A Low Complexity Channel Estimation and Detection for Massive MIMO Using SC-FDE
Applied Sciences (Switzerland) Vol. 1, Nº 1, pp. 3 - 17, March, 2020.
ISSN (print): 2076-3417
Journal Impact Factor: 1,679 (in 2016)
Digital Object Identifier: 10.3390/telecom1010002
Download Full text PDF ( 1 MB)
Downloaded 2 times
5G Communications will support millimeter waves (mm-Wave), alongside with the conventional centimeter waves, which will enable much higher throughputs and facilitate the employment of hundreds or thousands of antenna elements, commonly referred to as massive Multiple Input Multiple Output (MIMO) systems. This article proposes and studies an efficient low complexity receiver that jointly performs channel estimation based on superimposed pilots, and data detection, optimized for massive MIMO (m-MIMO). Superimposed pilots suppress the overheads associated to channel estimation based on conventional pilot symbols, which tends to be more demanding in the case of m-MIMO, leading to a reduction in the spectral efficiency. On the other hand, MIMO systems tend to be associated to an increase of complexity and increase of signal processing, with an exponential increase with the number of transmit and receive antennas. A reduction of complexity is obtained with the use of the two proposed algorithms. These algorithms reduce the complexity but present the disadvantage that they generate a certain level of interference. In this article, we consider an iterative receiver that performs the channel estimation using superimposed pilots and data detection, while mitigating the interference associated to the proposed algorithms, leading to a performance very close to that obtained with conventional pilots, but without the corresponding loss in the spectral efficiency.