协同信道空时优化MIMO无线传输系统

杨贵德; 周渊平; 夏文龙

doi:10.11999/JEIT170321

协同信道空时优化MIMO无线传输系统

doi: 10.11999/JEIT170321

基金项目:

高等学校博士学科点专项科研基金(20130191110006)

计量
- 文章访问数: 1426
- HTML全文浏览量: 170
- PDF下载量: 187
- 被引次数: 0
出版历程
- 收稿日期: 2017-04-12
- 修回日期: 2017-08-30
- 刊出日期: 2018-01-19

Cooperative Channel MIMO Wireless Transmission System with Space-time Optimization

Funds:

University Doctoral Research Foundation of China (20130191110006)

摘要

摘要: 该文提出一种基于虚拟信道的空时优化多输入多输出(MIMO)无线传输系统。通过在发射端产生不同的空时虚拟信道，与实际空间无线信道级联，构成系统的整体传输信道即协同空分信道。系统可以根据接收端的反馈信息采用模拟退火算法来优化虚拟信道，改善误码率(BER)性能。利用虚拟信道方法，可以使一根MIMO发射天线在同一时间、同一频段传输多路叠加合并后的数据信号，从而可以使发射的不同数据信号的总路数超过发射天线的数量，突破了现有MIMO系统在同一时间、同一频段最多只能发射与发射天线数量相等的不同数据信号的传统方式，可以显著提高系统的频谱效率。仿真结果和基于ZC706和AD9361硬件平台的微波暗室实际测试结果充分验证了新MIMO系统的有效性。
- MIMO系统 /
- 虚拟信道 /
- 模拟退火算法 /
- 误码率 /
- 频谱效率
Abstract: A space-time optimized Multiple-Input Multiple-Output (MIMO) wireless transmission system based on virtual channel method is proposed. At the transmitter, various space-time virtual channels are generated that are connected with the actual space wireless channels to form the cooperative space division channels. According to the feedback information from the receiver, the Bit Error Rate (BER) can be significantly improved by using the simulated annealing algorithm to optimize the virtual channels. Morever, by using the virtual channel method, it allows one MIMO antenna to transmit multiple superposed data streams in one frequency band at the same time, therefore it can transmit more number of different data streams than the number of transmit antennas, breaking the conventional way that the number of different data streams to be transmitted is equal to the number of transmit antennas. Thus, the proposed MIMO system can significantly improve the spectral efficiency. Simulation results and experimental test results based on ZC706 and AD9361 hardware platforms in microwave anechoic chamber fully demonstrate the effectiveness of the proposed MIMO system.
- MIMO system /
- Virtual channel /
- Simulated annealing algorithm /
- Bit Error Rate (BER) /
- Spectral efficiency

HTML全文

参考文献(19)

ZHANG Q, JIN S, MCKAY M, et al. Power allocation schemes for multicell massive MIMO systems[J]. IEEE Transactions on Wireless Communications, 2015, 14(11): 5941-5955. doi: 10.1109/TWC.2015.2444856.

HONG X M, WANG C X, THOMPSON J, et al. On spacefrequency correlation of UWB MIMO channels[J]. IEEE Transactions on Vehicular Technology, 2010, 59(9): 4201-4213. doi: 10.1109/TVT. 2010.2075947.

LIU Y, AI B, and CHEN B H. Impact of mutual coupling on LTE-R MIMO capacity for antenna array configurations in high speed railway scenario[C]. IEEE Vehicular Technology Conference, Nanjing, China, 2016: 1-5.

NTT DOCOMO, Inc. 5G radio access: Requirement, concept and techniques[R]. 5G White Paper, Tokyo, Japan, 2014.

RIMAL B P, VAN D P, and MAIER M. Mobile edge computing empowered fiber-wireless access networks in the 5G era[J]. IEEE Communications Magazine, 2017, 55(2): 192-200. doi: 10.1109 /MCOM.2017.1600156CM.

AL-ABBASI Z Q and SO D K C. Power allocation for sum rate maximization in non-orthogonal multiple access system [C]. Personal, Indoor and Mobile Radio Communications, Hong Kong, 2015: 1649-1653.

DO N T, COSTA D B D, DUONG T Q, et al. A BNBF user selection scheme for NOMA-based cooperative relaying systems with SWIPT[J]. IEEE Communications Letters, 2017, 21(3): 664-667. doi: 10.1109/LCOMM.2016.2631606.

DING Z G, DAI H Y, and POOR H V. Relay selection for cooperative NOMA[J]. IEEE Wireless Communications Letters, 2016, 5(4): 416-419. doi: 10.1109/LWC.2016. 2574709.

ALWAKEEL A S, MEHANA A H, and GHONEIM A. Pilot hopping in massive MIMO systems with MMSE channel estimation[C]. International Conference on Computing, Networking and Communications, Silicon Valley, CA, USA, 2017: 298-302.

UPADHYA K, VOROBYOV S A, and VEHKAPERA M. Superimposed pilots are superior for mitigating pilot contamination in massive MIMO[J]. IEEE Transactions on Signal Processing, 2017, 65(11): 2917-2932. doi: 10.1109/TSP. 2017.2675859.

SONG N, YANG T, and SUN H. Overlapped subarray based hybrid beamforming for millimeter wave multiuser massive MIMO[J]. IEEE Signal Processing Letters, 2017, 24(5): 550-554. doi: 10.1109/LSP.2017.2681689.

SUN Q, HAN S F, PAN Z G, et al. On the ergodic capacity of MIMO NOMA systems[J]. IEEE Wireless Communications Letters, 2015, 4(4): 405-408. doi: 10.1109/LWC.2015. 2426709.

SUN R J, WANG Y, WANG X S, et al. Transceiver design for cooperative nonorthogonal multiple access systems with wireless energy transfer[J]. IET Communications, 2016, 10(15): 1947-1955. doi: 10.1049/iet-com.2016.0120.

DIAMANYOULAKIS P D, PAPPI K N, DING Z G, et al. Wireless-powered communications with non-orthogonal multiple access[J]. IEEE Transactions on Wireless Communications, 2016, 15(12): 8422-8436. doi: 10.1109/ TWC.2016.2614937.

SHIEH S L, LIN C H, HUANG Y C, et al. On gray labeling for downlink non-orthogonal multiple access without SIC[J]. IEEE Communications Letters, 2016, 20(9): 1721-1724. doi: 10.1109/LCOMM.2016.2584040.

WINTERS J H. On the capacity of radio communication systems with diversity in a rayleigh fading environment[J]. IEEE Journal on Selected Areas in Communications, 1987, SAC-5(5): 871-878. doi: 10.1109/JSAC.1987.1146600.

王青, 肖怀铁, 张安. 基于模拟退火算法的MIMO雷达稀疏线阵设计[J]. 计算机工程与应用, 2011, 47(8S): 272-276.

WANG Q, XIAO H T, and ZHANG A. MIMO radar sparse linear array design based on simulated annealing algorithm [J]. Computer Engineering and Applications, 2011, 47(8S): 272-276.

田景文, 高美娟. 人工神经网络算法研究及应用[M]. 北京: 北京理工大学出版社, 2006: 182-190.

施引文献

资源附件(0)

访问统计