Analysis of Linear Precoding Techniques for Massive MIMO-OFDM Systems under various scenarios. Issue 1 (March 2021)

• Record Type: Journal Article
• Authors: Subitha, D.; Vani, R.
• Is Part Of: IOP conference series. Volume 1084:Issue 1(2021)
• Publication Date: 2021-03
• Subjects: Massive MIMO -- Linear precoding -- Zero-Forcing(ZF) -- Conjugate gradient -- Minimum Mean Square Error (MMSE); Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/1084/1/012053
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: Emerging 5G technology is largely supported by the base station signal processing techniques such as precoding. Precoding combines the input signals in a predefined way and deliver them in a right proportion to the multiple antenna elements. Such precoding algorithms are crucial for the design of the emerging 5G technology; massive MIMO system. In this paper, the performance of various linear precoding algorithms such as Zero Forcing (ZF), Minimum Mean Square Error (MMSE) and Conjugate Gradient (CG) based precoding are analyzed in terms of Bit Error Rate (BER) and achievable sum-rate. The results are analyzed under various channel conditions such as rural, sub urban and urban. The above algorithms are tested for MIMO-OFDM system. OFDM system simulated here uses 52 subcarriers and a Base Station equipped with more than 100 antennas serving multiple users simultaneously. The channel models are stochastic channels simulated using WINNER II modeling.