scholarly journals SVR Based Blind Signal Recovery for Convolutive MIMO Systems With High-Order QAM Signals

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 23249-23260 ◽  
Author(s):  
Chao Sun ◽  
Ling Yang ◽  
Li Chen ◽  
Jiliang Zhang
Keyword(s):  
Mimo Systems ◽  
High Order ◽  
Signal Recovery ◽  
Blind Signal

A Lineariztion Approach for Blind Signal Recovery in Multipath MIMO Systems with Signal Misalignment

2020 ◽  
Author(s):  
Jiong Li
Keyword(s):  
Blind Deconvolution ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Taylor Series Expansion ◽  
Signal Recovery ◽  
Well Performance ◽  
Recovery Algorithm ◽  
Blind Signal ◽  
Input Multiple Output ◽  
Source Signal

Abstract This paper deals with blind deconvolution for signal recovery in multipath multiple-input multiple-output (MIMO) systems, where the delays of different paths of each source signal from transmit antenna to receive antenna are random. Such a problem is often solved in an ideal state in literature, i.e., each transmitted signal arrives at the receive antennas simultaneously and the arrival time intervals of two adjacent paths are identical. However, the ideal case could not be satisfied in most applications. To address this issue, we propose a blind signal recovery algorithm. Specifically, by using Taylor series expansion to approximate sources, the convolutive MIMO signal recovery problem is transferred into instantaneous blind source separation (BSS) problem. Building on the ideas of second-order blind identification (SOBI), an extended SOBI algorithm is developed to recover the extended sources (including original sources and their derivatives). The simulation results illustrate the well performance and the interest of the proposed algorithm in comparison with other approaches.

High Order PSK Modulation in Massive MIMO Systems with 1-bit ADCs

2020 ◽  
pp. 1-1
Author(s):  
Bule Sun ◽  
Yiqing Zhou ◽  
Jinhong Yuan ◽  
Ya-Feng Liu ◽  
Lu Wang ◽  
...  
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
High Order

scholarly journals Channel Estimation for Broadband Millimeter Wave MIMO Systems Based on High-Order PARALIND Model

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Ting Jiang ◽  
Maozhong Song ◽  
Xiaorong Zhu ◽  
Xu Liu
Keyword(s):  
Channel Estimation ◽  
Millimeter Wave ◽  
Mimo Systems ◽  
Model Simulation ◽  
Path Loss ◽  
Estimation Algorithm ◽  
Multipath Channels ◽  
High Order ◽  
Propagation Path ◽  
Necessary Condition

Channel state information (CSI) is important to improve the performance of wireless transmission. However, the problems of high propagation path loss, multipath, and frequency selective fading make it difficult to obtain the CSI in broadband millimeter-wave (mmWave) system. Based on the inherent multidimensional structure of mmWave multipath channels and the correlation between channel dimensions, mmWave multiple input multiple output (MIMO) channels are modelled as high-order parallel profiles with linear dependence (PARALIND) model in this paper, and a new PARALIND-based channel estimation algorithm is proposed for broadband mmWave system. Due to the structural property of PARALIND model, the proposed algorithm firstly separates the multipath channels of different scatterers by PARALIND decomposition and then estimates the channel parameters from the factor matrices decomposed from the model based on their structures. Meanwhile, the performance of mmWave channel estimation is analysed theoretically. A necessary condition for channel parameter estimation is given based on the uniqueness principle of PARALIND model. Simulation results show that the proposed algorithm performs better than traditional compressive sensing-based channel estimation algorithms.

scholarly journals Signal Detection Based on Parallel Group Detection Algorithm for High-Load Massive MIMO Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Thanh-Binh Nguyen ◽  
Minh-Tuan Le ◽  
Vu-Duc Ngo
Keyword(s):  
Massive Mimo ◽  
Mimo Systems ◽  
Mimo System ◽  
Detection Algorithm ◽  
High Load ◽  
Signal Recovery ◽  
Parallel Group ◽  
Group Detection ◽  
Practical Complexity ◽  
Ber Performance

In this paper, a parallel group detection (PGD) algorithm is proposed in order to address the degradation in the bit error rate (BER) performance of linear detectors when they are used in high-load massive MIMO systems. The algorithm is constructed by converting the equivalent extended massive MIMO system into two subsystems, which can be simultaneously detected by the classical detection procedures. Then, using the PGD and the classical ZF as well as the QR-decomposition- (QRD-) based detectors, we proposed two new detectors, called ZF-based PGD (ZF-PGD) and QRD-based PGD (QRD-PGD). The PGD is further combined with the sorted longest basis (SLB) algorithm to make the signal recovery more accurate, thereby resulting in two new detectors, namely, the ZF-PGD-SLB and the QRD-PGD-SLB. Various complexity evaluations and simulations prove that the proposed detectors can significantly improve the BER performance compared to their classical linear and QRD counterparts with the practical complexity levels. Hence, our proposed detectors can be used as efficient means of estimating the transmitted signals in high-load massive MIMO systems.

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