This paper concentrates on the rate analysis and optimization for a downlink cell-free massive multi-input multi-output (MIMO) system with mixed digital-to-analog converters (DACs), where some of the access points (APs) use perfect-resolution DACs, while the others exploit low-resolution DACs to reduce hardware cost and power consumption By using the additive quantization noise model (AQNM) and conjugate beamforming receiver, a tight closed-form rate expression is derived based on the standard minimum mean square error (MMSE) channel estimate technique With the derived result, the effects of the number of APs, the downlink transmitted power, the number of DAC bits, and the proportion of the perfect DACs in the mixed-DAC architecture are conducted We find that the achievable sum rate can be improved by increasing the proportion of the perfect DACs and deploying more APs Besides, when the DAC resolution arrives at 5-bit, the system performance will invariably approach the case of perfect DACs, which indicates that we can use 5-bit DACs to substitute the perfect DACs Thus, it can greatly reduce system hardware cost and power consumption Finally, the weighted max–min power allocation scheme is proposed to guarantee that the users with high priority have a higher rate, while the others are served with the same rate The simulation results prove the proposed scheme can be effectively solved by the bisection algorithm

https://www.mdpi.com/1424-8220/21/8/2624/pdf

Analysis and Optimization for Downlink Cell-Free Massive MIMO System with Mixed DACs.

The future 6G mobile communication network will support an unprecedented amount of Internet of Things (IoT) devices, which will boost the demand for low cost terminals under the principle of green communication. One of the critical issues for low cost terminals is the sampling rate of analog-to-digital converters (ADCs) at the receivers. A high sampling rate of the ADC gives rise to a high energy consumption and high hardware cost for the terminal. In the conventional multi-user OFDM systems, all users have to sample the received signal with a sampling rate that is larger than or equal to the Nyquist rate, despite only a small fraction of the bandwidth (number of subcarriers) is allocated to each user. This paper proposes a low sampling rate receiver design for multi-antenna multi-user OFDM systems. With the aid of zero-forcing precoding, the sampling rate of the receiver can be reduced to 1/K of the Nyquist rate, where K is the number of users. The simulation results show that with a significant reduction in sampling rate, performance loss is insignificant and acceptable in terms of bit error rate, mutual information and peak-to-average power ratio.

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A Low Sampling Rate Receiver Design for Multi-Antenna Multi-User OFDM Systems

An iteration Phase Noise Estimator for OFDM System

The invention belongs to the technical field of wireless communication and relates to an IQ imbalance compensation method for a large-scale multi-antenna system According to the method, an IQ imbalance parameter is modeled into a random variable, and a statistical characteristic of an equivalent channel can be obtained; then, channel estimation and data detection are carried out, and the IQ imbalance parameter and the channel information are not separately considered; after the IQ imbalance parameter and the channel information are combined into consideration, an accurate IQ imbalance parameter does not need to be obtained by a detector, and only the statistical characteristic of the equivalent channel needs to be obtained In an actual system, the latter is easier to be implemented thanthe former in engineering implementation On the performance, accurate known conditions of the IQ imbalance parameter can be approximated based on channel estimation and signal detection of the equivalent channel, and the method has the advantages that extra expenditure for obtaining accurate IQ parameter lists can be avoided

IQ imbalance compensation method for large-scale multi-antenna system

Few-bit analog-to-digital converter (ADC) is regarded as a promising technique to greatly reduce power consumption of Internet of Things (IoT) devices in millimeter-wave (mmWave) communications. In this work, based on the recently proposed parametric bilinear generalized approximate message passing (PBiGAMP), we propose a new scheme to perform joint symbol detection, channel estimation and decoding. The proposed scheme is flexible to deal with discrete prior on symbols, Gaussian mixture prior on channels and quantized likelihood on observations. Furthermore, we introduce doping factor to control the portion of “extrinsic” and “posterior” information with negligible complexity increase. Since this joint scheme can be implemented via fast Fourier transformation (FFT), the complexity grows only logarithmically. Compared to the benchmark algorithms, numerical results show that the proposed joint scheme can achieve significant performance gain, and demonstrate the effectiveness in dealing with the nonlinear distortion from few-bit ADC.

https://www.mdpi.com/1424-8220/20/7/1857/pdf

A Joint Symbol-Detection, Channel-Estimation and Decoding Scheme under Few-Bit ADCs in mmWave Communications

In this paper, we propose an iterative message passing receiver jointly performing channel, phase noise estimation and symbol detection for multi-input multi-output (MIMO) systems. The joint iterative receiver is designed using message passing techniques: general expectation maximization (GEM) and belief propagation (BP) on factor graphs. Therein, the nonlinear measurement function node and symbol detector are handled in E-step of GEM while the marginal posterior probability density function of channel parameter and phase noise are obtained by BP in M-step. Numerical simulation demonstrates that our proposed receiver outperforms the state-of-the-art soft-input extended Kalman smoothing approach in terms of mean square error, bit error rate and frame error rate with similar computational complexity.

A GEM-BP based receiver for joint estimation and detection in MIMO systems

The invention discloses a compensation method and system under an IQ branch unbalanced condition The method comprises the following steps: S1, acquiring an initial value of each channel parameter under the OFDM system in-phase quadrature IQ branch unbalanced condition; S2, acquiring an estimation value of the IQ branch unbalanced parameter by using a joint message passing algorithm based on a preset factor graph model and the initial value of each channel parameter; and S3, compensating the IQ branch of the OFDM system based on the estimation value of the IQ branch unbalanced parameter By using the compensation method and system under the IQ branch unbalanced condition, the factor graph is constructed, and the edge posterior probability information of each unknown parameter in the OFDM system is received through a message passing method in the factor graph, a problem that the receiver bit error rate performance is lowered under the in-phase quadrature branch unbalance condition is solved, thereby acquiring the reliable bit error performance with low complexity

Cui Jianhua

Papers

A Joint Symbol-Detection, Channel-Estimation and Decoding Scheme under Few-Bit ADCs in mmWave Communications

A GEM-BP based receiver for joint estimation and detection in MIMO systems

Compensation method and system under IQ branch unbalanced condition