Energy Efficiency Equalization Method of Cell-Free System Based on ADC Precision and AP Selection

doi:10.19678/j.issn.1000-3428.0063843

Abstract

Abstract: Cell-free massive Multiple Input Multiple Output (MIMO) systems achieve macro diversity gain and low path loss owing to the large-scale deployment of Access Points (AP), but the resulting large power loss also leads to an imbalance with respect to system energy efficiency.To address the energy efficiency quality imbalance problem of multi-AP joint cooperation in cell-free massive MIMO systems, this paper proposes an energy efficiency equalization method based on Analog-to-Digital Converter (ADC) precision and AP selection.First, the Poisson process is used to model the user distribution, and the closed-form solutions of spectral efficiency and energy efficiency are derived when all AP are activated.Then, the effective channel and interference channel gain are considered as a kind of indicator to obtain the corresponding channel covariance matrix by using the method of descending order index, step-by-step according to the index of AP set selection. When using the AP service users to determine whether the change in the spectral efficiency difference is less than the threshold, stop filter and determine the AP combination of low interference between users.Finally, through the joint optimization of ADC precision and AP selection, the optimal quantization number is obtained to achieve a balance in terms of the system spectral efficiency and energy efficiency. Simulation results show that compared with the AP selection method based on full AP selection and large-scale fading, the proposed method can achieve a better energy efficiency balance, especially in the user intensive area, which can improve energy efficiency by about 20%.Moreover, the use of max-min power control can further realize good regional consistent user service quality.

Key words: cell-free massive Multiple Input Multiple Output(MIMO), Access Points(AP) selection, Analog-to-Digital Converters(ADC) precision selection, signal interference difference, energy efficiency balance

摘要： 去蜂窝大规模多输入多输出（MIMO）系统通过部署大规模接入点（AP），获得宏分集增益和较低的路径损耗，但产生的大量功耗损失使得系统能效质量失衡。针对去蜂窝大规模MIMO系统与多AP联合协作的能效质量失衡问题，提出一种基于模数转换器（ADC）精度和AP选择的能效均衡方法。利用泊松过程对用户分布进行建模，推导出激活所有AP时频谱效率及能量效率的闭式解，将有效信道与干扰信道增益的占比作为排序指标，通过降序排序的方法获得相应信道方差矩阵索引，按索引对AP集进行逐层筛选，当AP联合服务用户获得频谱效率的变化差值小于阈值时，停止筛选并确定用户间干扰低的AP组合。通过ADC精度与AP选择的联合优化获取最优量化位数，实现系统频谱效率与能效的均衡。仿真结果表明，与全AP选择、基于大尺度衰落的AP选择方法相比，该方法能达到较优的能效质量均衡，尤其在用户密集区域，可提升约20%能效，同时利用最大最小功率控制可保证系统区域一致良好的用户服务质量。

关键词: 去蜂窝大规模多输入多输出, 接入点选择, 模数转换器精度选择, 信号干扰差值, 能效均衡

CLC Number:

TN929.5

DING Qingfeng, XU Mengyin, SHI Hui, LI Yihao, YANG Qian. Energy Efficiency Equalization Method of Cell-Free System Based on ADC Precision and AP Selection[J]. Computer Engineering, 2022, 48(11): 192-200.

丁青锋, 徐梦引, 石辉, 李怡浩, 杨倩. 基于ADC精度与AP选择的去蜂窝系统能效均衡方法[J]. 计算机工程, 2022, 48(11): 192-200.

