Performance Analysis of Linear Precoding in Downlink Based on Polynomial Expansion on Massive MIMO Systems

Abstract The performance of linear precoding schemes in downlink Massive MIMO systems is dealt with in this paper. Linear precoding schemes are incorporated with zero-forcing (ZF) and maximum ratio transmission (MRT), truncated polynomial expansion (TPE), regularized zero force (RZF) in Downlink massive MIMO systems. Massive MIMO downlink output is evaluated with linear precoding included. This paper expresses the performance of achievable sum-rate linear precoding with variable signal-to-noise (SNR) ratio and achievable sum rate and several transmitter-receiver antennas, such as imperfect CSI, less complex processing, and inter-user interference. The transmitter has complete state information on the channel. The information narrates how a signal propagates to the receiver from the transmitter and reflects, for example, the cumulative effect of distance scattering, fading, and power decay. They show that the performance analysis of two linear precoding techniques, i.e., Maximum Ratio Transmission (MRT) and Zero Forcing (ZF) for downlink mMIMO output network over a perfect chain. The results show the improved ZF precoding achievable sum rate compared to the MRT precoding schemes and compared the average achievable rate RZF and TPE.

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Performance Analysis of Linear Precoding in Downlink Based on Polynomial Expansion on massive MIMO systems

10.21203/rs.3.rs-787294/v1 ◽

2021 ◽

Author(s):

SAMMAIAH THURPATI ◽

P Muthuchidambaranathan

Keyword(s):

Performance Analysis ◽

Massive Mimo ◽

Mimo Systems ◽

Cumulative Effect ◽

Polynomial Expansion ◽

Achievable Rate ◽

Linear Precoding ◽

Zero Forcing ◽

Sum Rate ◽

Ratio Transmission

Abstract The performance of linear precoding schemes in downlink Massive MIMO systems is dealt with in this paper. Linear precoding schemes are incorporated with zero forcing (ZF) and maximum ratio transmission (MRT), truncated polynomial expansion (TPE), regularized zero force (RZF) in Downlink massive MIMO systems. Massive MIMO downlink output is evaluated with linear precoding included. This paper expresses the performance of achievable sum rate linear precoding with variable signal-to-noise (SNR) ratio and achievable sum rate and several transmitter-receiver antennas, such as imperfect CSI, less complex processing and inter-user interference. The transmitter has complete state information on the channel. The information narrate how a signal propagates to the receiver from the transmitter and reflects, for example, the cumulative effect of distance scattering, fading, and power decay. They show that the performance analysis of two linear precoding techniques,i.e.Maximum Ratio Transmission (MRT) and Zero Forcing (ZF) for downlink mMIMO output network over a perfect chain. The results show the improved ZF precoding achievable sum rate compared to the MRT precoding schemes and also compared the average achievable rate RZF and TPE.

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The Performance Analysis of Two Conventional Linear Pre-Coding Schemes in Massive MIMO System with Imperfect CSIT

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.668-669.1386 ◽

2014 ◽

Vol 668-669 ◽

pp. 1386-1390

Author(s):

Ren Kai Yu ◽

Jun Xuan Wang ◽

You Ming Sun ◽

Yang Liu

Keyword(s):

Performance Analysis ◽

Massive Mimo ◽

Mimo System ◽

Zero Forcing ◽

Low Snr ◽

Coding Schemes ◽

Sum Rate ◽

Ratio Transmission ◽

Maximum Ratio Transmission

For this paper, we analyze the achievable sum rate of zero-forcing (ZF) pre-coding and Maximum Ratio Transmission (MRT) pre-coding with Matrix Normalization in massive MIMO system with Imperfect CSIT. We compare the performances of these two pre-codings and find that ZF pre-coding outperforming MRT pre-coding in the high SNR region while MRT pre-coding outperforming ZF pre-coding in the low SNR region. Then we derive the threshold of the pre-coding selection and provide the procedure of pre-coding schemes selection.

