Sorted QR-Decomposition Based Parallel Detection Algorithm for MIMO Systems

2013 ◽  
Vol 427-429 ◽  
pp. 591-595
Author(s):  
Li Liu ◽  
Jin Kuan Wang ◽  
Xin Song ◽  
Ying Hua Han ◽  
Dong Mei Yan
Keyword(s):  
Maximum Likelihood ◽  
Interference Cancellation ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Detection Algorithm ◽  
Qr Decomposition ◽  
Detection Performance ◽  
System Capacity ◽  
Parallel Detection ◽  
Ml Detection

Multiple input multiple output (MIMO) wireless communication system can increase system capacity enormously. Maximum likelihood (ML) detection algorithm can obtain the optimal detection performance with exponential computational complexity that results it difficulty to use in practice. Classical ordered successive interference cancellation (SIC) algorithm suffers from error propagation and high complexity, so an improved parallel SIC algorithm based on Maximum likelihood (ML) detection is proposed, in which signal detection is performed at two stages. ML detections for one layer is carried out firstly, and redundancy of candidate sequences are selected to perform parallel detection for improving detection performance for next step. Sorted QR decomposition based SIC algorithm are performed in second step in order to reduce calculating complexity. By adjusting the number of candidate sequences, tradeoff between detection performance and calculating complexity can be obtained properly.

Depth-First QRD-M Detection Algorithm for MIMO Systems

2013 ◽  
Vol 347-350 ◽  
pp. 3478-3481
Author(s):  
Li Liu ◽  
Jin Kuan Wang ◽  
Xin Song ◽  
Yin Hua Han ◽  
Yu Huan Wang
Keyword(s):  
Ordered Set ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Detection Algorithm ◽  
Qr Decomposition ◽  
Detection Performance ◽  
Detection Scheme ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Ml Detection

Maximum likelihood (ML) detection algorithm for multiple input multiple output (MIMO) systems provided the best bit error rate (BER) performance with heavy calculating complexity. The use of QR decomposition with M-algorithm (QRD-M) had been proposed to provide near-ML detection performance and lower calculating complexity. However, its complexity still grew exponentially with increasing dimension of the transmitted signal. To reduce the problem, an improved detection scheme was proposed here. After constructing the tree detecting model of MIMO systems, the ML search of one layer was done, the branch metrics were calculated and sorted, which gave an ordered set of the layer, then depth-first search were used to search the left layers with termination methods. The proposed algorithm provides near QRD-M detection performance.

Improved Stack Algorithm for MIMO Systems

2013 ◽  
Vol 333-335 ◽  
pp. 666-669
Author(s):  
Li Liu ◽  
Jin Kuan Wang ◽  
Xin Song ◽  
Yin Hua Han
Keyword(s):  
Bit Error Rate ◽  
Ordered Set ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Detection Algorithm ◽  
Qr Decomposition ◽  
System Capacity ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Ml Detection

Multiple input multiple output (MIMO) systems could increase wireless communication system capacity enormously. The best optimal detection algorithm for MIMO systems was maximum likelihood (ML) detection algorithm, which could provide the best bit error rate (BER) performance for MIMO systems. However, the computational complexity of ML detection algorithm grew exponentially with the number of transmit antennas and the order of modulation, which resulted in difficult using for practice. A modified MIMO signal detection algorithm which combined ML detection with stack algorithm was presented in this paper. After performing QR decomposition of the channel matrix, the ML detection with length L was done firstly. The partial accumulated metrics were calculated and sorted, which produced an ordered set secondly. Based on the ordered set, stack algorithm was performed to search for the symbol with the minimum accumulated metrics. The proposed algorithm reduced the probability of look back in stack algorithm.

