Precoding and Detection for Broadband Single Carrier Terahertz Massive MIMO Systems Using LSQR Algorithm
Journal article, 2019

The terahertz (THz) communication utilizes the frequency spectrum above 300 GHz and is widely considered as a promising solution to the future high-speed short-range wireless communication beyond millimeter wave (mmWave) communication. While providing tens of gigahertz bandwidth, it is subjected to high propagation path loss, inter-symbol and inter-user interferences. The massive multiple-input- multiple-output (MIMO) can be applied to address these problems by cooperation between many access point (AP) antennas. However, the THz channel characteristics, including high propagation path loss, frequency selectivity and big number of samples per channel impulse response (CIR), require carefully tailored algorithm for massive MIMO signal processing. In this paper, we propose a single carrier minimum mean square error (MMSE) precoding and detection algorithm for frequency selective THz channels. The MIMO signal transmission is described with the block matrices. A gain control heuristic is introduced to reduce the complexity. The sparsity property of the channel is utilized to construct sparse channel matrices and the least square QR (LSQR) algorithm is applied to efficiently solve the problems. Besides the uniform antenna array, the hybrid array consisting of several subarrays is considered as well. Simulation results show that the massive MIMO array can provide a satisfactory performance in terms of bit error rate (BER).

block matrix


frequency selective channel

LSQR algorithm

massive MIMO

THz communication




Bile Peng

Technische Universität Braunschweig

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Stefan Wesemann


Ke Guan

Beijing Jiaotong University

Wolfgang Templ


Thomas Kürner

Technische Universität Braunschweig

IEEE Transactions on Wireless Communications

15361276 (ISSN) 15582248 (eISSN)

Vol. 18 8599164 1026-1040 8599164

Subject Categories


Communication Systems

Signal Processing



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