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References

[1] NAYEBI E, ASHIKHMIN A, MARZETTA T L, et al.Precoding and power optimization in cell-free massive MIMO systems[J].IEEE Transactions on Wireless Communications, 2017, 16(7):4445-4459.
[2] 章嘉懿.去蜂窝大规模MIMO系统研究进展与发展趋势[J].重庆邮电大学学报(自然科学版), 2019, 31(3):285-292. ZHANG J Y.Overview of cell-free massive MIMO system[J].Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition), 2019, 31(3):285-292.(in Chinese)
[3] ZHANG J Y, BJÖRNSON E, MATTHAIOU M, et al.Prospective multiple antenna technologies for beyond 5G[J].IEEE Journal on Selected Areas in Communications, 2020, 38(8):1637-1660.
[4] GUENACH M, GORJI A A, BOURDOUX A.Joint power control and access point scheduling in fronthaul-constrained uplink cell-free massive MIMO systems[J].IEEE Transactions on Communications, 2021, 69(4):2709-2722.
[5] DAO H T, KIM S.Effective channel gain-based access point selection in cell-free massive MIMO systems[J].IEEE Access, 2020, 8:108127-108132.
[6] NGUYEN T H, NGUYEN T K, HAN H D, et al.Optimal power control and load balancing for uplink cell-free multi-user massive MIMO[J].IEEE Access, 2018, 6:14462-14473.
[7] NGO H Q, TRAN L N, DUONG T Q, et al.On the total energy efficiency of cell-free massive MIMO[J].IEEE Transactions on Green Communications and Networking, 2018, 2(1):25-39.
[8] SHAKYA I L, ALI F H.Joint access point selection and interference cancellation for cell-free massive MIMO[J].IEEE Communications Letters, 2021, 25(4):1313-1317.
[9] 赵迪, 郭爱煌, 宋春林.去蜂窝大规模MIMO系统功率控制算法[J].系统工程与电子技术, 2021, 43(3):854-860. ZHAO D, GUO A H, SONG C L.Power control algorithm for cell-free massive MIMO system[J].Systems Engineering and Electronics, 2021, 43(3):854-860.(in Chinese)
[10] BISWAS S, VIJAYAKUMAR P.AP selection in cell-free massive MIMO system using machine learning algorithm[C]//Proceedings of the 6th International Conference on Wireless Communications, Signal Processing and Networking.Washington D.C., USA:IEEE Press, 2021:158-161.
[11] JACOBSSON S, DURISI G, COLDREY M, et al.Throughput analysis of massive MIMO uplink with low-resolution ADCs[J].IEEE Transactions on Wireless Communications, 2017, 16(6):4038-4051.
[12] ZHANG Y, ZHOU M, QIAO X, et al.On the performance of cell-free massive MIMO with low-resolution ADCs[J].IEEE Access, 2019, 7:117968-117977.
[13] HU X L, ZHONG C J, CHEN X M, et al.Cell-free massive MIMO systems with low resolution ADCs[J].IEEE Transactions on Communications, 2019, 67(10):6844-6857.
[14] BASHAR M, CUMANAN K, BURR A G, et al.Energy efficiency of the cell-free massive MIMO uplink with optimal uniform quantization[J].IEEE Transactions on Green Communications and Networking, 2019, 3(4):971-987.
[15] BASHAR M, NGO H Q, CUMANAN K, et al.Uplink spectral and energy efficiency of cell-free massive MIMO with optimal uniform quantization[J].IEEE Transactions on Communications, 2021, 69(1):223-245.
[16] 王海荣, 王玉辉, 黄永明, 等.大规模MIMO蜂窝网络系统中的导频污染减轻方法[J].通信学报, 2014, 35(1):24-33. WANG H R, WANG Y H, HUANG Y M, et al.Pilot contamination reduction in very large MIMO cellular network[J].Journal on Communications, 2014, 35(1):24-33.(in Chinese)
[17] CHOI T, ITO M, KANNO I, et al.Energy efficiency of uplink cell-free massive MIMO with transmit power control in measured propagation channel[J].IEEE Open Journal of Circuits and Systems, 2021, 2:792-804.
[18] NGO H Q, LARSSON E G, MARZETTA T L.Energy and spectral efficiency of very large multiuser MIMO systems[J].IEEE Transactions on Communications, 2013, 61(4):1436-1449.
[19] FAN L, JIN S, WEN C K, et al.Uplink achievable rate for massive MIMO systems with low-resolution ADC[J].IEEE Communications Letters, 2015, 19(12):2186-2189.
[20] ZHANG Y, ZHOU M, CAO H T, et al.On the performance of cell-free massive MIMO with mixed-ADC under rician fading channels[J].IEEE Communications Letters, 2020, 24(1):43-47.
[21] ZHANG Y, ZHOU M, ZHAO H T, et al.Spectral efficiency of superimposed pilots in cell-free massive MIMO systems with hardware impairments[J].China Communications, 2021, 18(6):146-161.
[22] NGO H Q, ASHIKHMIN A, YANG H, et al.Cell-free massive MIMO versus small cells[J].IEEE Transactions on Wireless Communications, 2017, 16(3):1834-1850.
[23] MARZETTA T L, LARSSON E G, YANG H, et al.Fundamentals of massive MIMO[M].Cambridge, UK:Cambridge University Press, 2016.
[24] MAI T C, NGO H Q, TRAN L N.Energy efficiency maximization in large-scale cell-free massive MIMO:a projected gradient approach[J].IEEE Transactions on Wireless Communications, 2022, 34(1):1235-1246.
[25] LI W F, SUN X B, CHEN D J.Pilot assignment based on weighted-count for cell-free massive MIMO systems[C]//Proceedings of 2021 Asia-Pacific Conference on Communications Technology and Computer Science.Washington D.C., USA:IEEE Press, 2021:258-261.
[26] ÖZDOGAN Ö, BJÖRNSON E, ZHANG J Y.Performance of cell-free massive MIMO with rician fading and phase shifts[J].IEEE Transactions on Wireless Communications, 2019, 18(11):5299-5315.

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