1 |
张平, 陶运铮, 张治. 5G若干关键技术评述[J]. 通信学报, 2016, 37 (7): 15- 29.
|
|
ZHANG P , TAO Y Z , ZHANG Z . Survey of several key technologies for 5G[J]. Journal of Communication, 2016, 37 (7): 15- 29.
|
2 |
张军阳, 王慧丽, 郭阳, 等. 深度学习相关研究综述[J]. 计算机应用研究, 2018, 35 (7): 1921- 1928.1921-1928, 1936
doi: 10.3969/j.issn.1001-3695.2018.07.001
|
|
ZHANG J Y , WANG H L , GUO Y , et al. Review of deep learning[J]. Application Research of Computers, 2018, 35 (7): 1921- 1928.1921-1928, 1936
doi: 10.3969/j.issn.1001-3695.2018.07.001
|
3 |
LARSSON E G . MIMO detection methods: how they work[J]. IEEE Signal Processing Magazine, 2009, 26 (3): 91- 95.
|
4 |
BOUKHAROUBA A , DEHEMCHI M , BOUHAFER A . Low-complexity signal detection and precoding algorithms for multiuser massive MIMO systems[J]. SN Applied Sciences, 2021, 3 (2): 1- 7.
|
5 |
ZHAO S F , SHEN B , HUA Q . A comparative study of low-complexity MMSE signal detection for massive MIMO systems[J]. KSⅡ Trans.on Internet & Information Systems, 2018, 12 (4): 1504- 1526.
|
6 |
TANG C , LIU C , YUAN L C , et al. High precision low complexity matrix inversion based on newton iteration for data detection in the massive MIMO[J]. IEEE Communications Letters, 2016, 20 (3): 490- 493.
doi: 10.1109/LCOMM.2015.2514281
|
7 |
LI H, ZHAO X Y, GUO C, et al. A high-parallelism detection algorithm for massive MIMO systems[C]//Proc. of the IEEE 7th International Conference on Electronics Information and Emergency Communication, 2017.
|
8 |
LI H, ZHAO X Y, GUO C, et al. A low-complexity detection method based on iteration for massive MIMO systems[C]//Proc. of the 9th IEEE International Conference on Communication Software and Networks, 2017.
|
9 |
O'SHEA T , HOYDIS J . An introduction to deep learning for the physical layer[J]. IEEE Trans.on Cognitive Communications and Networking, 2017, 3 (4): 563.
doi: 10.1109/TCCN.2017.2758370
|
10 |
朱啸豪, 孙超, 姜述超. 基于深度学习和AMP的MIMO检测算法[J]. 微型电脑应用, 2020, 36 (5): 96- 98.
|
|
ZHU X H , SUN C , JIANG S C . MIMO detection algorithm based on deep learning and AMP[J]. Microcomputer Applications, 2020, 36 (5): 96- 98.
|
11 |
LI Q, ZHANG A H, LI J J, et al. Soft decision signal detection of MIMO system based on deep neural network[C]//Proc. of the 5th International Conference on Computer and Communication Systems, 2020: 665-669.
|
12 |
SAMUEL N, DISKIN T, WIESEL A. Deep MIMO detection[EB/OL]. [2021-09-01]. https://arxiv.org/abs/1706.01151.
|
13 |
SAMUEL N , DISKIN T , WIESEL A . Learning to detect[J]. IEEE Trans.on Signal Processing, 2019, 67 (10): 2554- 2564.
|
14 |
张晓羽, 贺光辉. 基于深度学习的大规模MIMO检测算法研究[J]. 信息技术, 2020, 44 (6): 10- 14.
|
|
ZHANG X Y , HE G H . Deep learning for massive MIMO detection algorithm[J]. Information Technology, 2020, 44 (6): 10- 14.
|
15 |
胡钟秀, 王鸿, 宋荣方. 基于SAMP-Net的MIMO信号检测算法[J]. 南京邮电大学学报(自然科学版), 2020, 40 (6): 36- 41.
|
|
HU Z X , WANG H , SONG R F . Signal detection based on SAMP-Net method for MIMO systems[J]. Journal of Nanjing University of Posts and Telecommunications(Natural Science Edition), 2020, 40 (6): 36- 41.
|
16 |
WU M , YIN B , WANG G H , et al. Large-scale MIMO detection for 3GPP LTE: algorithms and FPGA implementations[J]. IEEE Journal of Selected Topics in Signal Processing, 2017, 8 (5): 916- 929.
|
17 |
KINGMA D, BA J. Adam: a method for stochastic optimization[C]//Proc. of the 3rd International Conference on Learning Representations, 2015.
|