On the Comparison of Various Overhead Arrangements for Massive MIMO-OFDM Channel Estimation

被引:2
|
作者
Sure, Pallaviram [1 ]
Bhuma, Chandra Mohan [2 ]
机构
[1] REVA Inst Technol & Management, Bangalore, Karnataka, India
[2] Bapatla Engn Coll, Bapatla, India
关键词
Massive MIMO-OFDM; time domain synchronous; comb type with cyclic prefix; grid type with cyclic prefix; denoising threshold; LS channel estimation;
D O I
10.2478/eletel-2014-0021
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Massive multi input multi output (MIMO) systems incorporate orthogonal frequency division multiplexing (OFDM) technology to render high data rate services for future wireless communication applications. The channel estimator (CE) employed by a reliable massive MIMO-OFDM system requires huge amount of overhead in the form of known and null data transmissions, hence limiting the system spectral efficiency (SE). Often, CE design is a tradeoff between SE and system reliability. In this paper, CE with three different overhead arrangements, namely time domain synchronous (TDS), comb type with cyclic prefix (CTCP), 2 D grid type with cyclic prefix (GTCP) are investigated and a GTCP based CE is proposed which offers both high SE and improved system reliability. The proposed CE uses autocorrelation based denoising threshold for channel impulse response (CIR) estimation and does not require any knowledge of channel statistics (KCS). A 4 x 1 6 MIMO-OFDM system is simulated in a rayleigh fading channel environment with U-shaped doppler spectrum. From the bit error rate (BER) performance results inWiMax SUI-4, Advanced Television Technology Center (ATTC) and Brazil A channel environments, it is verified that the proposed CE with GTCP overhead and proposed denoising scheme, indeed improves both SE and system reliability. Hence it is suitable for application in all massive MIMO-OFDM systems.
引用
收藏
页码:173 / 179
页数:7
相关论文
共 50 条
  • [31] Beamforming-based Spatial Precoding with Channel Estimation for Massive MIMO-OFDM system
    Chiu, Chen-Hao
    Lee, Ju-Hong
    2024 IEEE RADIO AND WIRELESS SYMPOSIUM, RWS, 2024, : 19 - 22
  • [32] Channel Estimation of Massive MIMO-OFDM System Using Elman Recurrent Neural Network
    Nandi, Shovon
    Nandi, Arnab
    Pathak, Narendra Nath
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2022, 47 (08) : 9755 - 9765
  • [33] Convergence Condition of Simplified Information Geometry Approach for Massive MIMO-OFDM Channel Estimation
    Fan, Mingrui
    Yang, Jiyuan
    Chen, Yan
    Lu, An-An
    Gao, Xiqi
    Xia, Xiang-Gen
    Slock, Dirk
    2024 IEEE 99TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2024-SPRING, 2024,
  • [34] Hybrid Message Passing Algorithm for Downlink FDD Massive MIMO-OFDM Channel Estimation
    Song, Yi
    Zhang, Chuanzong
    Lu, Xinhua
    Saggese, Fabio
    Wang, Zhongyong
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2024, 23 (05) : 4596 - 4609
  • [35] Downlink transmission and channel estimation for cell-free massive MIMO-OFDM with DSDs
    Guo, Yunxiang
    Fan, Zhenqi
    Lu, An
    Wang, Pan
    Liu, Dongjie
    Xia, Xinjiang
    Wang, Dongming
    EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2022, 2022 (01)
  • [36] Large random matrix-based channel estimation for massive MIMO-OFDM uplink
    Sure, Pallaviram
    Babu, Narendra C.
    Bhuma, Chandra Mohan
    IET COMMUNICATIONS, 2018, 12 (09) : 1035 - 1041
  • [37] An Enhanced Whitening Rotation Semi-Blind Channel Estimation for Massive MIMO-OFDM
    Al-Salihi, Hayder
    Nakhai, Mohammad Reza
    2016 23RD INTERNATIONAL CONFERENCE ON TELECOMMUNICATIONS (ICT), 2016,
  • [38] Structured Hybrid Message Passing Based Channel Estimation for Massive MIMO-OFDM Systems
    Liu, Xiaofeng
    Wang, Wenjin
    Gong, Xinrui
    Fu, Xiao
    Gao, Xiqi
    Xia, Xiang-Gen
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2023, 72 (06) : 7491 - 7507
  • [39] Channel Estimation of Massive MIMO-OFDM System Using Elman Recurrent Neural Network
    Shovon Nandi
    Arnab Nandi
    Narendra Nath Pathak
    Arabian Journal for Science and Engineering, 2022, 47 : 9755 - 9765
  • [40] 3-D Parameterized Multipath Channel Estimation for Massive MIMO-OFDM Systems
    Liang, Junhui
    He, Jin
    Yu, Wenxian
    IEEE SYSTEMS JOURNAL, 2022, 16 (03): : 4094 - 4105