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Low-Complexity Multi-User Parameterized Beamforming in Massive MIMO Systems

Electronics ◽

10.3390/electronics9060882 ◽

2020 ◽

Vol 9 (6) ◽

pp. 882 ◽

Cited By ~ 1

Author(s):

Geon-Woong Jung ◽

Yong-Hwan Lee

Keyword(s):

Computer Simulation ◽

Massive Mimo ◽

Mimo Systems ◽

Low Complexity ◽

Beam Direction ◽

Transmission Scheme ◽

Zero Forcing ◽

Combined Use ◽

Ratio Transmission ◽

Maximum Ratio Transmission

In this paper, we design a complexity-reduced transmission scheme in massive antenna environments. To reduce the implementation complexity for the generation of beam weight, we design a multi-user parameterized beamforming (MUPB) scheme that can control the beam direction using a single parameter with combined use of maximum ratio transmission and partial zero-forcing scheme that partially nulls out interference. We design the MUPB to maximize the signal-to-leakage plus noise ratio (SLNR). To further reduce the implementation complexity, we optimize the MUPB based on approximated SLNR instead of accurate SLNR. Finally, the performance of the proposed MUPB is verified by computer simulation.

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Satellite-Assisted Cell-Free Massive MIMO Systems with Multi-Group Multicast

Sensors ◽

10.3390/s21186222 ◽

2021 ◽

Vol 21 (18) ◽

pp. 6222

Author(s):

Jiamin Li ◽

Lingling Chen ◽

Pengcheng Zhu ◽

Dongming Wang ◽

Xiaohu You

Keyword(s):

Closed Form ◽

Massive Mimo ◽

Mimo Systems ◽

Transmission Efficiency ◽

Spectrum Efficiency ◽

Achievable Rate ◽

Zero Forcing ◽

Channel State ◽

Average System ◽

Ratio Transmission

In this paper, we use satellite-assisted and multi-group multicast mechanisms to relieve ground traffic pressure and improve data transmission efficiency of cell-free massive MIMO systems. We propose to estimate channel state information (CSI) by common pilot scheme. Given the estimated CSI, we derive the closed-form expressions of achievable rate with maximum ratio transmission (MRT) and zero-forcing (ZF) precoding. The correctness of the closed-form expressions is verified through simulations. The results show that with the help of satellite and multicast, the average system spectrum efficiency (SE) can be significantly improved.

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Joint user pairing and power allocation scheme based on transmission mode switching between NOMA based maximum ratio transmission and MMSE beamforming in downlink MISO systems

10.21203/rs.3.rs-58837/v2 ◽

2021 ◽

Author(s):

Zhixin Zhao ◽

Dong Wang ◽

Hongwei Zhang ◽

Haitao Sang

Keyword(s):

Power Allocation ◽

Mode Switching ◽

Achievable Rate ◽

Rate Performance ◽

User Pairing ◽

Rate Region ◽

Transmission Modes ◽

Sum Rate ◽

Ratio Transmission ◽

Maximum Ratio Transmission

Abstract IThis paper investigates the design of the joint user pairing and power allocation scheme with transmission mode switching (TMS) in downlink multiple-input-single-output (MISO) systems. Firstly, the closed-form expressions of the boundary of achievable rate region of two candidate transmission modes, i.e., non-orthogonal multiple access based maximum ratio transmission (NOMA-MRT) and minimum mean square error beamforming (MMSE-BF), are obtained. By obtaining the outer boundary of the union of the achievable rate regions of the two transmission modes, an adaptive switching method is developed to achieve a larger rate region. Secondly, based on the idea that the solution to the problem of weighted sum rate (WSR) optimization must be on the boundary of the achievable rate region, the optimal solutions to the problem of WSR optimization for NOMA-MRT and MMSE-BF are obtained for the two-user case, respectively. Subsequently, by exploiting the optimal solutions aforementioned for two transmission modes and the high efficiency of TMS, a suboptimal User pairing and Power Allocation algorithm (JUPA) is proposed to further improve sum-rate performance for the multi-user case. Compared with the Exhaustive Search based user Pairing and Power Allocation algorithm (ES-PPA), the proposed JUPA can enjoy a much lower computational complexity and only suffer a slight sum-rate performance loss, whereas outperforms other traditional schemes. Finally, numerical results are provided to validate the analyses and the proposed algorithms.

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