Combined QRD-M and Successive Interference Cancellation Detection Algorithm for MIMO Systems

2014 ◽  
Vol 556-562 ◽  
pp. 2834-2837
Author(s):  
Li Liu ◽  
Xin Song ◽  
Ying Hua Han ◽  
Fu Lai Liu ◽  
Jin Kuan Wang
Keyword(s):  
Interference Cancellation ◽  
Mimo Systems ◽  
Detection Algorithm ◽  
Detection Performance ◽  
Successive Interference Cancellation ◽  
Candidate Sequence ◽  
Trade Off ◽  
Simulation Results

In order to get better trade-off between detection performance and calculating complexity, an improved detection algorithm was presented here. QRD-M algorithm is performed for several layers firstly, and successive interference cancellation detection algorithm was used to detect the bottom several layers parallel, and the candidate sequence with smaller PAM was selected out as the answer. Simulation results show the validity of proposed algorithm.

scholarly journals Scheduled QR-BP Detector with Interference Cancellation and Candidate Constraints for MIMO Systems

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3734
Author(s):  
Sangjoon Park
Keyword(s):  
Bipartite Graph ◽  
Interference Cancellation ◽  
Belief Propagation ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Qr Decomposition ◽  
Error Performance ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Updating Procedure

In this paper, a QR-decomposition-based scheduled belief propagation (BP) detector with interference cancellation (IC) and candidate constraints is proposed for multiple-input multiple-output (MIMO) systems. Based on a bipartite graph generated from an upper triangular channel matrix following linear transformation using QR decomposition, the proposed detector performs a sequential message updating procedure between bit nodes. During this updating procedure, candidate constraints are imposed to restrict the number of possible candidate vectors for the calculation of observation-to-bit messages. In addition, after obtaining the soft message corresponding to the bit sequence in each transmit symbol, a hard-decision IC operation is performed to reduce the size of the bipartite graph and indirectly update the messages for the remaining symbols. Therefore, the proposed scheme provides a huge complexity reduction compared to conventional BP detectors that perform message updating by using all related messages directly. Simulation results confirm that the proposed detector can achieve suboptimum error performance with significantly improved convergence speed and reduced computational complexity compared to conventional BP detectors in MIMO systems.

Performance Improvement in Spatially Multiplexed MIMO Systems over Weibull-Gamma Fading Channel

Frequenz ◽  
2016 ◽  
Vol 70 (11-12) ◽  
Author(s):  
Keerti Tiwari ◽  
Davinder S. Saini ◽  
Sunil V. Bhooshan
Keyword(s):  
Interference Cancellation ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Optimal Performance ◽  
Detection Techniques ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Improved Performance ◽  
Ml Detection

AbstractIn multiple-input multiple-output (MIMO) systems, spatial demultiplexing at the receiver has its own significance. Thus, several detection techniques have been investigated. There is a tradeoff between computational complexity and optimal performance in most of the detection techniques. One of the detection techniques which gives improved performance and acceptable level of complexity is ordered successive interference cancellation (OSIC) with minimum mean square error (MMSE). However, optimal performance can be achieved by maximum likelihood (ML) detection but at a higher complexity level. Therefore, MMSE-OSIC with candidates (OSIC

scholarly journals An Improved Jacobi-Based Detector for Massive MIMO Systems

Information ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 165 ◽  
Author(s):  
Xiaoqing Zhao ◽  
Zhengquan Li ◽  
Song Xing ◽  
Yang Liu ◽  
Qiong Wu ◽  
...  
Keyword(s):  
Massive Mimo ◽  
Communication Systems ◽  
Mimo Systems ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Correction Method ◽  
Detection Algorithm ◽  
Detection Accuracy ◽  
Input Multiple Output ◽  
Mmse Detector

Massive multiple-input-multiple-output (MIMO) is one of the key technologies in the fifth generation (5G) cellular communication systems. For uplink massive MIMO systems, the typical linear detection such as minimum mean square error (MMSE) presents a near-optimal performance. Due to the required direct matrix inverse, however, the MMSE detection algorithm becomes computationally very expensive, especially when the number of users is large. For achieving the high detection accuracy as well as reducing the computational complexity in massive MIMO systems, we propose an improved Jacobi iterative algorithm by accelerating the convergence rate in the signal detection process.Specifically, the steepest descent (SD) method is utilized to achieve an efficient searching direction. Then, the whole-correction method is applied to update the iterative process. As the result, the fast convergence and the low computationally complexity of the proposed Jacobi-based algorithm are obtained and proved. Simulation results also demonstrate that the proposed algorithm performs better than the conventional algorithms in terms of the bit error rate (BER) and achieves a near-optimal detection accuracy as the typical MMSE detector, but utilizing a small number of iterations.

