MU-MIMO单比特ADC系统中软输出检测算法

doi:10.12305/j.issn.1001-506X.2021.02.30

系统工程与电子技术 ›› 2021, Vol. 43 ›› Issue (2): 555-560.doi: 10.12305/j.issn.1001-506X.2021.02.30

MU-MIMO单比特ADC系统中软输出检测算法

王华华(), 余永坤(), 于敏()

重庆邮电大学通信与信息工程学院, 重庆 400065

收稿日期:2020-04-05 出版日期:2021-02-01 发布日期:2021-03-16
作者简介:王华华(1981-),男,高级工程师,硕士,主要研究方向为移动通信基带处理嵌入式系统、通信软件开发。E-mail:8867420@qq.com|余永坤(1994-),男,硕士研究生,主要研究方向为移动通信物理层算法。E-mail:yuyk_yyk@qq.com|于敏(1996-),女,硕士研究生,主要研究方向为移动通信物理层算法。E-mail:1205886604@qq.com
基金资助:
国家科技重大专项(2017ZX03001021-004)

Soft output detection algorithm in MU-MIMO one-bit ADC system

Huahua WANG(), Yongkun YU(), Min YU()

School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China

Received:2020-04-05 Online:2021-02-01 Published:2021-03-16

摘要/Abstract

摘要：

低精度量化技术能解决毫米波通信射频链高能耗问题而使相关的接收技术受到广泛关注。本文针对应用于单比特量化上行多用户多输入多输出(multiuser multiple input multiple output, MU-MIMO)系统的软输出检测(soft output detection, SOD)算法计算复杂度高的问题，针对软输出检测(soft output detection, SOD)算法计算复杂度高的问题,结合串行干扰消除算法与SOD算法,提出排序多用户单比特串行干扰消除SOD(ordered multiuser one-bit successive interference cancellation SOD, OMuOSIC-SOD)算法,所提算法计算复杂度更低且能动态调整。在基于polar编码的MU-MIMO系统中的仿真结果表明, OMuOSIC-SOD算法随着同时检测的用户数目增加,误帧率(frame error rate, FER)逐渐接近SOD检测算法;在8×32 MIMO中, FER为10^-3时, OMuOSIC-SOD算法每次检测的用户数目每增加2个,得到约0.6 dB的性能增益。综上所述，所提算法可以通过调整每次检测的用户数量来调整检测性能，提升了算法的灵活性。

关键词: 单比特模拟数字转换器, 多用户多输入多输出, 软信号检测

Abstract:

Low-precision quantization technology can solve the problem of high energy consumption in the millimeter wave communication radio frequency chain, so related receiving technologies have received widely attention. This paper aims at the high computational complexity of the soft output detection (SOD) algorithm applied to the one-bit quantization uplink multiuser multiple input multiple output (MU-MIMO) system, combining with the successive interference cancellation algorithm and the SOD algorithm. The proposed algorithm has lower computational complexity and can be dynamically adjusted. The simulation results of the MU-MIMO system based on the polar coding show that the frame error rate (FER) of the OMuOSIC-SOD algorithm gradually approaches the SOD detection algorithm with the increase of the number of users detected simultaneously. In 8×32 MIMO, when the frame error rate is 10^-3, for the number of users detected by the OMuOSIC-SOD algorithm increases by 2 each time, the performance gain 0.6 dB is obtained. To sum up, the proposed algorithm can adjust the detection performance by adjusting the number of users detected each time, which improves the flexibility of the algorithm.

Key words: one-bit analog-to-digital converter (ADC), multiuser multiple input multiple output (MU-MIMO), soft signal detection

中图分类号:

TN929.53

王华华, 余永坤, 于敏. MU-MIMO单比特ADC系统中软输出检测算法[J]. 系统工程与电子技术, 2021, 43(2): 555-560.

Huahua WANG, Yongkun YU, Min YU. Soft output detection algorithm in MU-MIMO one-bit ADC system[J]. Systems Engineering and Electronics, 2021, 43(2): 555-560.

