocation for CoMP in cellular networks with base station sleeping [J ] . IEEE Access , 2018 , 6 ( 1 ): 12620 - 12633 .

NIGAM G , MINERO P , HAENGGI M . Coordinated multipoint joint transmission in heterogeneous networks [J ] . IEEE Transactions on Communications , 2014 , 62 ( 11 ): 4134 - 4146 .

XU G Z , LIU A , JIANG W , et al . Energy-efficient beamforming for two-tier massive MIMO downlink [J ] . China Communications , 2015 , 12 ( 10 ): 64 - 75 .

LEE N , JIMENEZ D , LOZANO A , et al . Spectral efficiency of dynamic coordinated beamforming:a stochastic geometry approach [J ] . IEEE Transactions on Wireless Communications , 2014 , 14 ( 1 ): 230 - 241 .

IRMER R , DROSTE H , MARSCH P , et al . Coordinated multipoint:concepts performance and field trial results [J ] . IEEE Communications Magazine , 2011 , 49 ( 2 ): 102 - 111 .

MOWLA M , AHMAD I , HABIBI D , et al . A green communication model for 5G systems [J ] . IEEE Transactions on Green Communications and Networking , 2017 , 1 ( 13 ): 264 - 280 .

HAO Y Y , NI Q , LI H , et al . On the energy and spectral efficiency tradeoff in massive MIMO-enabled hetnets with capacity-constrained backhaul links [J ] . IEEE Transactions on Communications , 2017 , 65 ( 11 ): 5720 - 4733 .

CHEN L , YU F , JI H , et al . Distributed virtual resource allocation in small-cell networks with full-duplex self-backhauls and virtualization [J ] . IEEE Transactions on Vehicular Technology , 2016 , 65 ( 7 ): 5410 - 5423 .

CHEN L , YU F , JI H , et al . Green full-duplex self-backhaul and energy harvesting small cell networks with massive MIMO [J ] . IEEE Journal on Selected Areas in Communications , 2016 , 34 ( 12 ): 3709 - 3724 .

TOMBAZ B , MONTI P , WANG K , et al . Impact of backhauling power consumption on the deployment of heterogeneous mobile networks [C ] // Global Telecommunications Conference . IEEE , 2011 : 1 - 5 .

MONTI P , TOMBAZ S , WOSINSKA L , et al . Mobile backhaul in heterogeneous network deployments:technology options and power consumption [C ] // International Conference on Transparent Optical Networks . 2012 : 1 - 7 .

SUÁREZ L , BOURAOUI M , MERTAH M , et al . Energy efficiency and cost issues in backhaul architectures for high data-rate green mobile heterogeneous networks [C ] // 26th Annual International Symposium on Personal,Indoor,and Mobile Radio Communications . IEEE , 2015 : 1563 - 1568 .

NG D , LO E , SCHOBER R . Energy-efficient resource allocation in OFDMA systems with large numbers of base station antennas [J ] . IEEE Transactions on Wireless Communications , 2012 , 11 ( 9 ): 3292 - 3304 .

ARNOLD O , RICHTER F , BLUME O , et al . Power consumption modeling of different base station types in heterogeneous cellular networks [C ] // Future Network ＆ Mobile Summit . 2010 : 1 - 8 .

KARAKAYALI M , FOSCHINI G , VALENZUELA R . Network coordination for spectrally efficient communications in cellular systems [J ] . Wireless Communications IEEE , 2006 , 13 ( 4 ): 56 - 61 .

HUQ K , MUMTAZ S , BACHMATIUK I , et al . Green HetNet CoMP:energy efficiency analysis and optimization [J ] . IEEE Transactions on Vehicular Technology , 2015 , 64 ( 10 ): 4670 - 4683 .

ZARAKOVITIS C , NI Q . Maximizing energy efficiency in multiuser multicarrier broadband wireless systems:convex relaxation and global optimization techniques [J ] . IEEE Transactions on Vehicular Technology , 2016 , 65 ( 7 ): 5275 - 5286 .

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