scholarly journals Design and VLSI Implementation of a Reduced-Complexity Sorted QR Decomposition for High-Speed MIMO Systems

Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1657
Author(s):  
Lu Sun ◽  
Bin Wu ◽  
Tianchun Ye
Keyword(s):  
Communication Systems ◽  
High Speed ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Cmos Technology ◽  
Qr Decomposition ◽  
Time Sharing ◽  
Hardware Complexity ◽  
Givens Rotation ◽  
Hardware Efficiency

In this article, a low-complexity and high-throughput sorted QR decomposition (SQRD) for multiple-input multiple-output (MIMO) detectors is presented. To reduce the heavy hardware overhead of SQRD, we propose an efficient SQRD algorithm based on a novel modified real-value decomposition (RVD). Compared to the latest study, the proposed SQRD algorithm can save the computational complexity by more than 44.7% with similar bit error rate (BER) performance. Furthermore, a corresponding deeply pipelined hardware architecture implemented with the coordinate rotation digital computer (CORDIC)-based Givens rotation (GR) is designed. In the design, we propose a time-sharing Givens rotation structure utilizing CORDIC modules in idle state to share the concurrent GR operations of other CORDIC modules, which can further reduce hardware complexity and improve hardware efficiency. The proposed SQRD processor is implemented in SMIC 55-nm CMOS technology, which processes 62.5 M SQRD per second at a 250-MHz operating frequency with only 176.5 kilo-gates. Compared to related studies, the proposed design has the best normalized hardware efficiency and achieves a 6-Gbps MIMO data rate which can support current high-speed wireless communication systems such as IEEE 802.11ax.

scholarly journals Massive MIMO-NOMA Networks with Imperfect SIC: Design and Fairness Enhancement

2020 ◽  
Author(s):  
Arthur Sousa de Sena ◽  
Pedro Nardelli
Keyword(s):  
Outage Probability ◽  
Power Allocation ◽  
Interference Cancellation ◽  
Massive Mimo ◽  
Multiple Access ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Optimal Solution ◽  
Input Multiple Output ◽  
The Impact

This paper addresses multi-user multi-cluster massive multiple-input-multiple-output (MIMO) systems with non-orthogonal multiple access (NOMA). Assuming the downlink mode, and taking into consideration the impact of imperfect successive interference cancellation (SIC), an in-depth analytical analysis is carried out, in which closed-form expressions for the outage probability and ergodic rates are derived. Subsequently, the power allocation coefficients of users within each sub-group are optimized to maximize fairness. The considered power optimization is simplified to a convex problem, which makes it possible to obtain the optimal solution via Karush-Kuhn-Tucker (KKT) conditions. Based on the achieved solution, we propose an iterative algorithm to provide fairness also among different sub-groups. Simulation results alongside with insightful discussions are provided to investigate the impact of imperfect SIC and demonstrate the fairness superiority of the proposed dynamic power allocation policies. For example, our results show that if the residual error propagation levels are high, the employment of orthogonal multiple access (OMA) is always preferable than NOMA. It is also shown that the proposed power allocation outperforms conventional massive MIMO-NOMA setups operating with fixed power allocation strategies in terms of outage probability.

scholarly journals Efficient Power Allocation for LDPC-Coded MIMO Systems

2011 ◽  
pp. 127-133
Author(s):  
Layak Ali Sd ◽  
K. Kishan Rao ◽  
M. Sushanth Bab
Keyword(s):  
Interference Cancellation ◽  
Communication Systems ◽  
Mimo Systems ◽  
Geometric Mean ◽  
Multiple Input Multiple Output ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Coded Systems ◽  
Efficient Power ◽  
Q Function

In this papers an efficient ordering scheme for an ordered successive interference cancellation detector is determined under the bit error rate minimization criterion for multiple-input multiple-output(MIMO) communication systems using transmission power control. From the convexity of the Q-function, we evaluate the choice of suitable quantization characteristics for both the decoder messages and the received samples in Low Density Parity Check (LDPC)-coded systems using M-QAM schemes. We derive the ordering strategy that makes the channel gains converge to their geometric mean. Based on this approach, the fixed ordering algorithm is first designed, for which the geometric mean is used for a constant threshold using correlation among ordering results.

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