图/表 5

参考文献 25

1	LU L , LI G Y , SWINDLEHURST A L , et al. An overview of massive MIMO: benefits and challenges[J]. IEEE Journal of Selected Topics in Signal Processing, 2014, 8 (5): 742- 758. doi: 10.1109/JSTSP.2014.2317671
2	YANG H, MARZETTA T L. Total energy efficiency of cellular large scale antenna system multiple access mobile networks[C]//Proc.of the IEEE Online Conference on Green Communications, 2013.
3	MEZGHANI A, NOSSEK J A. Modeling and minimization of tran-sceiver power consumption in wireless networks[C]//Proc.of the IEEE International ITG Workshop on Smart Antennas, 2011.
4	LIANG N , ZHANG W . Mixed-ADC massive MIMO[J]. IEEE Journal on Selected Areas in Communications, 2015, 34 (4): 983- 997.
5	HANZO L , EL-HAJJAR M , ALAMRI O . Near-capacity wireless transceivers and cooperative communications in the MIMO era: evolution of standards, waveform design and future perspectives[J]. Proceedings of the IEEE, 2011, 99 (8): 1343- 1385. doi: 10.1109/JPROC.2011.2148150
6	ZHANG J Y , DAI L L , HE Z Y , et al. Performance analysis of mixed-ADC massive MIMO systems over rician fading channels[J]. IEEE Journal on Selected Areas in Communications, 2017, 35 (6): 1327- 1338. doi: 10.1109/JSAC.2017.2687278
7	JUNIL C , MO J H , ROBERT W H J . Near maximum-likelihood detector and channel estimator for uplink multiuser massive MIMO systems with one-bit ADCs[J]. IEEE Trans.on Communications, 2015, 64 (5): 2005- 2018.
8	JEON Y S , HONG S N , LEE N . Supervised-learning-aided communication framework for MIMO systems with low-resolution ADCs[J]. IEEE Trans.on Vehicular Technology, 2018, 64 (8): 7299- 7313.
9	HONG S N , KIM S , LEE N . A weighted minimum distance decoding for uplink multiuser MIMO systems with low-resolution ADCs[J]. IEEE Trans.on Communications, 2018, 66 (5): 1912- 1924. doi: 10.1109/TCOMM.2017.2787565
10	HONG S N , LEE N . Soft-output detector for uplink MU-MIMO systems with one-bit ADCs[J]. IEEE Communications Letters, 2018, 22 (5): 930- 933. doi: 10.1109/LCOMM.2018.2808967
11	CHO Y , HONG S N . One-bit successive cancellation soft output (OSS) detector for uplink MU-MIMO systems with one-bit ADCs[J]. IEEE Access, 2019, 7, 27172- 27182. doi: 10.1109/ACCESS.2019.2901942
12	ZHANG T C , WEN C K , JIN S , et al. Mixed-ADC massive MIMO detectors: performance analysis and design optimization[J]. IEEE Trans.on Wireless Communications, 2016, 15 (11): 7738- 7752. doi: 10.1109/TWC.2016.2606592
13	JOÃO G , RUI D , PAULO . Low-complexity SC-FDE techniques for massive MIMO schemes with low-resolution ADCs[J]. IEEE Trans.on Communications, 2019, 67 (3): 2368- 2380. doi: 10.1109/TCOMM.2018.2881462
14	JEON Y S , DO H , HONG S N , et al. Soft-output detection methods for sparse millimeter wave MIMO systems with low-precision ADCs[J]. IEEE Trans.on Communications, 2019, 67 (4): 2822- 2836. doi: 10.1109/TCOMM.2019.2892048
15	HE H T , WEN C K , JIN S . Bayesian optimal data detector for hybrid mm wave MIMO-OFDM systems with low-resolution ADCs[J]. IEEE Journal Selected Topics Signal Processing, 2018, 12 (3): 469- 483. doi: 10.1109/JSTSP.2018.2818063
16	ROTH K, NOSSEK J A. Robust massive MIMO equilization for mm wave systems with low resolution ADCs[C]//Proc.of the IEEE Wireless Communications and Networking Conference Workshops, 2018: 113-118.
17	WANG H , WEN C , JIN S . Bayesian optimal data detector for mm wave OFDM system with low-resolution ADC[J]. IEEE Journal on Selected Areas in Communications, 2017, 35 (9): 1962- 1979. doi: 10.1109/JSAC.2017.2720978
18	CHRISTOPH S , GIUSEPPE D . Quantized massive MU-MIMO-OFDM uplink[J]. IEEE Trans.on Communications, 2016, 64 (6): 2387- 2399. doi: 10.1109/TCOMM.2016.2558151
19	WEN C K , WANG C J , JIN S , et al. Bayes-optimal joint channel-and-data estimation for massive MIMO with low-precision ADCs[J]. IEEE Trans.on Signal Processing, 2016, 64 (10): 2541- 2556. doi: 10.1109/TSP.2015.2508786
20	WANG S C , LI Y Z , WANG J . Multiuser detection in massive spatial modulation MIMO with low-resolution ADCs[J]. IEEE Trans.on Wireless Communications, 2015, 14 (4): 2156- 2168. doi: 10.1109/TWC.2014.2382098
21	ALEVIZOS P N . Low-complexity multiuser QAM detection for uplink 1-bit massive MIMO[J]. IEEE Communications Letters, 2018, 22 (8): 1592- 1595. doi: 10.1109/LCOMM.2018.2844346
22	JEON Y S , LEE N , HONG S N , et al. One-bit sphere decoding for uplink massive MIMO systems with one-bit ADCs[J]. IEEE Trans.on Wireless Communications, 2018, 17 (7): 4509- 4521. doi: 10.1109/TWC.2018.2827028
23	SHAO Z C , RODRIGO C D L , LUKAS T N L . Iterative detection and decoding for large-scale multiple-antenna systems with 1-bit ADCs[J]. IEEE Wireless Communications Letters, 2018, 7 (3): 476- 479. doi: 10.1109/LWC.2017.2787159
24	ZHANG Z Y , CAI X , LI C G , et al. One-bit quantized massive MIMO detection based on variational approximate message passing[J]. IEEE Trans.on Signal Processing, 2018, 66 (9): 2358- 2373. doi: 10.1109/TSP.2017.2786256
25	WANG S C , ZHANG L , LI Y Z , et al. Multiuser MIMO transmission aided by massive one-bit magnitude measurements[J]. IEEE Trans.on Wireless Communications, 2016, 15 (10): 7058- 7073. doi: 10.1109/TWC.2016.2596718

[1]	韩康祺, 钱骅, 裴旭明, 康凯. 降低多用户MIMO系统PAPR的广义SLM算法[J]. 系统工程与电子技术, 2021, 43(6): 1673-1678.
[2]	王舒, 达新宇, 褚振勇. 基于人工噪声多用户MIMO系统的窃密算法[J]. 系统工程与电子技术, 2016, 38(11): 2648-2652.

MU-MIMO单比特ADC系统中软输出检测算法

Soft output detection algorithm in MU-MIMO one-bit ADC system

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 5

参考文献 25

相关文章 2

编辑推荐

Metrics

本文评价